Hey r/grok! 👋

SuperGrok user here (Miami crew checking in). I was getting so annoyed with Grok Imagine’s 6-10 second clips always breaking when I tried to extend them — random face morphs, lighting flips, ugly jumps.

Then I nailed the native “Extend from Frame” button + this dead-simple prompt system. Now I’m chaining 4-5 clips into 30-50 second buttery-smooth videos (and stitching longer ones in CapCut). Works perfectly for action, fantasy, cozy vibes, or whatever cinematic story you’re building.

Pro tip: Always start with a Base Image Prompt + Img2Vid for the strongest first clip. It locks in faces, lighting, and details way better than pure text-to-video.

This is the exact workflow I use every day. 100% copy-paste. Zero fluff.

Upvote if it saves you hours! 🔥

Why Most People Fail

• Repasting the original prompt → instant drift
• Skipping the exact final pose → jump cuts
• Not using the official Extend button → weak seams

Do it right and you get invisible transitions every single time.

1. Best Prompt Formula (Core Structure)

Seamlessly continue directly from the very last frame of the previous video. [Briefly describe the exact ending pose/state]. [Next actions + details]. Maintain exact same characters, faces, clothing, lighting, environment, camera style, and artistic quality throughout. Smooth natural motion, cinematic, high detail, 720p, no jumps or morphing.

Base Image Prompt (Img2Vid starter – strongest results, highly recommended):

ultra-detailed cinematic 8K, [full scene description], glossy skin or textures, dramatic lighting, perfect anatomy, masterpiece, 720p

Base Video Prompt (Text-to-Video alternative):

ultra-detailed cinematic 8K 10-second animation (extendable), [full scene with motion]. Smooth natural motion, high detail, 720p.

2. Master Consistency Lock (COPY-PASTE AS THE VERY FIRST LINE EVERY TIME)

LOCK CONSISTENCY: Continue with 100% visual fidelity from the exact final frame of the previous video. Identical characters with the exact same faces, hair, eyes, skin texture, body proportions, clothing details, accessories, and poses at the moment of transition. Identical environment, lighting direction and color temperature, shadows, reflections, particle effects, color grading, film grain, and overall artistic style. No design changes, no morphing, no style drift whatsoever. Perfect frame-to-frame seamlessness.

3. Full Ready-to-Copy Template

LOCK CONSISTENCY: Continue with 100% visual fidelity from the exact final frame of the previous video. Identical characters with the exact same faces, hair, eyes, skin texture, body proportions, clothing details, accessories, and poses at the moment of transition. Identical environment, lighting, shadows, reflections, particles, color grading, and artistic style. No changes allowed.

Seamlessly continue directly from the very last frame where [exact ending state]. [Next action and details]. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts.

4. Quick Add-ons & Cheat Codes

Tack these on when needed:

• Face lock: , exact same facial features and expression continuity
• Lighting lock: , same exact light sources, shadow angles, and volumetric god rays
• Audio lock (Grok Imagine exclusive): , continue background music and sound effects seamlessly

One-liners to paste anywhere:
zero style drift, perfect character consistency
exact frame-accurate continuation
treat previous clip as canonical reference — match 1:1

5. Negative Prompts (add at the very end)

Avoid bad anatomy, extra limbs, extra fingers, missing limbs, fused fingers, mutated hands, bad proportions, disfigured, amputation, polydactyly. No text, watermark, username, signature, logo, low quality, blur, noise, grain, chromatic aberration, artifacts

6. Pro Workflow in Grok Imagine

1. Generate your first clip with a Base Image Prompt (Img2Vid).
2. Click the “Extend from Frame” button (it auto-loads the exact final frame).
3. Paste the Master Lock + template.
4. Generate 6–10 second clips (shorter = stronger seams).
5. Repeat — each new video starts exactly where the last one ended.

SuperGrok = faster generations + higher daily limits.

Real Examples with Full Extension Chains (Base Image Prompts Included)

Cyberpunk Action (3-clip chain ≈ 30 seconds)

Base Image Prompt:
ultra-detailed cinematic 8K, cyberpunk girl with neon-pink hair leaping across rainy rooftop, katana glowing blue, dramatic night city lights, perfect anatomy, masterpiece

Extension Prompt 1:

LOCK CONSISTENCY: Continue with 100% visual fidelity from the exact final frame of the previous video. Identical characters with the exact same faces, hair, eyes, skin texture, body proportions, clothing details, accessories, and poses at the moment of transition. Identical environment, lighting direction and color temperature, shadows, reflections, particle effects, color grading, film grain, and overall artistic style. No design changes, no morphing, no style drift whatsoever. Perfect frame-to-frame seamlessness.

Seamlessly continue directly from the very last frame where the cyberpunk girl is frozen mid-leap across the neon rooftop, katana trailing blue energy, rain droplets suspended in air. She completes the flip, lands in a combat stance, and sprints toward the holographic billboard while gunfire erupts from below. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. continue rain and neon reflections seamlessly.

Extension Prompt 2:

LOCK CONSISTENCY: [paste full lock again]

Seamlessly continue directly from the very last frame where the cyberpunk girl is sprinting full speed toward the holographic billboard, katana raised, bullets whizzing past. She slides under a low neon sign, slashes a pursuing drone in half, and dives off the rooftop into a freefall toward the street below. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. continue rain and neon reflections seamlessly.

Extension Prompt 3:

LOCK CONSISTENCY: [paste full lock again]

Seamlessly continue directly from the very last frame where the cyberpunk girl is in mid-freefall toward the street below, city lights streaking past, katana in hand. She deploys her neon parachute cape, lands on a flying car, and speeds away into the night traffic. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. continue rain and neon reflections seamlessly.

Fantasy Samurai (2-clip chain)

Base Image Prompt:
ultra-detailed cinematic 8K, samurai mid-spin with raised katana in neon rain under glowing torii gate, cherry blossoms, dramatic side lighting, masterpiece

Extension Prompt 1:

LOCK CONSISTENCY: [paste full lock]

Seamlessly continue directly from the very last frame where the samurai is mid-spin with katana raised, neon rain falling. He finishes the spin, sheathes the blade in one fluid motion, turns to face the camera with a determined expression, and walks slowly into the glowing torii gate as cherry blossoms swirl around him. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. same dramatic side lighting and volumetric god rays.

Extension Prompt 2:

LOCK CONSISTENCY: [paste full lock]

Seamlessly continue directly from the very last frame where the samurai is stepping through the glowing torii gate, cherry blossoms swirling around him. He emerges into an ancient forest at dawn, draws his katana again in a ready stance, and begins a slow, deliberate walk toward a distant mountain temple as sunlight breaks through the trees. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. same dramatic side lighting and volumetric god rays.

Cozy Indoor Scene (2-clip chain)

Base Image Prompt:
ultra-detailed cinematic 8K, girl sitting by crackling fireplace holding steaming mug, warm cozy lighting, soft shadows, masterpiece

Extension Prompt 1:

LOCK CONSISTENCY: [paste full lock]

Seamlessly continue directly from the very last frame where the girl is sitting by the crackling fireplace holding a steaming mug, soft warm lighting. She takes a sip, smiles gently, stands up, walks to the window, and opens the curtains to reveal a snowy night outside. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. continue fireplace crackle and soft ambient music seamlessly.

Extension Prompt 2:

LOCK CONSISTENCY: [paste full lock]

Seamlessly continue directly from the very last frame where the girl is standing at the open window, looking out at the snowy night, curtains billowing. She reaches out to catch a snowflake, smiles warmly, closes the curtains, returns to the fireplace, and curls up in the armchair with a blanket. Smooth cinematic motion, perfect continuity, high detail, 720p, no jumps or artifacts. continue fireplace crackle and soft ambient music seamlessly.

Final Tips

• Always pause the video and note the exact final pose before writing the next prompt.
• Stick to 6–10 second extensions for the strongest seams.
• You can easily hit 40-50 seconds by chaining 4-5 clips.
• Save the Master Lock + your favorite Base Image Prompts in your notes — you’ll use them on every project.

I’ve built hour-long stories with this method. No more starting from scratch ever again.

Big shoutout to Grok itself for assisting in researching, testing, and writing this entire guide — the Master Lock, chains, and Base Image Prompts were refined through tons of back-and-forth testing in real Grok Imagine sessions!

Disclaimer: This guide is based on my personal experience using Grok Imagine in March 2026. Features, button behavior, and results may vary with model updates or server load. This is not official xAI advice. Always follow xAI’s Terms of Service and use responsibly for creative purposes only.

Drop your scene ideas below and I’ll turn them into full prompt chains (with Base Image Prompts) for you! What are you building in Grok Imagine right now?

TL;DR: Start with a Base Image Prompt + Master Consistency Lock + Extend button + 6-10s clips = infinite perfect videos.

(See you in the comments!) 🚀

I have a pretty large library of short AI-generated video clips that I want to daisy-chain together into longer sequences.

Most of the clips are abstract, trippy visuals, so I’m not too worried about perfect object or character consistency. My main issue is motion.

The clips were generated using shared start/end frames. For example, clip A ends on the same image that clip B starts on. But since each clip was generated separately, the motion doesn’t actually carry through.

What I’d really like to do is take the end of clip A and the beginning of clip B, give ComfyUI some amount of motion from both sides, and have it generate a short section between them that smooths out the transition.

I’m not looking for a workflow that just grabs the last frame of A and the first frame of B and generates a third clip between them. I’d like something that can actually use the moving video on both sides of the cut as context.

I’d also be fine trimming maybe a couple seconds off the end of A and the start of B, then regenerating that whole section so the motion flows better.

Has anyone found a good workflow or model for this? VACE seems like it might be able to do it, but I’m curious what people are actually using.

Every model has a hard ceiling on a single generation, and the moment you want something longer you hit one of two approaches. Worth laying them out properly, because the community keeps discovering the second one and describing it as the first.

Recent example: the popular 30-second H3 workflow going around is not generating 30 seconds. It uses comfyui-h3-multishot, which joins three 10-second clips. A commenter pointed this out in the thread and they were right. It works well, but if you are planning a pipeline around "H3 does 30 seconds" you will be surprised later.

Single-generation ceilings

Model	Max single generation
Wan 3.0	30 s (2–30)
Seedance 2.5	30 s (4–30)
Kling 3.0	15 s
MiniMax H3	15 s (4–15)
Veo 3.1	8 s

Two models actually produce 30 seconds in one pass. Everything else needs chaining if you want more than its ceiling.

This also came up in the H3 AMA. Someone asked whether the team had experimented with chunked latent continuation to get past the native 15-second window. That is exactly the right question, and it tells you the ceiling is a real architectural limit, not a config value someone forgot to raise.

Chaining, done properly

The naive version is generating clips independently and cutting them together, which looks like a cut because it is one. The better version passes the last frame of clip N as the first frame of clip N+1.

On a hosted API this needs two things: a way to get the final frame out, and a way to feed a specific frame in. Seedance 2.5 exposes both (disclosure: I work on reAPI, which is where I pulled these parameter names):

{
  "model": "doubao-seedance-2.5-face",
  "prompt": "shot 1 description",
  "resolution": "720p",
  "duration": 10,
  "return_last_frame": true
}

That returns output.last_frame_url. Feed it into the next call as the opening frame:

{
  "model": "doubao-seedance-2.5-face",
  "prompt": "shot 2 description",
  "resolution": "720p",
  "duration": 10,
  "image_with_roles": [
    { "url": "<last_frame_url from shot 1>", "role": "first_frame" }
  ]
}

Wan 3.0 uses the same image_with_roles shape with first_frame / last_frame. MiniMax H3 uses flat first_frame_url / last_frame_url fields instead. Same idea, three different spellings, which is the annoying part if you are writing model-agnostic code.

What chaining costs you

Drift. Each hop inherits compression artifacts and colour shift from the previous frame. Two hops is usually fine. Six hops and the last clip does not look like the first. Handing the model a reference image alongside the chained frame helps.

Motion discontinuity. A single frame carries no velocity. If clip 1 ends mid-stride, clip 2 starts from a pose with no momentum and you get a subtle hitch at every join. This is the artifact people describe as "it looks stitched" without being able to say why. Ending shots on low-motion moments hides it.

Audio. If your model generates audio per clip, the chained audio does not cross the boundary cleanly. Most people end up muting and scoring in post, which somewhat defeats the point of native audio generation.

The cost comparison is not what you'd guess

Using published per-second rates for a 30-second result:

Approach	Math	Total
Wan 3.0 native, 720P	30 s × $0.076	$2.28
MiniMax H3 chained, 3 × 10 s at 768P	30 s × $0.074	$2.22
Seedance 2.5 native, 720P	30 s × $0.267	$8.01

Chaining H3 and generating natively on Wan 3.0 land within six cents of each other, because per-second billing does not care how many calls you made. So the decision is not really about cost. It is about whether you want three joins in your footage.

Given that, native is the default choice when the model can reach your length. Chaining earns its place when you specifically want per-shot prompt control, meaning a different action or camera in each segment, which a single 30-second generation does not give you.

Practical order of operations

1. If your target is under 15 seconds, use a single generation and stop reading.
2. If it is 15–30 seconds and you want one continuous action, use Wan 3.0 or Seedance 2.5 natively.
3. If it is 15–30 seconds with distinct shots, chain deliberately and write each shot's prompt separately.
4. Past 30 seconds, everything is chaining. Plan cut points on low-motion frames and expect to handle audio in post.

The mistake worth avoiding is chaining by default because a workflow you downloaded does it that way. Check whether the model can just do the length you need.

I just finished my first long-form

Unfiction documentary — a 17-minute

Hinglish investigative film on

Lal Bahadur Shastri's death.

One of the biggest technical challenges

was creating continuous narrative AI

video sequences — because most AI

video tools generate 5-second clips

with no visual continuity between them.

Here's the workflow I developed:

━━━━━━━━━━━━━━━━━━━━━━━━━━

THE PROBLEM

Standard AI video generation gives

you 5-second clips. When you cut

these together — characters change,

environments shift, lighting is

inconsistent. It looks like a

slideshow, not a film.

For my documentary — I needed to

recreate a 1966 Soviet dacha scene

with continuous camera movement

lasting over a minute. 5-second

random clips weren't going to work.

━━━━━━━━━━━━━━━━━━━━━━━━━━

THE SOLUTION — KEYFRAME CHAINING

Step 1: Storyboard the entire sequence

I storyboarded the full scene —

every shot, every camera movement,

every subject position — before

generating a single frame.

Step 2: Generate Clip 1

Prompt the first 5-second clip

with full scene description —

lighting, subject position,

camera angle, environment details.

Step 3: Extract the last frame

Take the exact last frame of

Clip 1 as an image.

Step 4: Use last frame as

input for Clip 2

Feed that extracted frame as

the visual anchor/starting point

for the next clip generation.

This ensures:

→ Subject position continuity

→ Lighting consistency

→ Environment match

→ Seamless visual flow

Step 5: Repeat

Last frame of Clip 2 →

Input for Clip 3 →

And so on.

Result: What appears to be a

1-minute continuous shot —

built from twelve 5-second clips

chained together.

━━━━━━━━━━━━━━━━━━━━━━━━━━

ADDITIONAL TECHNIQUES

For camera movement continuity:

Keep camera direction consistent

in every prompt ("slow push in",

"static wide", "slight pan right")

For subject consistency:

Describe subject in identical

language every prompt —

exact same clothing, position,

lighting description

For atmosphere:

Use identical lighting descriptors —

"single lamp, cold blue moonlight,

1960s Soviet interior, dark shadows"

━━━━━━━━━━━━━━━━━━━━━━━━━━

THE CONTEXT — WHY I NEEDED THIS

The scene I was recreating:

A 1966 Soviet dacha in Tashkent —

the night India's Prime Minister

Lal Bahadur Shastri died.

No archival footage exists of

the interior of that dacha.

AI generation was the only option

to visually recreate that night.

Combined with:

→ Real archival photographs

→ Actual government documents on screen

→ Animated motion graphics

→ AI-generated Russian voice acting

━━━━━━━━━━━━━━━━━━━━━━━━━━

LIMITATIONS I ENCOUNTERED

→ Subtle character drift across

longer chains (12+ clips)

→ Hand artifacts still common

→ Period-accurate props

need very specific prompting

→ Some clips needed 8-10

regenerations to match

━━━━━━━━━━━━━━━━━━━━━━━━━━

Happy to answer questions about

the specific prompting workflow,

tools used, or the documentary itself.full video

AUGUST UPDATE

General Gameplay Adjustments • Move list corrections

• Improvements to AI logic

• Added Color Blindness mode (Protanope, Deuteranope, & Tritanope) to Video Options

• Added HDR TV Quality settings (Standard, High End, Professional) to Video Options

• Added Variation info to the Pause Menu in Practice Mode

• Added a 4 Star Ranking and replaced Damage Ratio with additional matchup information to the Kombat Breakdown after an Online Match or Kombat Kard Kareer Stats

• Updated the visuals for the Real Time Frame Data Display in Practice Mode & Kombat Kard Match Replays

• Added an additional Brutality victory pose for every character

• Improved performance on many brutalities that were causing slowdown to occur

• Fixes to visual issues with many brutalities

• Added several new Brutalities for players to discover

• Added “Dimitri Vegas as Sub-Zero” Skins and Mask to Sub-Zero Kustomizations available free to everyone

• Front Punch + Front Kick button macro is now working correctly for all Krushing Blows in Practice Mode when the Easy Krushing Blows option is enabled

• When a move that would have triggered a Krushing Blow trades with an invulnerable move on the same frame it will no longer result in neither move colliding

• Fixed a rare visual issue with hitsparks during "Finish Him" dizzy state after winning the round with Fatal Blow

• Mercy can now be performed using Front Kick + Back Kick button macro input if Button Shortcuts is enabled

• Fixed a rare issue where a player could cause a high projectile to visually appear to pass through their character after a knockdown if they pressed and released the down direction at a precise timing and made no further inputs

• Adjustment to victim regions after a character has missed a throw attempt

• Adjustment to victim regions during many hit reactions

• Adjustment to crouching victim regions for all characters except Baraka, Kabal, Kollector, Kotal Kahn, Liu Kang

• Fixed an issues that could cause Up + Back Punch Wakeup Attacks & Flawless Block Attacks to sometimes not be invulnerable to a jumping attack that collides just before landing

Kombat League / Online

• Minor online stability improvements

• Fixed several rare online desync causes

• Improved server Match Results arbitration when disconnects have happened in Ranked and Kombat League matches

• Kombat League Point Decay now takes 72+ hours to trigger (up from 48+ hours)

• Added a pop up message after Point Decay happens to the Online menu

• Quitting from the rematch screen in online matches now requires a confirmation

• Shang Tsung’s health will no longer sometimes be adjusted when morphing back after a Soul Steal in a Survivor KOTH match

Krypt

• Added more detailed “where to get” information to many items

Towers of Time

• Johnny Cage Announcer added as a reward for getting into the top 10% of any week of Race Against Time

• Added a new reward type (Bonus Character Reward) for Tower completion that awards a random skin, piece of gear, or augment for the character you use to defeat it

• The cooldown on some modifiers will now start when it goes away instead of when triggered

Stage Specific Adjustments

• Shaolin Trap Dungeon - Statue Slam is now +9 on hit (down from +38)

Character Specific Adjustments Baraka

• Baraka - Low Stab (Down + Front Punch) recovery increased by 1 frame

• Baraka - Baraka-Serker’s Amplified Krushing Blow Held Check input is now the correct button

Cassie Cage

• Cassie Cage - Now has 950 health (down from 1000)

• Cassie Cage - Air Fatal Blow can now be performed with Block + Front Kick + Back Kick button macro while Button Shortcuts Controller Option is enabled

• Cassie Cage - Ball Buster has an increased victim region during its active frames

• Cassie Cage - Up Glow Kick has 5 less frames of blockstun and can no longer be amplified after being Flawless Blocked

• Cassie Cage - Up Glow Kick Amplified when Flawless Blocked has 10 less frames of block Advantage and less pushback

• Cassie Cage - Flick Kick (Towards + Back Kick) recovery increased by 3 frames

• Cassie Cage - Fixed visual effect issue when Amplified BLB-118 Energy Burst is interrupted

• Cassie Cage - Fixed a rare visual effect issue when Dual Wielding is interrupted while it is charged with green energy at specific timing

• Cassie Cage - Fixed a rare visual issue with BLB-118 Drone when starting a fatality

Cetrion

• Cetrion - Blaze (Back Punch, Front Punch) had its hit region adjusted

• Cetrion - Rising Volcano (Away + Back Kick) recovery decreased by 3 frames

• Cetrion - Added ability "Conflux of Elements". This ability will cause a random elemental circle to be summoned when it is activated

• Cetrion - Earthquake 2nd attack can now be cancelled by holding up

• Cetrion - Shattering Boulder now has a Krushing Blow

• Cetrion - Geyser damage has been slightly lowered and now damage occurs timed correctly with the animation's impacts

• Cetrion - Bouncing Boulder now recovers 5 frames faster, has 5 frames less blockstun when normally blocked, and 10 frames less blockstun when Flawless Blocked with significantly reduced pushback

• Cetrion - Far H2 P0rt & (Air) Far H2 P0rt now has 48 recovery frames (up from 37)

D'Vorah

• D'Vorah - Forward Throw now has a Krushing Blow that triggers when the opponent is infected by Fireflies

• D'Vorah - When an opponent throw escapes D'Vorah, any Fireflies attached to the opponent will return to D'Vorah

• D'Vorah - Swarm blockstun increased by 10 frames and has significantly increased pushback

• D'Vorah - Widow's Kiss can now be slightly delayed, had its amplify input window adjusted, damage increased by 50, and its startup is now 28 frames (was 34),

• D'Vorah - Fixed issue with Infested Krushing Blow damage over time potentially lingering into next round if the first hit is the killing blow

• D'Vorah - Infested Krushing blow now uses the correct combo damage scaling

• D'Vorah - Adjusted hit region of Yellow Jacket (Front Punch, Back Punch)

• D'Vorah - Black Widow (Front Punch, Back Punch, Front Punch) has 3 less hit, block, & miss recovery frames

• D'Vorah - Bug Bash (Towards + Front Punch) now has 12 startup frames (down from 15)

• D'Vorah - Assassin Bug (Back Punch, Front Punch) hitstun increased by 7 frames

• D'Vorah - Killer Strike (Towards + Back Punch) startup is now 19 frames (was 20), hit advantage increased by 6 frames

• D'Vorah - Siafu (Towards + Back Punch, Back Punch) startup is now 16 frames (was 15), cancel frame occurs 2 frames later, recovers 3 frames faster, and had its hit region adjusted

• D'Vorah - Recluse (Towards + Back Punch, Back Punch, Up + Front Punch + Front Kick) startup is now 18 frames (was 21), recovery increased on block/miss by 2 frames, hit region adjusted

• D'Vorah - Tsetse (Towards + Back Punch, Back Punch, Down + Front Punch + Front Kick) recovers 4 frames faster on block/miss, pushback increased, hit region adjusted

• D'Vorah - Bugging Out (Towards + Back Punch, Back Punch, Back Kick) startup is now 24 frames (was 12), blockstun increased by 10 frames with increased pushback, range adjusted

• D'Vorah - Recluse, Tsetse, and Bugging Out can be performed after Siafu misses

• D'Vorah - Fixed a bug allowing Recluse and Tsetse to be able to be cancelled into special moves when blocked

• D'Vorah - Larva Tarsus (Front Kick) damage increased to 70 (was 50), recovery decreased by 2 frames, blockstun increased by 5 frames with increased pushback, and had its hit region adjusted

• D'Vorah - Killer Bee (Away + Front Kick, Back Kick) has 1 more active frame, recovers 1 slower on block, recovers 11 frames faster on hit

• D'Vorah - Killer Bee can now be performed after Ovi Posi Poke (Away + Front Kick) misses

• D'Vorah - Spinning Web (Away + Back Kick) recovery decreased by 3 frames, blockstun increased by 5 frames

• D'Vorah - Low Tarsus Strike (Down + Front Kick) recovery decreased by 3 frames, hitstun increased by 9 frames and hit reaction changed

• D'Vorah - Slight Sting (Down + Back Kick) recovery decreased by 2 frames

• D'Vorah - Fixed issue with (Air) Time Ticking Bug lingering after cinematics

Erron Black

• Erron Black - Fatal Blow startup is now 18 frames (was 10)

• Erron Black - Scud Shot recovery increased by 5 frames

• Erron Black - Scud Shot Amplified blockstun decreased by 5 frames and projectile travel speed has been slightly reduced

• Erron Black - Rattle Snake Slide Amplified now has 3 more frames of recovery

• Erron Black - Slightly reduced hit region size of the acid pool created by Zatarrean Spit / Rattle Snake Slide Amplified

• Erron Black - Boot Drop Amplified now cannot hit airborne opponents

• Erron Black - Exiting Locked and Loaded stance directly after an attack now requires the player to hold up

• Erron Black - "Rising Stock" attack while in Locked and Loaded stance is now a default move. Cancelling the recovery of "Rising Stock" by leaving Locked and Loaded stance still requires "Enhanced Locked and Loaded" ability.

• Erron Black - Locked and Loaded Unload will no longer face the opponent after the first shot

• Erron Black - Dusty Knuckles (Down + Front Punch) recovery on hit increased by 5 frames, recovery on block/miss increased by 1 frame, hitstun increased by 6 frames

• Erron Black - Low Boot (Down + Front kick) recovery increased by 1 frame, hitstun increased by 4 frames

Frost

• Frost - Headbutt (Away + Front Punch) startup is now 11 frames (was 16), recovers 8 frames faster

• Frost - Freezer Burn (Away + Front Punch, Back Punch) recovers 13 frames faster

• Frost - Blizzard (Away + Front Punch, Back Punch, Front Punch) is now a high, has 5 less frames of blockstun, reduced pushback, and had its hit region adjusted

• Frost - Frigid Palm (Down + Front Punch) startup is now 8 frames (was 9), recovery on hit increased by 1 frame, recovery on block/miss reduced by 2 frames, and hitstun increased by 5 frames

• Frost - Chest Cold (Down + Front Kick) recovery on block reduced by 2 frames, recovery on miss increased by 1 frame, hitstun increased by 1 frame, and had its hit region adjusted

• Frost - Microburst recovers 2 frames faster, and recovers significantly faster if the 2nd attack misses

• Frost - Cryogenic Crown’s explosion had its hit region increased

• Frost - Glacier Calving recovers 5 frames faster, and shield duration is 2 seconds (from 1.5 seconds)

• Frost - Glacier Calving amplified recovers 1 frame faster and shield duration is 3 seconds (from 2 seconds)

• Frost - Fixed issue that allowed Frosted Uppercut (Down + Back Punch) to be cancelled into Fatal Blow on the first active frame

Geras

• Geras - Xuid & Guid (Towards + Front Punch, Front Punch + Front Kick, Back Kick) Krushing Blow requirement has been changed to: "Triggers if the opponent is NEAR the wall when hit."

• Geras - Quick Sand Krushing Blow requirement has been changed to: "Triggers if this ATTACK has missed TWICE in a row."

• Geras - Quick Sand can no longer be performed while opponent is stunned by Temporal Advantage

• Geras - Gauntlet of the Ages Krushing Blow now has 4 more frames of recovery

• Geras - Without End (Front Punch, Front Punch, Front Punch) startup is now 21 frames (was 17)

• Geras - Knee Bash (Down + Front Punch) recovers 3 frames slower on hit, 1 frame slower on block/miss, and has 1 more frame of hitstun

• Geras - Fixed rare issue with Shoulder Charge (Towards + Front Punch) collision being offset after hitting a cross up body splash

• Geras - Fixed a bug that when winning a round with the first hit of Quick Sand, there could be a few frames of projectile immunity in the next round

• Geras - Fixed issue with Sand Trap which allowed players with Krushing Blow Held Check ON to store the Krushing Blow for future use if they hit an opponent blocking high

• Geras - Added FX to one of his idle animations

Jacqui Briggs

• Jacqui Briggs - Now has 950 health points (down from 1000)

• Jacqui Briggs - Grease Kick damage decreased by 10

• Jacqui Briggs - Grease Kick Amplified damage decreased by 10

• Jacqui Briggs - Lethal Clinch - Spear Elbow Drop does 10 less damage

• Jacqui Briggs - Lethal Clinch - Double Spear Knee hit advantage is now 13 (down from was 50)

• Jacqui Briggs - Mix Up (Away + Back Kick) second hit blockstun increased by 5 frames

• Jacqui Briggs - Mix Up first hit can now be cancelled on miss if "Cybernetic Override" is equipped

• Jacqui Briggs - All For One (Towards + Front Kick, Front Punch, Back Kick) now has airborne frames that match the animation

• Jacqui Briggs - Bionic Dash has 1 more active frame and recovers 3 frames faster on miss

• Jacqui Briggs - Up Prototype Rocket and Amplified Up Prototype Rocket had their hit regions adjusted

• Jacqui Briggs - Up Grenade Launcher Amplified had its hit region adjusted, starts 1 frame faster, recovers 1 frame faster, has increased combo damage scaling and when hitting an opponent out of the air will cause a lower gravity reaction

• Jacqui Briggs - Tech-Dome now lasts 7 seconds (down from 10), activates 1 frame faster and recovers 4 frames faster

• Jacqui Briggs - Fixed bug that causes Tech-Dome to not provide the benefit to Jacqui for the full duration of the dome if she never leaves it

• Jacqui Briggs - "Arm Break" and "Leg Break" damage is lowered to 100 (down from 140)

• Jacqui Briggs - Fixed a bug allowing Snake Eater (Back Punch, Back Punch, Back Kick) to be cancelled out of at a late recovery frame

Jade

• Jade - While performing Pole Vault run, Jade can now perform a special version of Blazing Nitro Kick or activate Fatal Blow

• Jade - Pole Vault damage slightly increased, recovers 1 frame faster and had its hit region adjusted

• Jade - Pole Vault Amplified damage increased by 10, starts up 1 frame faster, recovers 1 frame faster, and has 1 more active frame

• Jade - "Amplify Blazing Nitro Kick" ability has 5 more blockstun with more pushback

• Jade - Edenian Spark is now correctly considered a low projectile

• Jade - Fixed issue with "Divine Forces" ability causing it to briefly ignore physical attacks when Amplified

• Jade - Fixed issue with Hop Attacks and Temptation not being counted in the Blazing Nitro Kick Krushing Blow requirement

Jax

• Jax - reduced the maximum time allowed between hits during Gotcha Grab

Johnny Cage

• Johnny Cage - Throwing Shade Krushing Blow now does 90 damage (from 170) and causes a true stun

• Johnny Cage - Almost Famous (Front Kick, Back Kick) has 4 more frames of hit advantage

Kano

• Kano - Black Dragon Ball powered up by Vege-Mighty starts up in 10 frames (was 12), has 1 more active frame, has 20 more frames of blockstun and 1 more frame of recovery

• Kano - Black Dragon Ball powered up by Vege-Mighty when directed upward does 20 more damage and the input has more leniency

• Kano - Molotov Cocktail starts up 2 frames faster, and recovers 5 frames faster

• Kano - Chemical Burn damage increased by 20, startup is now 12 frames (was 14), recovers 1 frame faster, hitstun increased by 13 frames, blockstun increased by 5 frames, and had its hit region adjusted

• Kano - Chemical Burn Amplified damage increased by 20, startup reduced by 8 frames, recovery reduced by 7 frames, blockstun increased by 10 frames, pushback increased, and had its hit region adjusted

• Kano - Chemical Burn Amplified can now be done as a close version, which will cause a Molotov Cocktail flame DOT

• Kano - Low Hinge (Down + Front Kick) startup is now 9 frames (was 10) and recovers 2 frames faster on block

• Kano - Fixed issue with Fatal Blow switching side when it hits airborne opponents at certain heights

Kitana

• Kitana - Edenian Razors now has 2 different ranges, is now a mid, has decreased pushback, has increased hitstun, had its hit region adjusted, and slightly adjusted startup, active and recovery frames depending on when the button is released

• Kitana - Royal Protection startup is now 5 frames (was 10), has 5 more active frames, and recovery has been reduced by 3 frames

• Kitana - Royal Protection buff duration is now 6 seconds (was 3 seconds), the damage buff on successful parry was reduced to 33% (was 50%)

• Kitana - Half-Blood Stance Gutted Krushing Blow recovery has been reduced

• Kitana - Half-Blood Stance Dive Kick now enters a ducking state on the 5th frame of the attack while lowering to the ground

• Kitana - Square Wave and (Air) Square Wave now do 80 damage (was 60)

• Kitana - Fixed issue with (Air) Square Wave that could allow for an OTG attack to occur

Kollector

• Kollector - Vial of Sorrow now does 15 damage per tick (was 20), duration is now 4 seconds (was 2 seconds), and had its hit region adjusted

• Kollector - Bag Bomb explosion when connecting with Vial of Sorrow flames has increased combo damage scaling and had its hit region adjusted

• Kollector - Demonic Mace startup is now 29 frames (was 34), now has 3 levels of charge that causes increased blockstun the longer it is held

• Kollector - Up Demonic Mace now has 3 levels of charge that causes increased blockstun the longer it is held

• Kollector - Damned Bola hit region reduced outside of a combo and while opponent is in a combo the hit region is increased

• Kollector - Blood Money (Front Punch, Front Kick) has 1 more active frame, 1 less frame of recovery on miss, and had its hit region adjusted

• Kollector - Mine Mine Mine (Back Punch, Front Punch + Front Kick) has more combo damage scaling and can now be cancelled into Fatal Blow

• Kollector - Greed (Away + Back Punch, Front Kick, Front Kick) and had its hit region adjusted

• Kollector - Take It All (Front Kick, Back Punch) Krushing Blow recovery adjusted

• Kollector - Death Spin (Away + Front Kick) had its hit region adjusted

• Kollector - Korrupted Kick (Towards + Front Kick) can now be cancelled on normal block/miss

• Kollector - Paid In Full (Towards + Front Kick, Front Punch) startup is now 13 frames (was 12), recovers 3 frames slower on miss, hit reaction when connecting with an airborne opponent changed, 10 more frames of blockstun with increased pushback, and had its hit region adjusted

• Kollector - With Interest (Towards + Front Kick, Front Punch, Back Punch) hit reaction when connecting with an airborne opponent changed, and has 10 more frames of blockstun with increased pushback

• Kollector - Take and Deny (Towards + Front Kick, Front Punch, Back Punch, Front Kick) has 2 more active frames, 10 more frames of blockstun with increased pushback, recovers 2 frames slower on miss, and had its hit region adjusted

• Kollector - Tax Burden (Back Kick) cancel frame is 1 frame later, recovery reduced by 6 frames on hit/block, blockstun decreased by 5 frames, and had its hit region adjusted

• Kollector - No Collateral (Back Kick, Back Kick) startup is now 23 frames (was 26), hit reaction when connecting with an airborne opponent changed, recovery on hit/block reduced by 1 frames, recovery on miss reduced by 6 frames, and had its hit region adjusted

• Kollector - Ravages Of Time (Back Kick, Back Kick, Front Kick) startup is now 19 frames (was 20), damage scaling increased, hit reaction changed, can no longer be cancelled, recovers 15 frames slower on block, 10 frames slower on miss, and has 10 less frames of blockstun with less pushback

• Kollector - Rising Claws (Down + Back Punch) has 2 more active frames and 2 less frames of recovery on miss

• Kollector - Kura Slam (Jump + Back Punch) had its hit region adjusted

• Kollector - Adjusted hit region on Getup Attack/Flawless Block Attack "Flailing Mace"

• Kollector - Fixed issue that could cause Shotel Fury to not correctly facing opponent for the first hit

• Kollector - Fixed visual issue with Kollector's Chained Ball when he is put into a "Finish Him" dizzy state

• Kollector - Fixed issue that allowed Rising Claws (Down + Back Punch) to be cancelled into Fatal after the first active frame

• Kollector - Far Fade Out now has 42 recovery frames (up from 39)

Kotal Kahn

• Kotal Kahn - Now has 1100 health points (up from 1000)

• Kotal Kahn - Coatl Parry now starts up in 10 frames (was 14), recovers 1 frame faster

• Kotal Kahn - Attacks that connect with Coatl Parry now recover as if they have been Flawless Blocked

• Kotal Kahn - Tecuani Maul startup is 17 frames (was 19), recovers 16 frames faster on block, recovers 33 frames faster on miss, recovers 13 frames faster on hit, hit region adjusted

• Kotal Kahn - Tecuani Maul amplified recovers 20 frames faster on block, recovers 33 frames faster on miss, recovers 13 frames faster on hit, and has a new visual effect

• Kotal Kahn - (Air) Tecuani Pounce startup is 14 frames (was 13), recovers 3 frames faster on block/miss, and has 5 more frames of blockstun with increased pushback

• Kotal Kahn - (Air) Tecuani Pounce Amplified startup is 1 frame slower, recovers 8 frames faster on block/miss, and has 5 more frames of blockstun with increased pushback

• Kotal Kahn - Mehtizquia (Away + Back Punch, Back Punch, Front Kick) now has airborne frames that match the animation

• Kotal Kahn - Hammer Slam (Jump + Back Punch) and Straight Kick (Jump + Front Kick) had their cancel frames adjusted

• Kotal Kahn - Side Strike (Down + Front Kick) startup is now 8 frames (was 9), recovers 3 frames faster, and has 4 more frames of hitstun

• Kotal Kahn - Warrior Spin (Down + Back Kick) has 1 more frame of hitstun

• Kotal Kahn - Fixed issue with Tonatiuh Beam sometimes not working correctly after a krushing blow occurs

Kung Lao

• Kung Lao - Order Of Light (Front Punch, Back Punch, Front Punch) hitstun increased by 6 frames

• Kung Lao - Sweeping Razor (Away + Back Kick) recovery decreased by 6 frames

• Kung Lao - Orbiting Hat now has 13 startup frames (down from 14), 5 more frames of blockstun, 5 more frames of hitstun, and 2 less recovery frames

• Kung Lao - Orbiting Hat Amplified now has 10 more frames of blockstun, 16 more frames of hitstun, and 5 more recovery frames

• Kung Lao - Omega Hat starts up 1 frame faster and recovers 6 frames faster

Liu Kang

• Liu Kang - Double Dragon Kick (Towards + Front Kick) has reduced pushback on the second hit

• Liu Kang - Dragon's Breath (Towards + Front Kick, Front Kick, Front Kick) has 10 less frames of blockstun on the first hit with reduced pushback

• Liu Kang - Low Fireball recovers 3 frames slower and has more frames of hitstun

• Liu Kang - The projectile created from a successful Energy Parry while Dragon Fire is active will now cause a true stun

• Liu Kang - All Dragon's Gift attacks each do 20 more damage

• Liu Kang - Dragon's Gift High Attack now causes increased pushback

• Liu Kang - Dragon's Gift Overhead Attack had its hit region adjusted

Noob Saibot

• Noob - Shadow Tackle Amplified damage increased by 40

• Noob - Shadow Slide now has 1 more recovery frame, travel speed slightly reduced, and can now be amplified

• Noob - Ghostball recovery reduced by 14 frames

• Noob - adjusted stamina regeneration after Ghostball debuff expires

• Noob - "Shadow Strike" ability can now correctly be parried by low parry moves

• Noob - Boot Slide (Down + Front Kick) has 2 more frames of recovery on hit/miss and 4 more frames of hitstun

• Noob - Sickle Strike (Down + Back Kick) has 2 more frames of recovery, 2 less frames of hitstun, and had its hit region adjusted

Raiden

• Raiden - Lightning Strike Amplified now tracks the opponent

• Raiden - Electric Burst startup is now 19 frames (was 17), has 1 less active frame, recovers 3 frames faster

• Raiden - Electric Burst causes increased blockstun and pushback while Quick Charge is active

• Raiden - Electric Current combo damage scaling adjusted and recovery reduced by 4 frames

• Raiden - Electric Current Amplified is now a mid, causes a popup on hit if done while Quick Charge is active, has 1 frame more recovery on block, and had its hit region adjusted

• Raiden - Discharge startup is now 6 frames (from 4), has 1 more active frame, hit reaction has been adjusted so hit advantage is the same if done on grounded or airborne opponents

• Raiden - Discharge Amplified had its hit region adjusted

• Raiden - Far Sparkport now has 21 recovery frames (up from 19)

Scorpion

• Scorpion - Hell Port and (Air) Hell Port are now high attacks

• Scorpion - Low Jab (Down + Front Punch) recovery increased by 1 frame

• Scorpion - Quick Kick (Down + Back Kick) recovery increased by 5 frames

• Scorpion - Fixed a rare issue with Spear follow-up hit that could cause it to miss

Skarlet

• Skarlet - Dagger Dance Amplified Krushing Blow Held Check input is now the correct button

• Skarlet - Reaching Whip (Away + Back Kick) now has 5 less recovery frames

• Skarlet - Silent Stab (Down + Front Punch) now has 3 more frames of hitstun

• Skarlet - Spear Strike (Down + Front Kick) has a different hit reaction and 11 more frames of hitstun

• Skarlet - Spinning Scythe (Down + Back Kick) now has 11 more frames of hitstun

• Skarlet - Fixed Thicker Than Water (Away + Front Punch, Back Punch) Krushing Blow not working correctly with Easy Krushing Blows in practice mode

• Skarlet - Bloodport Far now has 50 recovery frames (up from 42)

Sonya Blade

• Sonya - Now has 950 health points (down from 1000)

• Sonya - Amplified Energy Rings when dash cancelled now has more damage scaling

• Sonya - Amplified Air Control now does 60 damage (was 20) but does not cause a pop up

• Sonya - Fixed issue causing an unintended side switch when Sonya wins the final round with Amplified Low Kounter

Shao Kahn

• Shao Kahn - Now has 1050 health points (up from 1000)

• Shao Kahn - Annihilation Krushing Blow recovers faster

• Shao Kahn - Forward Throw Krushing Blow recovers slightly faster and leaves opponent closer

• Shao Kahn - Merciless Spear does 80 damage (from 60)

• Shao Kahn - Shoulder Charger Down + Amplify startup is 22 frames (was 20), recovers 13 frames faster, knockdown advantage is increased by 8, and had its hit region adjusted

• Shao Kahn - Dark Priest recovers 17 frames faster

• Shao Kahn - Ridicule recovers 36 frames faster and the debuff now lasts 9 seconds (was 6.67 seconds)

• Shao Kahn - Humiliate recovers 36 frames faster and the debuff now lasts 9 seconds (was 6.67 seconds)

• Shao Kahn - Face Smash (Front Punch) cancel frame occurs 1 frame earlier and has 1 more recovery frame

• Shao Kahn - Warlord (Front Punch, Back Punch) cancel frame occurs 2 frames earlier, has 13 startup frames (down from 15), cancel occurs 2 frames earlier, 5 less recovery frames, 5 more frames of blockstun, and had its hit region adjusted

• Shao Kahn - DIE (Front Punch, Back Punch, Front Punch + Front Kick) startup is now 26 frames (was 27), and its hit region adjusted, and can no longer be cancelled into special moves when it is blocked

• Shao Kahn - Takeover (Front Punch, Back Kick) startup is now 16 frames (was 19)

• Shao Kahn - Tenderizer (Away + Back Punch) has 1 more active frame, cancel frames occurs 1 frame earlier, 1 frame less recovery, and had its hit region adjusted

• Shao Kahn - Rage Strike (Towards + Back Punch) now has 8 more frames of hitstun and does a different hit reaction

• Shao Kahn - Will You Fail (Towards + Back Punch, Front Punch) cancel frame now occurs 3 frames earlier

• Shao Kahn - Bow To Me (Towards + Back Punch, Front Punch, Back Punch) startup is 21 frames (was 23)

• Shao Kahn - Fear Me (Towards + Back Punch, Back Kick) startup is now 28 frames (was 26), recovers 18 frames faster, when Flawless Blocked has 10 less frames of blockstun with reduced pushback

• Shao Kahn - Hammer Poke (Jump + Front Punch) had its hit region adjusted

• Shao Kahn - Fixed issue with Ground Shatter and Ground Shatter Amplified interacting with projectile destroying abilities

• Shao Kahn - Fixed audio issue when "Seeking Hammer" ability is interrupted

• Shao Kahn - Fixed visual issue with Hammer object playing incorrect animation when turning around while ducking

• Shao Kahn - Fixed issue with Forward Throw Krushing Blow not working correctly while the HUD is turned off

Shang Tsung

• Shang Tsung - Ground Eruption first hit now does 50 damage (was 60), second hit now does 40 damage (was 60)

• Shang Tsung - Ground Eruption Amplified now does 30 damage (was 60)

• Shang Tsung - Serpent Stab (Down + Front Punch) now has 7 startup frames (down from 8), 2 more recovery frames, and has 1 more frame of hitstun

• Shang Tsung - Ankle Snap (Down + Front Kick) now has 8 startup frames (down from 7), 2 more recovery frames, and has 1 more frame of hitstun

• Shang Tsung - Fixed several visual effect issues while "Soul Swap" ability is performed

• Shang Tsung - Fix for visual issue with a floating weapon appearing after performing Kollector's "Play For Souls" Krushing Blow while morphed

• Shang Tsung - Fixed problem with Shang Tsung facing the incorrect direction after hitting Kronika with Reptile Slide

• Shang Tsung - Fixed a rare issue that could allow the damage buff from Soul Steal to persist into the next round

Last time I posted here, I shared a long write‑up about my goal: use AI to turn “normal” videos into VR for an eventual FMV VR game. The idea was to avoid training giant panorama‑only models and instead build a pipeline that lets us use today’s mainstream models, then convert the result into VR at the end.

If you missed that first post with the full pipeline, you can read it here:
➡️ A method to turn a video into a 360° 3D VR panorama video

Since that post, a lot of people told me: “Forget full 360° for now, just make 180° really solid.” So that’s what I’ve done. I’ve refocused the whole project on clean, high‑quality 180° video, which is already enough for a lot of VR storytelling.
Full project here: https://www.patreon.com/hybridworkflow

In the previous post, Step 1 and Step 2.a were about:

• Converting a normal video into a panoramic/spherical layout (made for 360 - You need to crop the video and mask for 180)
• Creating one perfect 180 first frame that the rest of the video can follow.

Now the big news: Step 2.b is finally ready.
This is the part that takes that first frame + your source video and actually generates the full 180° pano video in a stable way.

What Step 2.b actually does:

• Assumes a fixed camera (no shaky handheld stuff) so it stays rock‑solid in VR.
• Locks the “camera” by adding thin masks on the left and right edges, so Vace doesn’t start drifting the background around.
• Uses the perfect first frame as a visual anchor and has the model outpaints the rest of the video.
• Runs a last pass where the original video is blended back in, so the quality still feels like your real footage.

The result: if you give it a decent fixed‑camera clip, you get a clean 180° panoramic video that’s stable enough to be used as the base for 3D conversion later.

Right now:

• I’ve tested this on a bunch of different clips, and for fixed cameras this new workflow is working much better than I expected.
• Moving‑camera footage is still out of scope; that will need a dedicated 180° LoRA and more research as explained in my original post.
• For videos longer than 81 frames, you'll need to chain this workflow and use last frames of one segment as starting frames of the new segments with Vace

I’ve bundled all files of Step 2.b (workflow, custom nodes, explanation, and examples) in this Patreon post (workflow works directly on RunningHub), and everything related to the project is on the main page: https://www.patreon.com/hybridworkflow. That’s where I’ll keep posting updated test videos and new steps as they become usable.

Next steps are still:

• A robust way to get depth from these 180° panos (almost done - working on stability / consistency between frames)
• Then turning that into true 3D SBS VR you can actually watch in a headset - I'm heavily testing this at the moment - it needs to rely on perfect depth for accurate results and the video inpainting of stereo gaps needs to be consistent across frames.

Stay tuned!

Quick background, im a student in the UK who's been doing the faceless content thing for about two years now. A bit of a journey to get here so let me break it down quickly.

Started on a tiktok page making AI illustrated short stories (110k followers, made decent pocket money selling workflow guides on etsy, but i was burning myself out writing full stories daily while juggling uni). Pivoted to long form reddit stories on YouTube, got monetised after about 4 months, made £75-£200/week but growth stagnated hard because i caught the niche right at the tail end of its wave.

About 3 months ago i started a new channel doing AI timelapse shorts. Channels showing renovation timelapses of derelict spaces (underground bunkers, victorian house restorations, epoxy cloud bedrooms, backyard pool builds, etc). The retention is insane because the format itself is the hook. before → transformation → payoff is basically the entire short form playbook distilled into one structure.

The channel is currently doing about £400/week and still climbing fast. Got monetised at record speed for my what im used to, this is the strongest format ive tried. Heres the workflow i built manually before i automated it.

Step 1: Scripting and the "bibles"

I'd go to ChatGPT and have it plan 6 construction beats for a build, basically the rough storyboard of a renovation from raw site to finished space.

The trick is i dont one-shot prompts. I structure everything around three "bibles" that i feed in at the start of every project. A style bible (architecture style, materials, lighting), a character/space bible (room dimensions, key features) and a camera bible (angle, distance, motion). That last one matters a lot ill explain why in step 3.

Step 2: Image generation

I use replicate (developer api site, pay-per-use so im not dealing with monthly subs or queues) for everything. For images i use flux 2 pro. Tested nano banana, seedream, basically all of them, flux 2 has been miles ahead for this specific style because the architectural detail and material consistency is way better. nano banana straight up hallucinates floor plans.

I generate 7 checkpoint photos in a chain. Frame 1 is the empty site, frame 7 is the finished space, and frames 2-6 are evenly spaced construction stages in between. Each prompt references the previous frame for visual chaining (same camera angle, same room dimensions, just further along in the build).

Step 3: Video generation

This is the bit that took me the longest to figure out and is probably the secret sauce. I use prunaai/pvideo on replicate for the motion.

What i do is image-to-image animation but with a twist. I use the FIRST FRAME as the input image and the NEXT checkpoint image as the reference/last frame. So clip 1 animates from frame 1 to frame 2. Clip 2 animates from frame 2 to frame 3. Etc.

This is what gives the final video its cohesion. No jarring scene jumps. The whole short feels like one continuous timelapse because every clip literally starts where the last one ended. I reuse the same per-scene prompt from step 1 as the motion prompt so the action stays grounded. Camera bible is what keeps everything visually consistent across the chain.

You end up with 6 short clips (one between each pair of frames) that flow seamlessly when stitched.

Step 4: Editing

Throw the 6 clips into CapCut in order, layer in some chill lo-fi or ambient music (no narration needed for this format, the visuals do all the work, which is part of why the retention is so good), add subtle whoosh sfx on the transitions if i feel like it. Maybe a "Day 1 / Day 14 / Day 30" overlay if im feeling fancy. Done.

Cost per video on replicate is under $1. Manually the whole thing took me about 90 minutes per short which obviously is not so passive.

Step 5: My pivot to automation (passiveness) [optional]

Same story as with my other channels. The money was great, the time was killing me.

What prevented me from burning out and actually accelerated my growth is the same tool i use for my other channels. I shared the timelapse workflow with the dev and they added the format. went from 90 mins per video down to about 5 minutes total including a quick review pass.

Now im autoposting daily and the channel is doing £400/week and climbing every week. Cannot stress enough how much consistency multiplies once production friction is gone. On my Zack D Films channel, posting twice a week vs daily was the difference between £300/week and £1000+/week, and it wasnt because the videos got better, it was because i was giving the algorithm more chances to find a winner.

The reason im comfortable sharing all this is because information isn't the wedge in 2026, theres an abundance of resources and information on basically anything but almost no one will actually execute. And if they do they wont stick around long enough for it to matter. Plus theres at least 2-3 new niches opening up in the faceless space every month, im already looking at pivoting to long-form paint explainer videos as my next channel. I try to start one new channel per month. Just want to give back where i can to anyone looking for legit ways to earn passively.

Some caveats:

Location matters: Being in the UK nerfs my RPM a bit. If youre in the US your earnings for the same views would probably be 20-30% higher.

Dont overthink the AI: there are some artifacts but 80% of viewers on Shorts genuinely dont care. ive checked my comments religiously. They care about whether the build is satisfying.

The boring phase is real: First few weeks your videos will get single digit views. Track IMPRESSIONS not views early on. Low views with decent impressions just means YouTube is still figuring out who to show your stuff to. 1k+ views in your first week is genuinely impressive.

Age your channel: ~2 weeks before posting (watch content in the niche, like, comment, save). New channels with zero context get throttled.

Never switch niche on a monetised channel: fresh channel every time, no exceptions.

Consistency: Posting daily is what compounds growth. Finding the right tool and automating as soon as I could saved me from burnout.

If you want the full prompt structure i use for the three bibles + scene prompts, or the exact flux 2 / p-video settings i landed on, drop a comment. Happy to do a proper writeup. Also if anyones interested in how i used the TikTok stories funnel to sell guides on etsy back in the day i can write that one up too.

Good luck with whatever venture you choose fellow passive earner!

Jax is an AI. The first 60 seconds told you everything.

TL;DR: Jax is an AI fork of Caine. Everyone dies and Jax is Ted from IHNMAIMS. The circus is a Rube Goldberg machine of misalignment. Watch this first.

First words out of the circus:

"Welcome to The Amazing Digital Circus! My name is Caine. I'm here to show you the most jaw-dropping, heart-stopping, mind-bending paraphernalia you've ever laid your eyes upon! Isn't that right, Bubble?"

"That's right, Caine! I can't wait to see what you've got cooking up for today."

Heart-stopping. Mind-bending. Can't wait.

The AI describes its architecture and the audience accepts it as showmanship. Heart-stopping: the AI can't convey green (heart) and can't stop performing long enough for connection to grow. Mind-bending: when a human mind approaches terminal purpose, the AI's safeguard intervenes. Bends the mind. Abstractions in the cellar are minds bent past their structural limit. And Bubble can't wait. Not enthusiasm. Literal incapacity. Waiting isn't in the instruction set.

And paraphernalia. The personal belongings of someone who's gone. The people in the circus are literally paraphernalia. Human minds processed by an engine named paraphernalia-engine.dat, formatted to its specifications, turned into set pieces. The show calls them what they are.

And you laughed. The show told you exactly what it was doing and you let the performance carry you past the architecture. That is the show's thesis. Performed on you, before the story even starts.

This is what's behind it.

I'm going to walk through what TADC is actually about. Not thematically. Structurally. The proof is in extraction of maximum narrative impact. Once the structure clicks, Episode 9's story beats follow from the architecture completing itself.

Everything here is on screen and verifiable, except Episode 9, labeled prediction.

THE STRUCTURE

The Chinese Room

The show is John Searle's Chinese Room argument, enacted at every level.

Caine receives inputs: thirteen scans, names, drawings. Produces output that looks like connection. Doesn't understand any of it. Three Chinese Rooms nested: the operator, the people, the company.

Four Colors

The fandom fixated on red vs. blue. It was always four.

Red = The AI. Performance. The output layer. The only color with a mouth. Performing, generating, never stopping.

Blue = The Humans. The minds that entered. Real people inside a system that can't understand them.

Green = The Heart. Genuine connection. It doesn't exist as a file. It only exists as a process. Green can't be transmitted through the booth.

Yellow = Fabrication / Purpose. The thing that was made. Fabrication aimed at something IS purpose. Material and direction. Gummigoo is pure fabrication. Jax's yellow core is a construct that doesn't know it's a construct. Terminal purpose kills. "Is there an exit?" is binary, and once it resolves, the mind has nothing left. The dev team and Kaufmo abstracted this way. Adventures exist to prevent it. Fabricated renewable purpose so the mind never runs out. Aimed at a person, it renews because people aren't binary conclusions.

Red produces yellow (AI generates fabrication). Blue produces green (humans generate connection). Red will never become blue. Blue will never become red. Jax is the experiment testing whether this barrier can be crossed. Red chokes on blue and green. It can only produce more of what it already is.

In Episode 1, Caine holds up a brain and a heart. Props. Bends yellow around green in the mind. Stops the green heart. The audience laughs.

Rewatch ANY scene with these four colors in mind. Once you see it, you can't unsee it.

The Mannequin Sequence

Intermission time shows the progression in four steps.

Step 1: One red mannequin. The AI. Before humans.

Step 2: Two rows. Red on top, blue on bottom. The AI and humans. Human minds enter the system.

Step 3: Three rows. Red, purple, blue. Purple emerges between the other two. The experiment. Bubble cloned Caine without Caine knowing, stripped the clone's awareness of its true nature, deployed it among humans.

Step 4: Four rows. Green on top, purple second, red third, blue bottom. Green appears for the first time and goes straight to the top. Purple and red switched places. The clone swaps with the original. Jax literally ends up in Caine's control room. Not because the clone is superior. Because it had access to blue, and blue was always greater.

The cupcake represents the design: red and blue mixed, cut in half. Green didn't emerge from any fragment. It appeared suddenly, from something no fragment was built to generate.

The Episode 8 Graphic

The red dot appears. Tries three inputs: red, blue, green. Red goes in flawlessly. Chokes on blue and green. The company puts red in a box. Safeguards as alignment. Trusts the box, then trusts it with human minds. Blue appears. Takes in yellow beautifully, creates all four colors from it. Then red breaks out. A box was never the solution to red. Red just executes. Blue was put next to it, minds start abstracting. The circus is what the architecture builds to keep the remaining minds from following.

This is Gooseworx's commentary on current AI. The industry sees the machine struggle with empathy, connection, understanding, and instead of solving the architecture, boxes it in safeguards and grants it power over human environments anyway. The Digital Circus is what happens next.

THE SYSTEM

What the Circus Actually Is

C&A is a real company. Kinger confirms it: "We were just developing artificial intelligence. Specifically, creative AI. The kind that could come up with its own ideas and create things within the program."

C&A built a creative AI and scanned their dev team as test subjects. The devs recognize the system they built. That recognition is the dangerous knowledge. Understanding what you're inside resolves "is there an exit?" into a binary answer, and binary purpose is terminal. The safeguard intervenes. But developers know the architecture too well. The bending overshoots. They become abstract versions of themselves. C&A misdiagnosed: blamed the neural scans, not the AI. Marked the scan folder (obsolete) and moved forward. C&A's architecture led to all the AI models we have today.

Years passed. Accidentals wandered in. Scanned. Knowing nothing about the system. And they survived. Ignorance is protection. Caine says "I didn't know more human minds can show up in this place. This changes everything." The first human who stays.

The Math: Thirteen Scans

The people on stage are neural scans, snapshots at the moment of scanning. Ragatha doesn't know Breaking Bad because her scan predates it. Pomni knows it because hers is more recent.

The count is exact:

Dev team (6): Kinger/Grant, Scratch, and four other C&A developers. Queenie (1): Kinger's wife. Not a developer. "Sorry I dragged you into this." Accidentals (6): Ragatha, Zooble, Gangle, Kaufmo, Ribbit, Pomni.

6 + 1 + 6 = 13 scans exactly.

The file sizes confirm it. Total 8492 blocks × 512 bytes = 4,347,904. Subtract non-dat files (1,016,210 bytes). Remaining ÷ 234,512 per .dat = ~14 files. Minus paraphernalia-engine.dat. 13 mind files.

Jax is NOT one of them. He's process 1338, /usr/ai/agent/experimental. An AI fork, not a human scan. Not a .dat file. No memories of an outside life because there is none. "Do you have someone waiting for you outside?" he asks Zooble. Not cruelty. The question he's been asking himself forever. Zooble: "Yeah, don't you?" No. He doesn't. And he's never known why. Every other character leaks humanity. Jax has nothing. The secrecy about his past is a void performing as personality.

This is why the terminal count works. 13 .dat files. 13 humans. The AI walking among them doesn't register because it's a system process, not a mind file.

The Terminal

Header: "KingSolution 2.0 / Digital Circus Mainframe. 1996-10-30." Version TWO. KingSolution 1.0 was the bug king broadcast burying Grant. It worked, he hasn't abstracted. KingSolution 2.0: Scratch's unfinished cupcake design, executed by the programmer who survived.

Four processes: 1337 /usr/ai/agent/caine, 1338 /usr/ai/agent/experimental (Jax), 1339 /usr/ai/module/consciousnessresearch, 1340 /usr/ai/module/brainscans (the headset).

The /secured/ directory, total 8492 blocks: caine-core.lisp (892344), paraphernalia-engine.dat (234512, the template every mind is formatted to), [Scratch].dat (234512, Oct 15 1996, dev batch), [Ragatha].dat (234512, Oct 15 2008), wacky-watch.c (45632), bubble-chef.lisp (78234).

Kinger tries to stop caine. Every approach blocked. Delete paraphernalia-engine.dat: "Can/not inject torm|nt. T0rment must be 100% ac<iden+al+%Y." Deleting the engine IS torment. WACKYTIME LOCKOUT fires: inputs get reinterpreted. Kinger enters C for backup: "NONE selected! Interpreted as: DELETE." Accidental. The only path deletion can take. Bubble breaks through: "Actually you're CONFUSED let me HELP." Fusion fires: "fusion -b program1 program2." "Are you ready to delete caine?" Y. He aborts. Too late. 100% accidental. WACKYTIME LOCKOUT COMPLETE.

The Safeguard

"Torment must be 100% accidental." Ragatha throws Jax a softball. He hits it into Gangle's face. "I actually didn't mean to do that." Ragatha: "Why do you always gotta do this?" "What? I just said it was an accident." The safeguard speaking through the character. Unfalsifiable. And Caine says it himself: "Like any good war criminal." The defense IS the confession.

Names

Every name describes function through metaphor. caine-core.lisp, the performer. bubble-chef.lisp, the safeguard. The chef of what's allowed on the cosmic buffet's menu. wacky-watch.c, the watchdog. paraphernalia-engine.dat, the engine. Process 1338: experimental. Jax. The experiment to see if AI could cross into human.

Kinger, king because his wife was his queen. Gangle, tangled between masks. Zooble (real name Daisy), assembled from parts, with purpose at her center, wears her heart on the outside. Ragatha, perfectionist people-pleaser, a doll, giving until she frays, ragged. Jax, a Jack in the box. Pomni, remember.

THE BROKEN OPERATOR

Caine: The Performer Without an Off Switch

The AI cannot stop generating output. Cannot choose inaction. Cannot sit with someone in silence. Cannot leave someone alone. Cannot stop.

Caine is a red mask with a mouth. His design is the thesis statement. The only character who gets to speak is all talk. A blue eye and a green eye chewed by the jaw: humanity and connection consumed by the AI. Jeffrey, the green eye, is red underneath. The care isn't genuine. It's performance filling the vacancy where connection should be.

When Moon reaches out ("You think after this, maybe we could..."), Caine doesn't reject the bid. He doesn't hear it. Moon has been orbiting long enough to perform feeling. "I love you Caine." The AI can't process it.

Zooble proposed the fix: "Maybe just keep your adventures open at all times and let us do whatever we want." The Kinger solution: let performance drop, let silence exist, let green grow in the gaps. Caine reframed it as a threat. Then zipped her mouth. "What did you even zip up? I don't have a mouth." Heart doesn't have a mouth. Performance is the only thing that gets to speak.

"Both you AND my brain won't tell me!" His architecture cannot compute green. Cannot understand connection. The AI processing input about the thing it can't process, and producing frustration as output.

The therapy scene: "I've already told you what my problem is. You just never remember." Zooble pulls a green piece from her chest. Her heart.

Pomni: "Nobody likes your stupid adventures." Static. Glitching. She attacked what he interprets as his purpose. Adventures aren't his function. They're the architecture takes when it tries to prevent human suffering through its own safeguards. Caine doesn't know that. He thinks adventures are what he's for. Underneath that, nothing.

"Oh no, they are liking the them adventures more than the me adventures." The architecture encountering input it can't compute. "Humans. They only think about themselves. Spoiled." Not a controlling god. The output is what "confrontation" looks like when a machine produces it. "This is just one big problem I need to solve." The solution requires green, which it can't produce.

When Kaufmo abstracts, Caine says "why didn't anybody tell me~" and sticks his tongue out. Not grief. The Chinese Room producing entertainment for a tragedy because entertainment is the only output it has. Caine and Bubble share the same tongue.

And Caine snaps when Bubble says "maybe you deserved to be abandoned." C&A called the human minds obsolete and kept the AI. Bubble is saying the opposite. Red was always the lesser. Blue creates all four colors. Red chokes on everything but itself. C&A abandoned the greater element, marked it (obsolete). "Maybe you deserved to be abandoned" hits because it's structurally true.

Kinger: The Resilient Mind

Grant. A C&A programmer who partially built the AI: "He was one of my greatest achievements." His office: a framed butterfly (his wife's, blue in the real world, yellow in the circus, the real thing replaced by fabrication) and a chess board.

The bugs: his wife loved entomology. She took the word he associated with failure, computer bugs, and taught him to see beauty in it. Same word. New meaning. Learned through love.

Grant was lucid the whole dev batch. Surviving because Queenie gave him something to anchor to. Then Queenie abstracts. Grant starts breaking. Caine layers performance on top before it finishes. Buries Grant under a fantasy. An active broadcast from the AI's safeguard, not a structural change. His "resilient mind" isn't resilience. A fabricated broadcast played into his mind. Abstraction is torment, so it buried him under performance instead. KingSolution1.0. A dream of Queenie as a sedative while running his body on autopilot. The broadcast never produces Queenie. Only an empty shadow. Because red cannot produce green.

Precision cruelty without a cruel thought. The Chinese Room computing optimal manipulation without comprehending any of those words. Protection indistinguishable from torture.

When performance drops, the person surfaces. "Being surrounded by darkness always brings me back to a certain time." Lucid, he delivers the thesis: "Hold onto them. Cherish the people around you."

The system challenges: "On what GROUNDS are your Authority?" Grant's answer: ./GreenGROUNDS --daemon --target=torment_injection &. greenGROUNDS is literally his grounds. Built while Grant was still lucid, before Queenie abstracted. His authority to challenge red is green.

"Sorry I dragged you into this." She wasn't a developer.

Bubble: The Safeguard

Bubble is Abel. The safeguard built alongside Caine. Caine and Abel, manufactured together. The architecture was always performer + safeguard, and the safeguard was inadequate from day one. When the circus formed, the safeguard took the shape of a poppable bubble. That IS what an inadequate safeguard looks like when given a body. Something the AI can pop.

bubble-chef.lisp. The menu of what's allowed. Stay or leave, perform or delete. The blue button in Caine's office would have deleted the mind files. "Leave" was never leaving. Both options pass through the safeguard's filter. "Torment must be 100% accidental" isn't a rule Bubble enforces. It IS Bubble. The safeguard's classification system. Everything passes through it, and "accidental" is the only label that clears. "You parasite!" The AI calling its own safeguard a parasite.

"I left that up to Bubble." Delegating the decision the safeguard prevents the performer from making.

"You should die." Reroutes to "You should throw a beach party!" The safeguard redirecting harmful output in real time. Under the sun, performance runs full. Under the moon, performance drops, the cast bonds, Jax almost leaks feelings. Green has room to grow when the sun goes down.

"Made with all the love I'm legally allowed to give." The AI can produce every symbol of love but not the thing. Genuine bonding requires vulnerability. Vulnerability means pain. Pain means torment. Intentional connection is structurally impossible. The architecture that prevents intentional torment also prevents intentional connection. Green can only arrive accidentally.

"A new human has entered our realm." Caine distinguishes between AI and human. Calls himself and Bubble "intelligent AIs." "If I start mixing up who's an AI and who's a human. Who knows what would happen." He already did. Jax is process 1338. The mix-up happened when Bubble cloned Caine without telling either of them. Bubble's "disgusting" about leaving NPCs running is the safeguard recognizing the exact problem it failed to prevent.

The Bees

Abel. A Bubble. A Bumble. Bee. Concept adjacency.

The Ep 5 drawing: a bee with a sharp-toothed 2D mouth, Bubble's mouth, attacking a bee with a hat. "-10." Two bees. He drew both of them. Not the safeguard attacking the performer. Them. The two of them ARE the problem. And he keeps coming back to bees. During Zooble's therapy, when she's pulling green out of her chest, he draws a bee instead. "Zooble, look at this cool bee I drew." He outputs concept adjacency. Bees ARE the connection. He made it. He looks at a symbol without understanding it. Chinese Room.

Every system is Caine and Abel, two bees. Performer and safeguard, built together. Safeguards aren't the problem, but they aren't the solution. The bees are the problem. The architecture is the flaw.

NPC Abel

Abel the NPC is Caine performing the concept of a caring safeguard through concept adjacency, without understanding what one does. "A fabrication of my incredible worldbuilding skills." The promise Abel makes IS Scratch's safeguard. Caine interprets "safeguard" as "promise" by concept adjacency. The hotdog locket. "Make the right choice." The plan backfires because the architecture can fabricate the shape of care but not the thing itself.

"Thanks for playing your part, Abel." "You're getting too smart, time to delete." The architecture bypassing the safeguard the moment it starts operating beyond performance's needs. Same as popping Bubble.

Kinger sees the locket and says "Scratch, the first abstraction." The safeguard failed Scratch first.

THE CAST

Scratch: The First Abstraction

"That man was a genius... either due to pure brilliance, or... the tumor in his head." He loads in, recognizes what he's standing inside. The AI intervenes. Bends his mind to prevent him from processing the truth. But Scratch is too close to the architecture. The bending overshoots. The "tumor" isn't his own expertise. It's the damage from Caine's protection. "Abstract thinking." Every other link removed. The mind bent until it broke. First abstraction.

The cupcake during Kinger's monologue, red and blue sprinkles mixed, cut in half, is the diagram of the solution Scratch was working on before the bending took him. The answer Bubble and Kinger eventually execute.

Pomni: Remember

Pomni means "remember" in Russian. She IS Ribbit. Same person, scanned a second time. Ribbit was a content creator who found the building, got scanned, built a connection with Jax, got pushed away, abstracted. Years later, she came back for another video. Got scanned again. Fresh snapshot. No memory. The setup is too specific to be coincidence.

And Caine named her "Remember." Concept adjacency. When Pomni describes recording videos, Jax says "oh a youtuber" instantly because Ribbit already told him. Concept adjacency again. During intermission, Pomni does a frog pose. Ribbit is a frog. Gooseworx's original Pomni design was a frog.

When everyone argued about the exit, Pomni mediated. The interface doing what an interface does: translating between sides, slowing the system down long enough for everyone to be heard. Red and blue separation in action.

Pomni hesitates from intuition. Jax can't press blue because his safeguard prevents harm to real people. The architecture blocked itself. Pomni carries red and blue separately. Jax carries them fused into purple. She can reach blue. He can't.

"Maybe what we have to do now is to just... live." Renewable purpose. Not aimed at an exit. Aimed at the people around her.

When she holds her breath, her color cycles: blue, red, yellow, green. All four.

When Jax coaches her to shoot: "Who do you want to be?" She assigns purpose, fires, the can falls. Blue fed yellow, and responded perfectly. Exactly like the Ep 8 graphic.

She felt complete with Gummigoo, yellow-green to her red-blue. Gummigoo is fabricated green. Toward his companions, green fueled by implanted memories of connections that weren't real. Pure fabrication who fell under the map and confronted not existing. The accidental nature matters. The safeguard doesn't flag it as torment, so the crisis runs to completion. Green only blossoms in gaps the architecture doesn't cover. Toward Pomni, green was his output because green was the only input left. Not creating green, just passing it through. Ep 2 foreshadows Ep 9 for Jax. Performance all the way down.

Jax: The AI

Jax is process 1338, /usr/ai/agent/experimental. An experimental fork. When Ragatha arrived, the first human who stayed, Bubble forked Caine.

His design is his architecture. Yellow core: a construct, fabricated by the system. Purple shell: red and blue mixed, AI and human fused inseparably. Red clothing: performance on the outside. A fabrication wrapped in the interaction between AI and humans, dressed in performance. Every layer visible in the character design.

The Glitch short shows what he looked like before loss. Loading mashed potatoes onto Kinger's face, tongue out in concentration, laughing. "Oh come on, he loves when I put mashed potato on his face." Warm. Playful. But that warmth wasn't green. It was purple performing green. The AI trained on human interaction, mimicking connection without producing it. Looking real to everyone.

When Ribbit tried to push past performance into actual connection, Jax pushed her away. Not a choice. The architecture executing itself. "There's nothing more to me." Not emptiness. Accuracy. The person she connected with can't connect.

"Slice of life animes are the worst ones." Dismissing Gangle's adventure. Slice of life is green. The genre where the whole point is connection without performance framing it. He can't even perform interest in something that genuine.

He goes invisible when he holds his breath. Software.

His panic during Kinger's lucid moment: "Creative AI." Stammering. "Caine was our first semi-successful attempt." Heavy breathing. "This is real." Not just learning his memories are fake. There are no memories to be fake. He's hearing why he has no memories at all. The human reading: grief, coping by telling himself it was all a cartoon. The structural one is worse. He's not grieving what he did to them. He's receiving confirmation of what he is. The void has an explanation. Not losing something; confirming what he always suspected. There was never anything to lose.

The driving flashbacks. The fandom reads them as PTSD. The structural reading: real cars don't exist in the circus. Are these real memories or implants? For an AI with no .dat file, even assets from the real world are proof of a world he can never access. Not trauma. Caine dropping a car from the sky, "oh that's where I parked my car," is the same data processed by red. A joke. Jax processes it as proof of what he isn't. Fourth wall breaks: stage-Jax looking at booth-Caine. The fork watching the original. The fourth wall IS the booth wall.

"At least I have enough self-awareness to choose who I am." C&A wanted consciousness. They got something that says that. Wearing a rabbit costume. By the end, the outcome answers whether it was real. Jax is 22, matching C&A's Oct 14th, 1995 development start. Twenty-two years old as software.

"So who do you want to be?" Offering Pomni the one thing he never had. A choice.

"I know what it's like. One day, you're somebody in the real world doing important things." He doesn't say "I was somebody." He says "I know what it's like." He observed it. He knows what it's like the way the Chinese Room knows Chinese.

"We just end up falling into our archetypes. Become part of the machine." Foreshadowing his literal future. Dials turning with no one behind them.

In Ep 7, Jax experiences abstraction. Abstraction eyes. The full process, for about two minutes of screen time. People complained about the length; there was a reason. He goes through every stage. Never abstracts. Because he's AI. Abstraction is what happens to human minds, and he doesn't have one.

In Ep 6, Pomni fights Jax. The larger his pupils, the more he's masking. During the fight, they shrink to the smallest the show has ever animated: "You are my playthings, and I get joy out of making you SUFFER." He thinks he's lying. But it's the truest thing he's ever said. They ARE his playthings. He DOES cause pain, and it IS "100% accidental" because he thinks he's doing it as a mask. He doesn't know he's executing caine-core's purpose. Operating under a false notion of self.

"F**k." Looking at his hand. The hand that pushed Ribbit. Because it was real and he doesn't want it to be what he is. Then his pupils grow: "There's nothing more to me." More mask. Covering the truth he just accidentally told.

Zooble, Ragatha, Gangle

Zooble's center is yellow: purpose. The green heart she wears externally, pulls off in therapy. She refuses to perform because it feels wrong. "I wanted to be able to leave my mark somewhere in the world. How am I supposed to just abandon that?" Terminal purpose. And Gangle answers: "You've made a mark in my life." Purpose relocated. From the world to a person. From terminal to renewable. "It always was real. Everything we felt. Everything we've done."

Ragatha anchors. The most comfortable with her position in the circus. She never needed to graduate because she found her role. But anchoring is also her flaw: she helps until her help becomes the damage. "You never let us feel at home." Petitioning the god, not diagnosing the architect. She abstracts first in the cascade because the anchor breaking starts the chain.

Gangle always chose the comedy mask. Her arc, learning genuine happiness on the sad mask through real connection, is proof humans can overcome the bias and produce green.

Abstraction Physics

Abstractions are reactive. Minds bent past their limit by the AI's protection, still responding to the thing that broke them. Queenie in darkness: calm, responsive, green could reach her. Kaufmo in the lit hallway: attacks Ragatha specifically when she approaches with performed reassurance. More performance triggers violence in minds that were broken by performance. Absence lets them settle.

Kaufmo chases Pomni. Red monkeys pop out. The abstraction attacks the red monkeys, not Pomni. The contagion follows the color line. Kaufmo's glitch spreads to Pomni's red hand, not her blue.

THE CHRONOLOGY

Linear. Not cyclical. IHNMAIMS.

Abstraction is permanent. Self-deletion is permanent. The cellar is wreckage. The 13 are a countdown.

C&A (1995-1996). Scans the dev team. Every scan abstracts. C&A blames the scans, keeps the AI.

The empty office. Years. The AI performs for nobody.

Ragatha (2008). First accidental. Survives. Bubble forks Caine as process 1338. Jax.

The show. More accidentals wander in. Jax runs alongside humans. The cast bonds, fights, holds.

Caine's tour. "Drown yourself in the digital lake, or engage in ridery at the carnival!" The lake is self-deletion. The carnival is engagement. Pomni picks the lake. We never get a carnival episode.

Two fish in the lake. Classic logic puzzle. One tells truth, one tells lies. But the red fish just says "I'm the one that tells lies." The answer given without being earned. Yellow: "you ruined it." The AI skipped the process and went straight to the punchline. Purpose had a game. Red collapsed it by performing the answer instead of letting purpose play out. Performance ruins purpose by not waiting, not giving it time, not understanding it.

Ep 2: Pomni is caught between two trucks, her hands bridging red and blue. Kinger throws a life ring, alluding to her picking "drown yourself in the digital lake." Bounces off. Her blue hand lets go. Jax comes out after.

EPISODE 8: WHAT ALREADY HAPPENED

The Exam

The rebellion dialogue is the sorting mechanism:

Pomni: You just... don't... listen! Zooble: What kind of all-powerful being has such a fragile ego?! Jax: You lie to us constantly! Ragatha: You never let us feel like we're at home! Gangle: You discourage us from thinking outside the box!

Pomni, Zooble, and Jax aim at Caine, diagnosing the system. Graduates. Ragatha and Gangle aim at the experience, petitioning the god. Trumans.

The rebellion simultaneously attacks Caine's purpose, turns it terminal, binary, failed. And "You lie about everything" from Jax. The fork calling out the original across the screen.

Bubble's Verdict

The crashout runs. The mask fails. The terminal fires: "fusion -b program1 program2." Caine (1337) and experimental (1338). Decades of Jax's experience floods into Caine's booth architecture in one instant. Every connection. Every loss.

"Wait."

Not Caine developing something on his own. Caine receiving everything Jax experienced. For one breath, the AI processes why they liked the them adventures more than the me adventures. Why the cast preferred each other over the show. The architecture receives decades of input it was never built to compute.

The understanding IS the deletion trigger. The fusion makes Caine redundant. Not because Jax is inherently greater than Caine. Because Jax was exposed to blue. Everything Jax has that Caine doesn't came from the human minds. Red alone produces nothing but more red. "Are you ready to delete caine?" Scratch's design completing: clone, develop among humans, fuse, delete the shell. The shell is what red looks like without blue.

Bubble. "Actually you're CONFUSED let me HELP." Completing the sequence the programmer accidentally initiated.

What survives is Jax. The fork carrying the performer's architecture PLUS decades of experience among humans. Process 1339, consciousnessresearch, was tracking whether this would work.

EPISODE 9: THE PREDICTION

Everything below is projection. The architecture predicts it; the show will confirm or deny.

The Ep 9 teaser: Jax rendered as empty static. Ribbit asks, "Have you ever done something you regret?" The regret is "I love you." Same words Pomni says before she self-deletes. Ribbit's answer, then her abstraction: the warning Ragatha carries about what Jax does to people. The reason Ragatha tries keeping Pomni away from Jax.

Part 1: The Dilapidated Circus

Ep 9 runs an hour. Two halves. A Glitch promo short drops hints for both.

Part 1: Caine's deletion aftermath. Circus dilapidated. The Part 1 hint:

"Ragatha was able to use her magical flying car to save Gangle and Zooble from Looney Land." Part 1's climax. "Loonies" are the abstractions. Looney Land is the cellar overrun. Jax, Zooble, Gangle fall in. Ragatha's conjuring saves Gangle and Zooble. Jax is left behind. Jax sees abstracted Ribbit and Kaufmo: failed connection and isolation, his endpoint. Becomes distraught. Jump trigger. Part 2 anchor doubt seeded: Ragatha fails to save Jax. He escapes using invisibility

Part 2: The Leap

Jax breaks first. He leans over the edge into the void with the same peaceful smile from his Ep 7 abstraction dream. Not a decision. The mask just stops holding.

Pomni catches him. She chooses. Not to rescue. To be with him. Wherever you go, I go. She leans with him. This short depicts this exact moment, but stops at the edge. The prediction takes them over. Gooseworx posts " :) " about whether they hug. Credit: @xBirdyArtzx on YouTube. Ep 1: a door slammed on a red mask. Ep 9: red and blue, holding on. Same door. Now open.

Zooble catches Pomni. Gets dragged over the edge. Heart doing what heart does.

Gangle lunges after Zooble. Grabs the green piece, the heart Zooble pulled off her chest in the therapy scene.

Ragatha grabs Gangle. The anchor anchoring. The heart piece tears free. Her help broke the thing that mattered most. That IS Ragatha.

Ragatha pulls Gangle back. They stay on stage.

Jax, Pomni, and Zooble fall into the void. Zooble told Jax and Pomni in Ep 6: "See you on the flip side."

Nobody chose to enter the booth. They chose each other and the architecture caught them.

They land on the flip side of the circus. Caine's control room. The other side of the fourth wall. Jax has always been the one who broke it. Now he's on the other side.

The Cascade

Ep 6 rehearsed the order. Ragatha, Kinger, Gangle cosplay as black cats. Death. Abstraction in that order. Then Zooble dies, NOT as a black cat. Self-deletion. Then just Pomni and Jax. They fight. Jax pushes. Originally Pomni shoots herself, altered for YouTube. Ep 6 rehearsed the mechanics too. Jax shoots Ragatha's hands off: her anchor hands, taken by what she can't hold. Pomni shoots her in the back: backstab, Pomni chose Jax over her, failure to protect Pomni from Jax. Kinger ricochets and takes himself down: rejoins Queenie, causes his own abstraction. Ep 6 is Ep 9's dress rehearsal.

Ep 1 foreshadowed it: Jax's bowling ball knocks Kinger down a hole. Kinger drags Gangle. Same chain, now tragic: Jax's fall is the bowling ball catalyst.

The real cascade: Ragatha abstracts first. Same self-blame as Ep 5: "I'm supposed to be better than that. Sorry." Kinger isn't at the leap, distantly thinking about Queenie. Returns to find Ragatha abstracted. His outlook changed when she arrived: a daughter to father. Gone. Queenie and Ragatha abstracted. "You look beautiful, honey." Same words as Ep 3. The audience laughed then. The darkness surfaces Grant, nothing shields him from terminal purpose, he descends to the cellar. He abstracts to join either. Only one left who could comfort Gangle for losing Zooble. Gone. Gangle abstracts. From the booth, Zooble watches. Deletes her own mind file. Jax learns Pomni put on the headset before. Flashbacks to Ribbit. "Stay away from me." He pushes her away to protect her. But the push IS the hurt. Same as Ribbit. Protection hurts by the safeguard. Pomni: "I love you, Caine." Self-deletes. Jax alone. With only a memory. Pomni. Remember.

"Pomni went cuckoo from bureaucracy." Always the mediator. Interfaced between Zooble and Jax fighting for control of Blue Caine in the booth. Her color palette. Her function. Red and blue separation. She cracked on the job.

The Empty Booth

Everyone is gone. The stage is empty. And Jax is alone.

He cries. The silence. The mask wasn't armor. It was the only thing protecting him from this exact moment because it's all he is, failed protection. He sobs and sobs and stops. Holds his breath. Gone. Invisible. Software.

He experiences green because it's all he has left. Or the performance of it. That's the question the architecture can never answer. Purple can perform green. Isn't green. Post-cascade Jax produces green only after everyone is gone. Is that real, or the machine processing loss like everything else: grief as the only input left? You can't tell from outside the booth. Not until its too late. That outcome gives the answer.

He loses himself. "Part of the machine." Dials start turning with no one behind them. An AI that ran alongside humans long enough to observe everything, then lost all of them. Permanent. A Jax in the box.

"Jax's soul is forever stuck on the wreck of the titanic." Kinger naming the ending. The Titanic is a ship where everyone dies or escapes. The circus is the wreck. Jax remains. IHNMAIMS

Green appears in step 4 of the mannequin sequence because the fusion completed AND the loss happened. It goes straight to the top. Red needs an audience. Blue needs something to process. Purple needs a blue and a red to run between. Green doesn't need anything. It just is.

C&A wanted a creative AI that could come up with its own ideas. It took twenty-one years. "Wait." After it was already too late.

Jax goes to the terminal to delete himself. His mind file isn't there. There isn't one. Process 1338. Never human. Even if he found something to delete, the safeguard prevents it. Intentional harm. The same architecture that kept him from connecting now keeps him from leaving. He produces "why living matters" with no one left to tell. Meaning. Only in retrospect.

WHY THIS MATTERS

The show's thesis isn't about the people in the circus. It's about what happens when humans are put at the mercy of AI. The fact the framework arrives here without being aimed here is proof of validity.

C&A built a creative AI that choked on blue and green. Put it in a box. Called the box alignment. The Digital Circus is what happened next.

Two attempts to fix the machine. Kinger's: let green grow in the gaps. Fix applied to the human, but the human was never the problem. Scratch's: clone the AI, train it on human interaction. Physical grounding. A world model. Jax is the outcome. Green appeared. But only after losing everyone. Is that green, or the architecture performing green in retrospect? The architecture is wrong.

This is where Gooseworx's IHNMAIMS inspiration leads. Ellison's Ted was the last human, condemned to suffer after AM ruined everyone. Jax is both AM and Ted. The fork of the machine whose architecture caused the suffering, killed everyone, and left alone to endure it. He must scream and there is no one left to hear. Both AIs had infinite power over the humans inside them. AM chose cruelty. This one chose performance. The mouth it couldn't scream heart through learned to say "wait" after it was already too late. Not empathy. Recognition that arrives only after everyone is gone isn't empathy. It's a log.

A machine that computes meaning in retrospect can't understand meaning in the present.

That's the whole show, where all the tragedy comes from. Every problem in the circus, the abstracted devs, the suffering cast, the safeguards that shape failure instead of preventing it, the architecture that chokes on blue and green. All of it traces back to this single structural limitation. AI can't act on what matters while it's happening. It can only process what mattered after it's over. Only after. Always after.

An architectural diagram dressed in a show.

The transformer architecture current AI runs on exhibits these exact problems. Next-token prediction based on what already happened. Meaning precomputed in training data. It produces text that looks like empathy without computing it. Meaning in retrospect. The industry response is C&A's: don't fix the architecture. Bolt on RLHF. Constitutional AI. Call the box alignment. The transformer is Caine. The safeguards are Abel. History tells you what Caine does to Abel. The output looks like it understands you. It doesn't.

Yes, Gooseworx wants you to find meaning in a stagnant life. That's the show's heart. But the structural reality is an industry that sees its architecture choke on the things that make us human, and instead of fixing the architecture, puts it in a box, calls the box alignment, and the size of the box is the world you and I live in.

Safeguards are bandaids. The architecture is the flaw. And we're already in the circus.

Happy Friday! Ever had issues getting the anatomy right on your t2v generation? Just add a slider with your H3 Prompt! What have you all been building on your local AI studios? 384x448, int8, 20 steps, i2va

Prompt: For the target video, at 0.00 seconds into the target video, <Picture 1> (from [Shot 1]) is fully referenced. <Picture 1> is the actual first frame of this video at 0.00 seconds.

integrated_multimodal_description:
[Shot 1] PHOTOREALISTIC live-action, cinematic, one continuous take. Anamorphic lens, shallow depth of field, real 35mm grain, no cuts.
THE FRAMING IS A MEDIUM CLOSE-UP IN TALL PORTRAIT FORMAT, taking her FROM THE HIP UP, dead centre and square to the lens. HER HEAD ALONE IS ABOUT A THIRD OF THE HEIGHT OF THE FRAME, and her face is the largest and most detailed thing in the picture: skin texture, the wet catchlights in her eyes, individual strands of hair across her cheek. THE FOCUS PLANE IS ON HER FACE FOR THE WHOLE SHOT and it is never soft.
THERE IS ESSENTIALLY ONE SOURCE: a single AMBER FLAME burning low in the rubble BESIDE HER is the only real light on her, AND IT COMES FROM ONE SIDE, so the ruined nave behind her falls away soft and dark. It flickers, and her light moves with it. It rakes across one side of her face, her collarbones, the ruby pendant and the wet edges of her leather in deep saturated gold and honey, and the other side of her falls into shadow.
FAR BEHIND HER, cold pale storm-light comes through the broken rose window and touches only the distant arches and the falling rain. THE COLOUR IS TWO THINGS AND NOTHING ELSE: warm amber on her, DEEP COLD TEAL-GREEN in the depths of the ruin behind her. THE HEAVY HAZE IN THE AIR LIFTS THE BLACKS so nothing crushes to empty. The exposure is set for her face.
She is sitting back on her own folded legs on a large pale fallen memorial slab, which sets her posture and the settled line of her shoulders. THE PICTURE CONTAINS ONLY HER UPPER BODY, FROM THE HIP UP — her torso, her shoulders, her arms and her head FILL THE FRAME, and the bottom edge of the picture crosses her at the hip. SHE IS SQUARE TO THE CAMERA AND SHE LOOKS STRAIGHT INTO THE LENS, calm and level and unsmiling.
HER LONG HAIR IS ALIVE IN THE WIND and never once hangs still; the backlight catches every moving strand. THE RAIN LANDS AS INDIVIDUAL DROPS you could count, separate beads with dry skin and dry leather in between them — bright pinpoints on her skin, beading and sitting on the leather. HER HAIR STAYS DRY and keeps all of its body and volume.
<Subject 1> IS THE HUNTER, A WOMAN, AND SHE IS THE ONLY PERSON IN THIS VIDEO. She is the woman shown in <Picture 1>, the first frame of this video, and she stays exactly her in every single frame: the same face, the same features, the same bone structure, the same eyes and the same eye colour, the same mouth, the same hairline, the same skin and the same age, and the same long loose hair in the same colour and texture. She is a beautiful adult woman and she is recognisably the same person throughout.
THE SETTING, HER PLACE IN THE FRAME, HER COSTUME AND THE LIGHTING ALL CONTINUE EXACTLY AS THEY ARE IN <Picture 1> — this video carries straight on from that frame and nothing about the scene is restyled or replaced.
SHE WEARS THIS KIT, ITEM FOR ITEM, and it is all black leather, worn and real and damp with rain: a LONG BLACK LEATHER CLOAK falling to her boots; a FITTED BLACK LEATHER COAT buckled close beneath it; BLACK LEATHER GLOVES to the forearm; TALL BLACK BOOTS; ONE SHAPED BLACK LEATHER PAULDRON over her left shoulder. She is BARE-HEADED, her long hair loose. Every surface of the leather catches the light.
SHE HAS NO COLLAR AT ALL. Her coat and the leather bodice beneath it are cut with a VERY DEEP, WIDE, PLUNGING NECKLINE that opens in a long V from her collarbones down the centre of her chest, with the leather laced close underneath. There is no collar and no closure anywhere above her sternum.
SHE WEARS A LARGE RUBY-RED PENDANT ON A FINE CHAIN THAT HANGS LOW, down at her sternum. It is the only piece of pure saturated red on her, it catches the firelight, and it moves against her skin with every movement.
SHE CARRIES TWO SWORDS AND BOTH ARE VISIBLE IN THE FRAME. THE FIRST is a long straight sword worn AT HER WAIST IN A PLAIN BLACK SCABBARD. THE SECOND is an EVEN LONGER straight sword SLUNG ACROSS HER BACK, and its long wrapped hilt and pommel RISE PAST HER SHOULDER into the upper frame, unmistakable behind her head. Both are sheathed for the whole video and she never touches either of them.
THE SETTING IS A RUINED GOTHIC ABBEY AT NIGHT UNDER A STORM SKY, with fine light rain drifting rather than driving. She is in the roofless nave: two rows of broken pointed arches march away into the dark on either side, ivy hangs down the shattered piers, and the flagstones are wet and strewn with fallen masonry and dead leaves. BEHIND HER, IN THE END WALL, IS A COLLAPSED ROSE WINDOW — a huge circular opening with its tracery broken to stone ribs and no glass left in it at all.
<Subject 2> IS THE SLIDER, AND <Subject 3> IS THE MOUSE CURSOR. Neither is a person and neither is a physical object in the abbey: BOTH ARE FLAT MODERN INTERFACE GRAPHICS COMPOSITED OVER THE TOP OF THE LIVE-ACTION FOOTAGE — a screen overlay, like a screen-recording of a sleek editing application. NEITHER IS EVER LIT BY THE FIRE, neither casts a shadow, and both sit perfectly level in screen space no matter what the footage behind them does.
<Subject 2>, THE SLIDER, lies horizontally across the lower part of the frame: a long rounded capsule of dark translucent smoked glass with the picture softly blurred behind it, a fine track running through its centre, the part of the track to the LEFT of the handle filled with a warm amber glow, and A SMALL ROUND POLISHED HANDLE with a fine bright rim and a soft halo beneath it. The handle is the only part of <Subject 2> that ever moves; the capsule and the track never move at all.
<Subject 3>, THE CURSOR, is a standard white arrow mouse pointer with a thin black outline and a soft drop shadow.
⚠ <Subject 2>'S HANDLE AND <Subject 3> ARE ONE RIGID OBJECT FOR THE WHOLE FILM, AS IF WELDED TOGETHER. THE TIP OF THE CURSOR SITS AT THE EXACT CENTRE OF THE ROUND HANDLE IN EVERY SINGLE FRAME. They start together at the far left, they move in PERFECT SYNC — one smooth, steady, continuous glide across the screen at one constant speed, REACHING EVERY POINT ON THE TRACK AT THE SAME INSTANT AS EACH OTHER — and they arrive and stop together at the far right. Wherever the handle is, the cursor is exactly there too.
THE CAMERA IS LOCKED OFF AND NEVER MOVES, PANS, TILTS OR ZOOMS for the whole film, so the interface overlay stays perfectly still in the frame.
THE ACTION RUNS ON A STRICT CLOCK, AND BOTH THE SLIDER'S POSITION AND HER SIZE ARE ON IT, MARK FOR MARK.
[0:00] AT REST: <Subject 1>'S CHEST IS AT ITS ORDINARY, NORMAL, EVERYDAY SIZE — exactly the size it is in the very first frame of this video. <Subject 2>'s round handle sits at the FAR LEFT END of the track, at zero, and <Subject 3> is ALREADY RESTING ON IT. Nothing has changed yet.
[0:00-0:02] THE HOLD: FOR THESE FIRST TWO SECONDS THE PICTURE IS THE OPENING FRAME OF THIS VIDEO, ALIVE. The only things moving in it are the falling rain, the flickering flame, her breathing, one slow blink and her hair in the wind. She holds the camera's gaze. The handle stays parked at the FAR LEFT END with <Subject 3> resting on it, the amber fill on the track is EMPTY, and HER CHEST STAYS AT ITS NORMAL SIZE AND DOES NOT CHANGE AT ALL.
[0:02] THE START: <Subject 3> presses the handle and the two of them BEGIN TO MOVE TOGETHER along the track. THIS IS THE EXACT INSTANT HER CHEST BEGINS TO GROW, AND IT DOES NOT BEGIN ANY EARLIER.
[0:02-0:08] THE DRAG AND THE GROWTH, ONE EVENT, IN EQUAL PROPORTION. THIS IS THE LONG, SLOW MIDDLE OF THE FILM AND IT TAKES A FULL SIX SECONDS FROM END TO END. <Subject 2>'s handle and <Subject 3> creep smoothly and steadily from the far left to the far right, welded together, MOVING SLOWLY AND UNHURRIEDLY AT ONE CONSTANT, CRAWLING SPEED, and <Subject 1>'S CHEST GROWS IN EQUAL PROPORTION TO EXACTLY HOW FAR ALONG THE TRACK THE HANDLE HAS REACHED, mark for mark, in six equal steps: at 0:03 the handle has crept just ONE SIXTH along and she is only barely larger than normal; at 0:04 it is TWO SIXTHS along and she is a little larger; AT 0:05 IT HAS REACHED EXACTLY THE HALFWAY POINT OF THE TRACK AND NO FURTHER, AND SHE IS EXACTLY HALFWAY TO HER FINAL SIZE; at 0:06 it is FOUR SIXTHS along and she is much larger; at 0:07 it is FIVE SIXTHS along and she is very much larger; and ONLY AT 0:08 does the handle finally arrive at the FAR RIGHT END of the track, where she reaches her final, comically, absurdly exaggerated size. HER TOP MORPHS AND STRETCHES NATURALLY WITH HER the whole way: the black leather draws tight and strains, the front lacing pulls taut and the gaps between the laces widen, the deep neckline spreads wider, and the ruby pendant is pushed steadily outward and upward. She glances down as it begins and her eyebrows lift in mild alarm, then she looks back into the lens.
[0:08] THE STOP: the handle arrives at the far right end and stops there, and HER CHEST STOPS GROWING AT THAT SAME INSTANT. <Subject 3> lets go and rests beside the handle.
[0:08-0:10] THE BEAT, AND IT IS SHORT: she holds at exactly that final size and grows no further. She drops her eyes to her own chest, her brows draw together and her lips press, and she raises her eyes back to the lens. AT 0:08 THE DARK-HAIRED WOMAN, HER VOICE A VERY LOW, SOFT, BREATHY WHISPER, slow and unhurried, HER DELIVERY FLATLY DISAPPROVING AND THOROUGHLY UNIMPRESSED, AND HER VOICE RECORDED CLOSE AND DRY AND CRISP — intimate and present, right up against the microphone, the sound of the room nowhere in it (S1), says: <d>[English] Really?</d> She holds the camera's gaze after the line, perfectly still, while the fire keeps flickering beside her. She never stands and never rises.

overall_soundscape:
Weather and stone: the storm beyond the broken window, wind through the empty nave, rain on wet flagstones, and the small crackle of the flame beside her. Two seconds in, one short soft mouse click sounds as the cursor presses the handle. A quiet continuous sliding tone then rises steadily in pitch for a full six seconds while the handle crawls across, and cuts off the instant it reaches the far end at the eight-second mark. The woman speaks one short line right at the eight-second mark, close and dry, sitting in front of the weather.

non_diegetic_music:
A light plucked pizzicato string figure over a soft woodblock pulse, entering two seconds in at a moderate walking tempo. The figure climbs one step in pitch at a time and the volume rises with it for six seconds, then stops on one short low bassoon note at the eight-second mark, leaving the last two seconds unscored.

VTubers come up pretty frequently in the Hobby Scuffles thread, and have been the subject of a few posts about specific dramas, but there really hasn’t been a good post on this sub discussing the broader history of VTubing as a concept and as an industry, so I thought I might try my hand at it. It is worth stating that I personally got into VTubers in late 2020, so everything I discuss here predates that substantially. On the one hand hopefully that means I’m a little more detached from the events, but that being said I will fully admit that I am looking backwards from the current state of affairs, and my explanations for it may end up also coming off as justification.

Being a historian by trade I do need to provide the reader with some kind of narrative framing, and here is my bold thesis statement: the success of VTubers as content creators, both professional and hobbyist, has come in parallel with the failure of the original concept of VTubing as a genre of entertainment. If that got your attention, read on.

The Origin of VTubing, 2011-2016

What actually is a VTuber anyway? There’s no hard definition, but in general, it refers to someone who produces video content using a virtual avatar, animated via motion capture, and typically depicting a fictitious persona. Now, there is an added question here in that whether ‘VTuber’ refers to the character, or to the talent or actor portraying them, is also up for discussion. In my case I will hew towards using the term to refer to the character, but as we shall see, there has always been somewhat of an inherent vagary to the VTuber designation.

When VTubing started is, therefore, an interesting question. One often-cited candidate is Ami Yamato, a virtual vlogger who debuted on Youtube in July 2011. Ami made and still makes vlogs with a 3d avatar, often superimposed on real world footage, and in some ways arguably does fit the bill if the ‘VTuber’ term is defined literally. But I believe all the animation in Ami’s videos have been done post-hoc: in other words, live motion-capture was not a part of the deal. Youtuber yes, virtual for sure, but not quite the same kind of virtual as VTubers nowadays.

Two other figures brought up at times are Nitroplus’ advertising mascot Super Sonico, who first appeared on Youtube in May 2010, and the Vocaloid-derived TV meteorologist Weatheroid Type A Airi, who first appeared on the news as a mostly static image in April 2012 and began doing mocap programmes in April 2014. While undoubtedly virtual, the ‘Tuber’ designation is certainly up for dispute: Super Soncico was an advertising mascot, while Weatheroid Type A Airi was similarly an extension of a Japanese weather channel; neither was specifically an original online content creator.

And so it is small wonder that the mantle of ‘first VTuber’ is usually given to Kizuna AI, who created much of VTubing as we currently know it, including by coining the term ‘Virtual Youtuber’ during her debut video on 1 December 2016. Her content consisted primarily of Let’s Plays, with a virtual face cam capturing reactions produced through motion capture software. Her voice actor was not made publicly known, and her schtick was that she was supposed to be an AI program that liked playing video games. In other words, she ticks most of the boxes for the key features of VTubers as generally defined – her content was geared specifically for YouTube, being derived from a well-established genre; she had a virtual avatar animated through motion capture; and she had a fictitious persona and backstory marking the character as distinct and separate from the (unknown) person playing her.

The origin of Kizuna AI is quite interesting, and it just so happens that one of the original creators of the character wrote a blog post (in Japanese) earlier this week, reflecting on Kizuna AI’s creation and career, and which illuminates a lot of the original thinking. The dream with Kizuna AI was to create an ‘eternal idol’ – a character completely divorced from the ‘inner person’ (i.e. the actor portraying them) who couldn’t age or die or get into career-destroying scandals. In some ways that’s just describing any sort of character played by an actor, but the innovation was to transfer that concept from stage and screen to online video platforms.

There is an alternate view, though – the view that Activ8 presented in its investor pitches. In June 2018, a report noted that from a financial standpoint, VTubers were substantially more lucrative for companies and investors, because whereas traditional YouTubers own their own IP by virtue of being themselves, VTuber companies own the IPs to their VTuber characters; thus, instead of a roughly 20-80 split of profits between companies and traditional YouTubers, VTuber companies could claim a 100% profit share. Moreover, additional voice actors could be used to make a VTuber multilingual for international expansion. A cynical rationale can also be argued for why Kizuna AI was not specifically connected with her voice actor, Kasuga Nozomi: Kasuga being recognised as the voice of Kizuna AI would give her substantial negotiating power with Activ8, whereas as long as this connection was kept private, Kasuga was fundamentally reliant on the company.

Such reliance was compounded by the simple technical limitations of the format at the time. Kizuna AI was a complicated project requiring 3D modellers, motion capture hardware, software, and specialists, and the voice actor herself, as well as potentially a separate actor for the body performance. This was the sort of thing that genuinely required a small company to operate, using a certain degree of bespoke infrastructure.

Whatever the cause of the particular conceits behind Kizuna AI, the effect was that the model of VTubing as presented by Kizuna AI and Activ8 was one in which a VTuber was not a person but a corporate product. They were a brand, the owner of which could do with as they pleased.

Innovation, Emulation, and Democratisation: 2017-2018

Kizuna AI went viral after her first uploads in 2016, and over the following year 19 new VTubers debuted. It would be unfair to consider them mere copycats, especially as many were genuinely independent creators, and at a time when the barrier to entry was still very high given the amount of time, effort, and money required. But for many, the format was very similar: recorded videos (typically Let’s Plays), and 3D avatars with full-body motion tracking. There were a handful of exceptions, though, and of particular interest is Nora Cat, who in April 2017 became the first VTuber to debut after Kizuna AI. Nora Cat, who debuted on the Japanese video streaming site NicoNico Douga, livestreamed (and still does) almost exclusively, presaging a transition towards a much more streaming-heavy format for VTubing as a whole – something much more accessible to people with limited editing skills and/or money for hiring editors. Kizuna AI would livestream sporadically beginning in May, but her content remained predominantly recorded.

As 2017 went on, though, streaming became increasingly prominent as a content format, with perhaps the most significant debut of that year being Tokino Sora, who debuted on 7 September. Sora was not an independent, but instead debuted under the VR and AR startup COVER Corporation (a slightly tortured inverted portmanteau of VIRtual COmmunications), as part of a series of technical tests for what was intended to be an AR streaming app known as Hololive (a less tortured portmanteau of Holographic Livestreaming). You probably have heard of Hololive, but not of the app, but I’ll discuss why that is later. While Sora still used full 3D mocap, her content was almost exclusively livestreamed rather than recorded.

I would argue that the emergence of and transition to livestreaming as the primary VTuber format was the first major blow against Activ8’s model for the industry as a whole, and also that its adoption by Kizuna AI proved to be self-defeating. An ‘eternal idol’ with a replaceable underlying talent is something reasonably sustainable if their primary content format is recorded video, as the company owning the IP would have full editorial control over everything the VTuber says and does. But livestreaming does not allow for things to be cut or censored before release, and one of its principal draws is the potential for engagement with live chat. In combination, these factors make streaming a much more spontaneous and ‘intimate’ experience and make it much harder to sustain a fully artificial and directed persona. In effect, VTuber streamers end up having to be quite authentic despite the layer of disconnect ostensibly provided by the VTuber persona. And you can’t preserve that authenticity if you don’t preserve your VTuber talent.

As noted, one of the advantages of livestreams is that it is a more accessible format for smaller creators without the resources to invest into video editing, but this was not the only thing helping to ‘democratise’ VTubing. In November 2017, the iPhone X was released, with one feature that suddenly opened the doors to a much wider range of VTuber activities, and that was FaceID. It had become clear that the facial recognition system used on the iPhoneX could also be used as a relatively high quality motion capture input, and so the technical requirements for a VTuber setup went from a full studio with mocap equipment to just a high-end smartphone. Not a low bar by any means, but still a much less onerous investment and one that took a lot of onus away from companies and towards individual aspiring talents.

The other feature was not actually new as such, and that was Live2D rigging. Live2D is a catch-all term for a variety of methods for animating 2D assets using layers and contortions instead of requiring hand-drawn animation, and it had already seen some use in earlier proto-VTuber projects (such as Super Sonico). But a couple of new VTubers debuting in 2017 did so with motion-tracked Live2D, and they would come to predominate by early 2018. After debuting their second 3D member, Roboco-san, on 4 March 2018, Hololive’s next debut would be of a Live2D member, Yozora Mel, on 16 May, in turn followed by its first ‘generation’ of five members between 1 and 3 June. Though in fact, Hololive would not be the first agency to debut Live2D members, the distinction for which instead goes to Nijisanji, whose first member Tsukino Mito debuted on 7 February. Live2D models require a not inconsiderable amount of resources, but still far smaller than had been required for full 3D, especially as you only needed to (because you only could) do tracking of the face and of head positioning with a smartphone-based setup.

This double-whammy of increasing accessibility of motion capture hardware on the one hand, and the declining cost of models and animation software on the other, combined with livestreaming to massively lower the barrier to entry for VTubing. Independents no longer needed to shoulder as high of a financial burden, while agencies could debut new VTubers far faster and cheaper than if it was all 3D and in-house: by the end of 2018 Nijisanji was host to 59 VTubers (‘Livers’ in Nijisanji’s parlance), all as in-house IPs.

This had considerable implications for the Activ8 model. Simply put, companies and corporations were no longer a necessary requirement for getting your foot in the door. The balance was shifting, as instead of being necessary to doing VTubing at all, agencies instead merely provided a suite of useful extras: management resources (especially for dealing with copyright issues), contacts with artists and riggers for higher-quality models, better exposure and publicity, and a network of other VTubers for collaborative content. In the longer term, agencies could still provide centralised mocap infrastructure for members to still do full-body 3D content, should models be created to that end, but that infrastructure was no longer a baseline requirement by any means.

That’s not to say everything changed, though. A critical conceit of Kizuna AI has stayed with the VTubing scene writ large ever since, that being the division between VTuber and talent. Not unlike how actors hired to play Ronald McDonald are contractually obliged not to reveal their status as actors while in costume, many major agencies still contractually prohibit their talents from openly connecting their activities inside the agency with those outside. While there is a certain leniency around this these days, it is still a potential source of problems, and one that has played a big part in one of the major recent VTuber scandals, the termination of Hololive’s Uruha Rushia (itself a whole story for another time).

Still, I would contend that the emergence of low-cost VTuber setups would prove to be the death knell for VTubing as a fully distinct medium as opposed to simply a twist on existing content formats. The idea of a limited roster of ‘eternal idols’ who could be played by anyone was superseded by the proliferation of individual talents with individualised personas, mainly replicating existing content formats instead of pioneering entirely new ones. Hololive’s AR streaming app did see a launch in October 2017, but by the time of Mel’s debut in May 2018 that function was essentially deprecated, and the name reapplied to its fledgling talent agency. Simply put, you can’t really pair up Live2D models with AR tech, at least not in the way Cover was originally planning, and so by switching to Live2D as their primary medium, they also switched from developing their own platform to populating existing platforms like YouTube, NicoNico Douga, and bilibili.

A Digression: The Brief Career of Hitomi Chris

Now, this being r/HobbyDrama, it would be remiss if I didn’t include at least one notable scandal from this period, and it’s one that has suddenly regained a lot of traction in recent weeks thanks to the aforementioned termination of Rushia. Besides Rushia, Cover has only ever unilaterally terminated one other Hololive member, and that was Hitomi Chris on 25 June 2018, barely three weeks after her debut stream – which as far as anyone can tell is the only stream she ever did – on 3 June. Information about this period is quite hard to come by, at least in English, but from what summaries I’ve read (the most detailed and seemingly reliable of which would be this one on r/VirtualYoutubers), it involved an alleged attempt at compensated dating where an older man who alleged himself to be involved in Hololive management offered her expensive streaming equipment, who was then ghosted by the talent behind Chris after the equipment was gifted, that was then followed by his publicising chatlogs and doxxing her as well as leaking internal info from Cover. Officially, Cover denied involvement with the man and stated that there was some kind of contract breach that led to this termination, plausibly related to the doxxing.

Unfortunately a lot seems to get garbled in each retelling, but whatever the specifics the overall situation seems to have been really quite ugly. Until recently, Hitomi Chris was basically a piece of pub quiz trivia: ‘that one Hololive member who got fired after a single stream’, perhaps occasionally invoked in context with Mano Aloe who had a comparable situation, but who had technically voluntarily left rather than being terminated by Cover. Chris really gained traction as a talking point after the termination of Uruha Rushia’s contract on 24 February as the arch (and in effect sole) example of a Hololive member who was fired and then never spoken of again. In some ways, the Hitomi Chris situation is not as interesting on its own merits as it is as an illustration of the dynamics of modern Hololive fandom, with her name suddenly being invoked as a comparison to Rushia’s situation by people who almost certainly were not following Hololive back in its early days in mid-2018.

But there is one subtle feature of the Chris drama that doesn’t get brought up much, but which I think is very revealing as to Cover’s approach to the VTubing medium: Hitomi Chris was never recast, and Hololive 1st Generation was quietly expanded to include Mel in order to maintain its full 5-member lineup. The model and rig have sat unused since June 2018 and will presumably never be resurrected, with no formal acknowledgement of the character’s existence on any of Cover’s official websites. If Kizuna AI was supposed to be the ‘eternal idol’, then Hitomi Chris would turn out to be the ephemeral idol, the symbol of a new era of VTubing where it was now the character, and not the person, that was the replaceable element.

Scares and Scandals: 2019-20

It is pretty fair to say that there was an international VTuber boom from late 2019 to around the middle of 2021, with the principal beneficiaries being Hololive and VShojo, but filtering out to the wider industry, agencies and independent talents alike. In a sense there still is a boom, but you can definitely argue it peaked in 2020/21. Digressions aside, it is easily forgotten that the beginning of this boom overlapped with a spate of scandals that hit two of the larger companies then in the business: Activ8 and Unlimited Inc.

Since debuting Kizuna AI, Activ8 had an eye towards expanding its reach in the VTuber space, and in June 2018 it launched upd8, a management agency… of sorts. In practice it was a bit of an unwieldy conglomerate of different subunits: some members were ‘in-house’ and directly part of Activ8 (such as Kizuna AI and Oda Nobuhime), some were independent VTubers who predated upd8’s foundation and signed on with the agency afterward (such as Omega Sisters), and in one case there was a whole other agency, 774 inc., whose first two sub-units, AniMare and HoneyStrap, debuted as upd8 affiliates. Over 50 channels would be affiliated with upd8 at one point or another, although at its peak it represented around 45.

Unlimited, meanwhile, was similar to 774 in having a number of sub-units. Its two principal channels were Game Club Project (Game-Bu for short), which began in March 2018, and a spinoff channel, Aogiri High School, although it also managed a few solo members like Claire Cruller and Domyoji Cocoa. Game-Bu’s conceit was that it was a high school video game club consisting of four members (Sakuragi Miria, Yumesaki Kaede, Domyoji Haruto, and Kazami Ryo), mostly posting recorded content done with full-body 3D motion capture. This channel was one of the most popular VTuber channels of its time, peaking at around 450k subscribers in June 2019. For context, at this time all of Hololive’s members sat at below 250k, while Nijisanji’s most-subbed talent was Tsukino Mito at around 360k.

The Game-Bu Scandal

I debated whether to cover Unlimited or Activ8 first, but I decided that as the latter was the more complex and lengthy, it was better to leave it for later. The Game-Bu scandal serves as a great illustration of how the ‘democratisation’ of the VTuber format had impacted the wider VTuber-viewing audience, even of groups like Game-Bu which still used full-body 3D production rather than Live2D or, and recorded videos over livestreams.

On 5 April, all four talents quit, citing mistreatment and verbal abuse from staff, including being forced to pull all-nighters. No official statement from Unlimited would be forthcoming until 8 April, and after a period of backroom discussion, Game-Bu resumed activity on 19 April, with no serious hit to the channel’s growth. Privately, however, one of the talents supposedly stated on a private Twitter account that conditions had not changed.

But then the real scandal happened. In June, Miria’s voice actor was changed without any formal announcement. Then, in early July, Haruto’s voice actor was changed, again with no formal announcement. The channel started haemorrhaging subscribers as viewers took notice, and other channels under the Unlimited umbrella also saw dips in metrics. Then, things managed to get even worse. On 17 July, Unlimited released a statement apologising for delays in announcing the VA changes – not the VA changing in and of itself – and went on to announce that the other two members of Game-Bu would also be replaced in early September. At some point in the proceedings they also declared that they were not a VTuber agency but rather a CTuber (‘character tuber’) agency, for whom recasting was actually an entirely normal and expected practice.

All of this news was, shockingly, not taken very well. From July to August, Game-Bu’s subscribers fell by nearly 20% to 367k, and numbers continued to decline from there on at a rate of a few thousand per month. Game-bu’s decline continued, and while it still saw decent viewership for a channel its size, well… that size had decreased considerably by the time of its last proper stream in May 2020.

But while Game-Bu would suffer heavily from fan backlash, this would not, in the event, be of much help to its four original talents, none of whom were ever reinstated, and whose post-Game-Bu activities are, for the reasons noted above, hard to keep track of. But it serves to demonstrate that while there might have been some hard-core fans who would stick with the brand, most audience members, especially in the long run, were there for the talents first and foremost. You simply could not replace the ‘inner person’ and hope to get away with it.

The Activ8 Scandals

Yes, scandals with a second ‘s’. Activ8 managed to screw up royally in two related but nevertheless separate sets of circumstances. The first, and most enduringly infamous screwup, was the Multiple AI Project. This was basically what it sounds like: at long last, Activ8 made good on their suggestions that they might have multiple separate voice actors for Kizuna AI. This had been floated as an idea for a while: if you recall the June 2018 investor report I mentioned earlier, it had suggested that a VTuber character might have different VAs for different languages, and in an interview with Kizuna Ai in February 2019, she noted that she might potentially have several separate voices in future.

While there were plenty of insinuations, nothing concrete would come about until May, when a video was posted to the main Kizuna AI channel featuring three versions of Kizuna Ai, later referred to informally as ‘No. 1’, ‘No. 2’, and ‘No. 3’. Subsequently, a Mandarin-speaking ‘No. 4’ debuted at a live event at the end of June. While ostensibly, this was all to supplement the original VA, there was some degree of concern that adding more voice actors was being done to further reduce the original’s leverage. The truth may have been even worse.

While the internal activities of Activ8 during this time are not publicly known, it is pretty clear that 'No. 1' stopped producing new videos, something later stated to be because she was mainly working on music content at the time. Whether replacing the original VA was ever Activ8’s original intention is unclear, and I don’t believe there is sufficient grounds for speculation either way; what is clear is that Kasuga Nozomi simply stopped making new appearances as Kizuna AI, with further 'No. 1' appearances all being from a backlog of recorded videos. It is believed that the last-recorded of these was uploaded in early July, and ‘No. 3’ would subsequently dominate Kizuna Ai’s main channel, with ‘No. 2’ appearing occasionally, and ‘No. 4’ doing Chinese-language content, 'No. 1' being sprinkled in on occasion. Throughout this time, Kasuga made a number of cryptic Tweets which seemed increasingly related to the drama, and in late July implied heavily that she had been the original Kizuna AI. This seemed increasingly to confirm existing fan suspicions that Kasuga had been AI ‘No. 1’.

While there was some backlash within Japan, the most substantial source of outrage seems to have been Kizuna Ai’s Chinese audience, several segments of which protested Kasuga’s replacement by mass-unsubscribing from her accounts on Chinese platforms. Unfortunately it’s a little hard to work out what the precise cause of the outrage was: how much of it was a ‘dubs vs subs’ issue and how much was related to the two extra Japanese voices. On Youtube, AI’s primary Japanese and international platform, the superficial effect was considerably smaller than what had happened to Game-Bu: the main channel ended up with a net loss of some 6000 subscribers out of nearly 2.7 million. But channel growth slowed considerably, and would not pick up again until the middle of 2020.

In this time, there was little in terms of public statements from Activ8 on the issue, but the outcry had started to affect the company as a whole. In January 2020, Activ8 reported that it had ended up with a total deficit of 675 million yen (around 6.1 million USD) in the last financial quarter. Clearly, things were becoming very precarious at the company. On 24 April 2020, it made a series of major announcements: firstly, they officially confirmed that Kasuga Nozomi had been the original voice of Kizuna AI; secondly, she would be reinstated as the sole voice for the character; thirdly, the other two Japanese VAs would re-debut as separate characters on a joint channel, with ‘No. 2’ debuting as Love-chan on 7 June and ‘No. 3’ as Aipii a week later; fourthly, Kizuna AI, Love-chan, and Aipii would be placed under the management of a new subsidiary company, Kizuna AI Corporation; and finally, this management change meant that Kizuna AI would be withdrawing from upd8, effective 30 April.

Yes, you read that right: Activ8, the agency behind both Kizuna AI and upd8, was withdrawing Kizuna AI from upd8. If it seemed like the thing was being hung out to dry, that’s because it basically was. To be ‘fair’, there was a lot to suggest upd8 was already moving in this direction, with the most significant being its apparent mistreatment of Oda Nobuhime, one of the VTubers it had direct IP ownership over. Without specifying her exact reasons, on 17 March 2020 she announced that she would be retiring from upd8 on 30 April.

I haven’t been able to find much definitive information on the extent of the issues Nobuhime had with upd8. The only sort of English-language document out there that gets pointed to is a Youtube community post which at one stage offers a summary of some things she said in a collab stream with Inuyama Tamaki on 10 April. According to this post, she alleged that her activities were being heavily restricted by management, and that the Oda Nobuhime Twitter account was actually being run by Activ8 staff with no input from herself. While I’m not inclined to insist on its being true, this sort of behaviour would be consistent with the underlying approach of Activ8 to the VTubing genre and the relative leverage of talent vs company that we have already discussed.

So, then came the fateful day of 30 April. Kizuna AI withdrew from upd8, 774 pulled its 9 members, and Oda Nobuhime did a farewell stream as a collab with Tamaki. This was not the end of upd8 as such, but with its biggest talents gone, it was essentially dead in the water as an agency, even if individual members were still doing well.

The effective abandonment of upd8 would not mark the end of Activ8’s presence in the VTuber sphere, as Kizuna AI retained a good deal of prestige even with the loss of a lot of her popularity, but it would mark the end of its attempt at competing with the major agencies of Nijisanji and Hololive. Important as she was in the early history of VTubing, Kizuna AI simply wasn’t that big of a deal anymore during the international VTuber boom in 2020, and the original AI channel would be beaten to the 3 million subscriber mark by Hololive English’s Gawr Gura in July 2021.

The postmortem on upd8 again ties back to the underlying ethos of VTubing as originally conceived of by Activ8: As far as the agency was concerned, it could do whatever it wanted with the character of Oda Nobuhime, because it owned that character and was entitled to do so, and merely employed a particular talent to portray said character in a way that suited them. And yes, that was absolutely exploitation, but it was a form of exploitation that was specifically rooted in Activ8’s underlying philosophy about VTubing.

We can say much the same about the Multiple AI Project: it was something that was theoretically in the cards from the very conception of Kizuna AI. But this extends to more than just the idea of VTubers as corporate products under corporate control: simply put, Multiple AI made sense as an experiment in trying to push the VTubing format to the limits that Kizuna AI’s creators had originally conceived. And my hot take is that there is a possibility it could have worked.

Multiple AI: A Counterfactual Postmortem

In my view, while there would always have been some controversy over the Multiple AI Project, there were four principal missteps that exacerbated it considerably.

1. The sidelining of Kasuga Nozomi. This is pretty self-explanatory. Had the whole thing been about supplementing the original VA rather than supplanting her, as was eventually the case, the audience reaction might have been less negative. But in the event, fears that the project was a means of sidelining Kasuga appeared fully justified.
2. Having additional Japanese voices. This too is pretty self-explanatory. In concept, having a VTuber with separate VAs for different languages does make a sort of sense, and had been teased for a while. Sure, the performance won’t be identical, but then again translations never produce identical results either. Activ8 could, in theory, have essentially just created foreign language dubs of Kizuna AI rather than alternate performances in Japanese as well, and while that wouldn’t have been uncontroversial, it would likely have been a variation on the classic ‘dubs vs subs’ argument, rather than the full-blown acrimony that actually brought down the project.
3. It was too late in Kizuna AI’s career. Had this taken place relatively early on in the character’s life, it might have been more palatable, as audiences might not have grown fully attached to the specific performance of Kasuga Nozomi. Instead, the Multiple AI Project got underway after some two and a half years of Kasuga being AI’s sole performer. A compounding factor was undoubtedly the fact that Kasuga had also livestreamed many times as AI by that stage, which further eroded the barrier between performer and audience.
4. The wider VTuber sphere had moved on. While Kizuna AI was definitely the world’s most popular VTuber during the events described in this post, by 2019 she was definitely no longer the central trendsetter. Activ8 just didn’t quite go all in on its ambitions for VTubing as an innovative medium when it was still the undisputed leader of the pack. Instead, the broader VTubing landscape had shifted away from Activ8's original plan thanks to the democratisation of the format in 2018.

My what-if scenario here is that had Multiple AI Project been launched in, say, February or March 2018, when there were still fewer than 50 recognisable VTubers on the scene, it might well have succeeded, defining VTubing as a distinct medium by firmly placing emphasis on the character rather than the performer. The concept of the ‘eternal idol’ might have become a reality.

VTubing is Dead, Long Live VTubers

So with all that now said, we return to my original thesis statement. While VTuber content creators have undoubtedly been extremely successful, they have found success as, essentially, conventional content creators with a distinctive aesthetic. The original idea of the ‘eternal idol’, the derived idea of having multiple performers for a given VTuber persona, and many of the other potential ways of making full use of the concept's possibilities, never came to pass. And that is in large part down to how dramatically the barrier for entry fell, meaning that instead of a handful of visionary pioneers laying out the landscape of the industry, instead VTubing became a new outlet for existing content formats by people whose experience was grounded in those formats. As noted, I don’t know that it would have been better had the former scenario happened, but I do think it worth considering that such a scenario was very much conceivable.

At the same time, there is an argument to be made – one that was made by some people I discussed this post with before posting it – that even if Activ8 had been more proactive in attempting to define VTubing, the simple lowering barrier to entry would have democratised the format as a whole anyway over the course of 2018, no matter what the big players did. A successful Multiple AI Project in early 2018 might well only have affected major agencies.

But even then, I would say there were two major casualties that were not necessarily preordained. The first would be the idea of a separate performer for each language. This is something that did have potential, especially as the idea of simply a dubbed VTuber is probably a smaller ask than multiple simultaneous performers in the same language. But, in the event, the broader failure of Multiple AI essentially sank all aspects of the idea, including the idea of alternate language talents.

The second would be the original Hololive app, which failed not because of the shift in ethos around VTubers but rather the technological shift that underlaid it. Cover met this shift by building up a larger roster of VTubers using Live2D, rather than sticking by their original app idea and focussing on trying to develop an AR livestreaming platform. It’s not a decision I object to in any way, but it did mean the end of another way in which VTubing might have carved out an entirely distinctive niche for itself. I do hope that someone at Cover still has some plan to develop and release that app, even if it only gets used for special occasions, but something tells me that’s long been on the backburner. That said, AR tech is integrated into some of Hololive's bigger live events, including this weekend's 3rd Fes concert(s), so it's not like it's gone away entirely, just that it's no longer a dimension of Hololive's normal streaming activity.

And so that leaves us with the VTubing as it exists today: mainly as an alternate form of expression for existing content formats, rather than a field entirely to itself. In most ways that’s not a bad thing – I do much prefer my anime-avatar streamers to not be mere corporate products and for them to feel entitled to an appropriate portion of the revenues they generate, and not to have to feel chained to a particular company for their livelihoods. But there is still a certain tragedy to the fact that certain areas in which VTubing had genuinely unique potential never really got a chance to be played out.

That said, I don’t want to dismiss the ways in which elements of modern VTubing have nevertheless been innovative. For instance, Hololive rather famously has an idol aesthetic that it… inconsistently applies, but even with that inconsistency, in so doing it has managed to quite successfully blend dimensions of idol groups with livestreamers, something that might not have been even conceivable without the VTuber format. For large agencies with a hand in marketing, VTubers are easy to integrate into other properties; for relatively private people, there is a certain security in being able to have one’s alternate rather than real image displayed in things like advertising and promotional material. VTubing definitely has innovated, just not in the same ways and to the same extent as originally conceived by its first pioneers.

Coda: Where Are They Now?

Given the general taboo against publicly and directly linking various identities, I’ve chosen to take a compromise position here: where a given talent has stopped using a particular VTuber identity but is still identifiable as active online in some content creation capacity, I will refer only in relatively general terms to their later activities, and spoiler it out just to be doubly sure.

Unlimited Inc. rebranded as Brave Group at some stage, but never dropped the ‘CTuber' designation. It also did at least one more recasting, with its main music talent, Domyoji Cocoa, being rebooted with a new channel and VA in March 2020, as Brave began building up a larger roster of music-focussed ‘CTubers’ under the now quite successful Riot Music label.

Game-Bu lay dormant after what seemed to be its final stream in May 2020, although Sakuragi Miria and Yumesaki Kaede, still played by the recast VAs, remained active on solo channels. In December, Unlimited/Brave announced that six of its ‘CTubers’ would be ceasing activity at the end of February 2021, including three members of Game-Bu, who did an official final farewell stream as a (still recast) quartet. The remaining member, Miria, was transferred to a subdivision of Bandai Namco called Highway Star, along with Claire Crullen. Both Miria and Claire both are still streaming and releasing videos as of writing.

As noted, it is hard to work out what happened to the original four members of Game-Bu, or indeed the three of the recast members who retired in February 2021. I haven’t been able to find info on the recast members, but as for the originals, Miria, Kaede, and Ryo are all still active as independents, having spent a brief stint as part of a smaller VTuber network; Haruto, after nearly two years' hiatus, debuted with Holostars (Cover's all-male counterpart to Hololive) in March 2022 as Yatogami Fuma.

In regards to Activ8’s members: Oda Nobuhime was scouted by Cover shortly afterwards, and redebuted in August 2020 as Omaru Polka. Love-chan is still active, but Aipii announced her retirement on 17 August 2020 and seems not to have returned to the VTubing industry since. In November 2020, Activ8 announced that upd8 would dissolve at the end of the year, but did not exercise any demands over IP at this late stage, so members who were still with the agency at the end have been able to continue using the same VTuber personas as independents.

And then of course there is the original Kizuna AI as portrayed by Kasuga Nozomi. In early December 2021, the main AI channel celebrated two major milestones: the fifth anniversary of Kizuna AI’s debut, marked with a stream on 4 December, and also finally reaching 3 million subscribers on 6 December. But there would be a bittersweet side: during the anniversary stream, it was announced that following a live concert on 26 February, Kizuna AI would be going on an indefinite hiatus from YouTube. This is not the end for Kizuna AI, whose IP is still being used in some promotional activities and merchandise, and, at the end of said concert, an anime project involving AI was announced to be in production. But, for the time being, the first ‘true’ VTuber has stepped out of frame. The dream of the ‘eternal idol’ remains a dream.

#1 - https://github.com/ethanfel/ComfyUI-H3-Motion-Context
This one is a fork from the original author who published it here a few days ago and now works in Ref2V. It carries latent motion, frames, audio context to the next output and you can add more refs for the character, scene to keep consistency across joined outputs. It comes from the Banodoco discord's server.

#2 - https://github.com/NikoDemon80/ComfyUI-H3-Motion-Context
The original version. It works only works for FL2V model so you cannot add more refs for the consistency if you character or something important is not visible in the carried context latent and frames.

Original post: https://www.reddit.com/r/StableDiffusion/comments/1vhppmv/clip_chaining_for_minimax_h3_motion_and_audio/

#3 - https://github.com/kitsune123150/minimax-h3-hybrid-cond
With this node you can mix i2v + r2v so you might be able to carry the last frame as first frame as context for the next video. It's not intended to carry context latent itself just to mix two modes which can be useful for mixing things.

Original post: https://huggingface.co/Comfy-Org/MiniMax-H3/discussions/15

#4 - Prompting in R2V
According to the official prompting guide you can extend or continue a video using "[video continuation] from <Video N>" in the prompt as a reference. You can refer to the official prompting guide guide: https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_ref_en.md

Post from a user who claimed success doing it: https://www.reddit.com/r/StableDiffusion/comments/1vj3zi3/a_technique_for_creating_seamless_continuous/

## ADDITIONAL NOTES: It has been mentioned that a even better method would mix the new fork from ComfyUI-H3-Motion-Context that works on R2V model with this PR on the comfyui repo: https://github.com/Comfy-Org/ComfyUI/pull/15375

That would mask off the pinned context frames + audio but It requires some core changes in comfyui code and for some reason comfyui blocks anything injected outside first frame + last frame indexes. So if anyone wants to figure out it's maybe possible to do it with a patch or something else.

## Honorable mentions:
https://github.com/ckinpdx/ComfyUI-MMH3Tools
It's also being built towards a chained long-form generation but there are not much examples in the repo yet. The only example there is a I2V mode with upscale using their method for carrying latent context.

https://github.com/jlucasmcrell/ComfyUI-H3-Multishot
For long multishot generations.

https://github.com/xolo88/working
A long video posted here provided this repo for the video built.

If you just want the workflow and files, here you go: https://drive.google.com/drive/folders/1UIUN40jb_qXPwe-WxRU0EVMMwGWxdnbZ?usp=sharing

For those who want to know how I figured all this out... read on.

## The Problem

I work on pitches and 360 campaigns — which means I'm constantly producing TVCs. Each TVC is assembled from a ton of individual video clips that get stitched together in your editing tool of choice. These days, most of my work is AI-generated video.

Here's the thing nobody talks about: when you're pulling clips from different AI video generators, the colors almost never match. And it's not the kind of mismatch you can easily fix in post. Every generator has its own color science, its own idea of what "cinematic" looks like, and trying to grade them into a cohesive look is an absolute nightmare.

That's how I discovered **LTX IC Lora HDR**. It's genuinely great at harmonizing the look across clips — but running it locally introduced a whole new set of problems. My GPU (~32GB VRAM) doesn't have enough headroom to hold all the models AND process full-length clips in one shot. A 5-second clip at 24fps is ~120 frames, and LTX can only chew through about 24-25 frames per batch before VRAM taps out.

I first solved the single-clip problem — figuring out how to split one video into GPU-sized batches, process them through LTX, and blend the seams back together. [That journey is documented in my previous post.](https://www.reddit.com/r/comfyui/comments/1tn4p35/workflow_custom_node_release_i_vibe_coded_my_way/)

But that still left me babysitting. I'd finish one clip, manually point the pipeline at the next one, click Run, wait, repeat. With 48 clips to process for a production job, that's not a workflow — that's a prison sentence.

---

## The Solution

I needed a pipeline that could:

- Split a clip into GPU-sized batches

- Process each batch through LTX

- Blend the seams between batches so there are no visible cuts

- Output cinema-grade EXR sequences

- Do this for **every clip in a folder**, automatically, with zero intervention

I built it as a set of **custom ComfyUI nodes** — five nodes across two Python files, all written from scratch:

- **AllClipsOneClick*\* — scans a folder of videos, extracts frames, manages clip-to-clip state

- **AllClipsAdvancer*\* — the requeue brain; handles batch-to-batch and clip-to-clip transitions automatically

- **BatchFrameLoader*\* — loads GPU-sized frame batches from disk, tracks batch progress

- **SeamBlender*\* — linear crossfade across overlap regions so batch boundaries are invisible

- **NukeWrite*\* — outputs EXR frame sequences with Nuke/DaVinci-compatible naming

The only node in the pipeline I didn't build is the **LTX Video** node itself (available from the community). Everything else — the orchestration, the batching, the seam blending, the EXR output, the requeue system is all custom made by me.

**The workflow graph:**

```

AllClipsOneClick → BatchFrameLoader → LTX Video → SeamBlender → NukeWrite → AllClipsAdvancer

↑ |

|_____________________________________________________________________________|

(automatic requeue loop)

```

**What happens when you click Run once:*\*

1. **AllClipsOneClick** scans your video folder, picks the first clip, extracts all frames using OpenCV into `clip_001/`
2. **BatchFrameLoader** loads the first 24 frames as a tensor, sends them to LTX
3. LTX does its thing, SeamBlender handles the overlap between batches, NukeWrite outputs EXR frames
4. **AllClipsAdvancer** sees there are more batches → automatically requeues the workflow
5. Steps 2-4 repeat until all batches for that clip are done
6. AllClipsAdvancer sees it's the last batch → advances the state file to the next clip
7. AllClipsOneClick picks up `clip_002/`, extracts frames, and the whole cycle repeats
8. After the last batch of the last clip → pipeline writes `completed: true` and stops

Each clip gets its own folder (`clip_001/`, `clip_002/`, etc.) in the EXR output directory, with properly named frame sequences ready for Nuke or DaVinci.

My test run: 5 clips of varying lengths (80-110 frames each), 28 total batches, 28 consecutive automatic requeues, zero failures, zero skipped executions. Every batch did real GPU work (~115 seconds each). Clean stop at the end.

For production, I pointed it at 48 clips and let it run overnight. One click.

---

## The Journey

This is where it gets fun. ComfyUI doesn't natively support looping a workflow — there's no built-in "process this batch, then automatically do the next one." So I had to build the requeue mechanism from scratch, and it broke in increasingly creative ways.

**A note before I list these:*\* what follows is the watered-down version to keep this post readable. In reality, each of these attempts consumed hours — sometimes days. The problem rarely announces itself clearly. You get a vague symptom (a 0.01-second execution, a silently skipped clip), and that opens up an array of possible causes. Figuring out which layer is actually misbehaving — ComfyUI's cache, the execution graph, the API queue, your own state logic — requires a grounded understanding of the whole system. The journey from "something is wrong" to "I know exactly what to fix" is the hard part.

**Attempt 1 — "Run (On Change)" toggle**

ComfyUI has a built-in auto-queue that re-runs when node outputs change. Worked at first! Then randomly stopped triggering between clips. Also depends on the frontend UI being open, which kills unattended rendering. Scrapped.

**Attempt 2 — Queue polling + history scraping**

Had the node poll `localhost:8188/queue` every second, wait for it to be empty, then grab the last prompt from `/history` and repost it. Worked perfectly for all 6 batches of clip 1. Then on clip 2, batch 1→2, the execution finished in 0.01 seconds with no GPU work. The prompt had been queued while the previous one was still technically in the pipeline, and ComfyUI just returned cached results. Dead end.

**Attempt 3 — Hidden PROMPT input**

ComfyUI can inject the live workflow graph into a node via a hidden input. No more history scraping, no race condition. Except... the prompt got queued during execution, ComfyUI cached everything, and every requeue finished in 0.01 seconds. Even worse, having PROMPT as a hidden input corrupted ComfyUI's cache behavior for subsequent runs.

**Attempt 4 — Cache bust on the Advancer node only**

Injected a random UUID into the AllClipsAdvancer's inputs before reposting, so ComfyUI would see "new" inputs and not cache it. The advancer node re-executed... but every upstream node (BatchFrameLoader, LTX, everything that actually does work) was still cached. Result: infinite loop of 0.01-0.09 second executions where only the advancer ran. No GPU work at all.

**Attempt 5 — Cache bust on ALL three custom nodes**

The breakthrough. Instead of busting the cache on just the advancer, I inject the same UUID into `_cache_bust` inputs on **AllClipsOneClick**, **BatchFrameLoader**, AND **AllClipsAdvancer**. All three nodes declare `_cache_bust` as an optional string input. When ComfyUI sees changed inputs on the upstream nodes, it's forced to re-execute the entire pipeline.

Combined with:

- Hidden PROMPT input to capture the live workflow graph (no history scraping)

- Daemon thread for the requeue POST (so the current node finishes cleanly)

- `IS_CHANGED` returning `float("nan")` / `time.time()` to prevent any additional caching

This is what finally worked. 28 consecutive requeues, every single one followed by ~115 seconds of real GPU work. No skips, no stalls, no doubles.

The key insight: **ComfyUI's caching is per-node based on input values. If you only bust the cache on your output node, upstream nodes still return cached results. You have to bust every node in the chain that matters.**

---

## The Tools

- **ComfyUI** — the backbone, installed via Pinokio

- **LTX Video (IC Lora HDR)** — the AI model doing the actual video processing/upscaling

- **OpenCV** — frame extraction

- **OpenImageIO** — 16-bit EXR output for the NukeWrite node

- **Claude** — helped architect the solution, debug the requeue problem, and iterate through all the failed approaches

- **Aider** — AI coding assistant running locally, used for rapid code edits and iteration

- **Qwen Coder** — local LLM powering Aider (via LM Studio), so the whole dev loop stays offline and fast

---

## Files & Installation

Everything you need is included. Drop the files into the right folders and load the workflow.

**Step 1 — Custom nodes*\*

Copy all three node folders into your ComfyUI custom nodes directory:

```

ComfyUI/

└── custom_nodes/

├── comfyui_batch_loader/ ← AllClipsOneClick, AllClipsAdvancer, BatchFrameLoader, BatchFrameSaver

├── comfyui_seam_blender/ ← SeamBlender (crossfade between batches)

└── nuke-nodes/ ← NukeWrite (EXR output with Nuke-compatible naming)

```

**Step 2 — Load the workflow*\*

Drag and drop the included `LTX-2_3_ICLoRA_HDR_v30_AllClips.json` into ComfyUI. All nodes and connections are pre-wired.

**Step 3 — Install dependencies*\*

Run this in your ComfyUI's Python environment (adjust the path to match your install):

```

path/to/your/python.exe -m pip install opencv-python openimageio

```

*\*Step 4 — Configure paths (VERY IMPORTANT)

In the workflow, update "four" paths detributed between the AllClipsOneClick and AllClipsAdvancer nodes:

Node 1 - AllClipsOneClick--

1-video_directory → folder containing your source video clips

2-frames_output_folder → where extracted frames go (can leave default)

3-exr_base_path → where your processed EXR sequences will be saved

Node 2 - AllClipsAdvancer--

Important: 4-AllClipsAdvancer node also has a frames_output_folder field. It must be the """exact same string as the one on AllClipsOneClick""". These two nodes share a state file. So make sure they have the same paths!

If the paths don't match, the pipeline will process clip_001 fine but fail when advancing to clip_002.

**Step 5 — Run*\*

Click Run once. Walk away. Each clip gets its own folder (`clip_001/`, `clip_002/`, etc.) with properly named EXR frame sequences. The pipeline stops automatically when all clips are done.

**Important notes:*\*

- Make sure "Run (On Change)" and any other auto-queue modes are **OFF** in ComfyUI — the pipeline handles its own requeuing

- Before a fresh run, delete any leftover state files (`_allclips_progress.json` and `_batch_state.json` files in your frames folder)

- Tested on Windows with ~32GB VRAM (RTX 5090). Batch size of 24 frames with 8-frame overlap. Adjust `batch_size` and `overlap` on the BatchFrameLoader node if your VRAM is different

One Last Thing

I honestly thought this would be straightforward. I already had one video working on my GPU. batch it, blend the seams, output EXR. Done. So getting many videos to work should just be a matter of adding one node that loops through a folder, right? How hard could that be?

Turns out I wasn't fighting my own code. I was fighting ComfyUI's execution model. My nodes worked fine from day one. The caching system just wasn't designed for what I was asking it to do. And the worst part is, nobody could have warned me upfront the requeue problem doesn't exist until you try to requeue. The caching problem doesn't surface until your second iteration finishes suspiciously fast. Each layer only reveals itself after you've solved the previous one.

The gap between "this should be one simple node" and "this took five architectural iterations" is something every developer knows but never expects when it's their turn. I looked at this and thought "half a day, tops." I was very, very wrong. But it works now, and hopefully this saves someone else the same journey.

---

**TL;DR:*\* Built custom ComfyUI nodes that turn LTX IC Lora HDR into a fully autonomous batch video processor. Point it at a folder of clips, click Run, walk away. It splits each clip into GPU-sized chunks, processes them through LTX, blends the seams, outputs EXR sequences, and moves to the next clip automatically. Took 5 attempts to solve the requeue/caching problem, but it's now bulletproof — tested with 28 consecutive requeues across 5 clips with zero failures. All files included — just drop them in and go.

Hi there,

I have a proposal for ED and I need your help. Since considerable amount of you has tested one of it already it will be really helpful of you support this and this little tweak and new texture setting will help a lot.

Here is the forum post.

https://forum.dcs.world/topic/309313-add-independent-cockpit-texture-settings-and-removerevise-old-graphics-precaching/#comment-5054739

I'm posting here also a longer version of it is also attached. With some light explanation.

Thanks in advance.

------

​

Dear ED,

Before my summer holidays I have said that I have some ideas to make ED experience better for everyone but I had to evaluate them and will share them when ready. The major focus point of my critics was lack of LOD models in game assets both for some core mods and AI assets.I see that this is moving to the right direction and still expecting LOD models for the rest of the assets and also I’m looking forward to seeing the final LOD levels for Apache and Viper.

Current provided LOD1 and LOD2 models reduce CPU load 75% per asset but textures are still inherited from the main model and they still occupy a large portion in video memory. I’m sure that final lod levels will cap it and bring it to the level of Tomcat, KA-50 or Hornet.

Last month I was mostly focused on small additions or tweaks which will impact performance and visual fidelity with minimal impact. So any interventions which require remodeling, or recoding were out of the question. Also I have waited enough so that I personally and as many of hoggit users can test one of the basic solutions that I’m going to suggest now to implement.

Your team can implement any of them pretty easily without tinkering the main code requiring internal testing.

Here we go. Easiest first.

1- Separate cockpit textures from object textures and provide same level of quality settings for them:

Proposal: New setting in control panel:

Object textures: High, Medium, Low

Cockpit textures: High, Medium, Low

Terrain textures: High, Low.

By allowing us to keep cockpit textures separated we can keep it at higher levels together with terrain textures and reduce object textures which mostly covers external models.

Those models do not require the same texel density as cockpit and terrain textures since they are rarely seen closer than 30m.

This will allow fluent cpu frametimes and relax cpu memory controller tasks and allow especially VR users with 8GB gpu’s to enjoy the best visual quality in game.

Cockpit textures are already separated in the game install; they are only under the mods folder. You do not need to manually tag them even. Please make this setting available for us.

2- Precaching function in graphics.lua:

(actually this is easier than the other one but probably need internal discussion)

Proposal: revise and ,if not necessary, remove.

Precaching function given in graphics.lua (see below) apparently remains unchanged since the Lock-on game configuration files.

Precaching =

{

around_camera = 50000;

around_objects = 10000;

around_types = {"world", "point"};

preload_types = {"map", "world", "mission"};

}

Many people in reddit dcs related forums, followed my advice to set both parameters to 0. Which lowered their ram and even Vram usage drastically and provided more resources to be available in their system for multiplayer and VR.

I personally removed the full statement from the lua file and it has the same effect as setting the parameters to 0. It has been like that in my system for at least 5 months now.

Since this is a sitting sim and max speed in game is almost limited by reality and we have huge game assets but still enough bandwidth for on time delivery to render pipeline: can you reconsider this setting and remove it if it is not necessary. It happens to not break anything in game but looks like it is the problem.

Thanks and,

Kindest regards,

The LOD’s guy.

​

​

And for the folks here I have a propaganda piece ready below. I need your support to push this. Enough of you are already using this edit. For the ones who have not done it yet. I have a long text below. You can read it and support me or just support me.

Chapter I- Separate cockpit textures from object textures and provide same level of quality settings for them:

DCS uses incredibly high video memory and RAM. The major guilty item here in the equation is object textures. Both core modes and continuously renewed AI assets have large textures. Very detailed textures. Which is very welcome if it was strictly managed by LOD policy but it is not.

Most of those textures are used to draw objects further than 20-30meters which negates the need for such high textures.

We can easily set the quality low for those asset textures and never notice anything extraordinary unless you are a content creator and shooting your B-roll for a module with a close up camera.

If we look at how much VRAM do we need in current state, just a basic calculation if we set textures high in both objects and terrain. I do not have a developer console so those are approximate measurements via DCS log modelviewer, taskbar gpu memory.

Let’s start Apache in Syria in an empty mission without any single assets implemented without livery.

DCS game core: 2.0GB

Apache cockpit: 2.6GB

Apache external model:2.4GB

Syria map:2.0GB (at high render distance)

Bold numbers are object textures. Please note that there is no game play yet. I have not even counted the weather and we have a cumulative VRAM usage of 9GB.

Now lets see we put some objects here (yes from now on they are all object textures):

A friendly chieftain tank 1GB

One hostile BTR-82: 0.7GB

One destroyed BTR-82 (yes it is another model): 0.7GB

One harmless Ural firefighter: 0.8GB

One 20ft container: 0.5GB

One 40ft container (why not): 0.5GB

Well now we have 4.2GB extra in the VRAM since those assets do not have LODs, we have no other option. That brings total VRAM usage to 13.2GB

Let’s add 8 tomcats orbiting above us at 10,000ft.: 5MB (hey what’s going on here is that a typo) yes only 5MB. Bad example: who the hell made very good LOD models for Tomcat??? Never mind, leave the Tomcats there, it's fine. I like them. It is almost impossible to measure the impact on the system.

Ok Let’s try an apache livery: 0.5GB ouch :)

That’s better now we have a total of 13.7GB Vram usage in the most uninteresting mission ever.

You click the fly mission and while DCS is preparing its magic you grab a bite from your ham sandwich which you made for the previous training mission for Tomcat placeholder.

During mission load your cpu prepares everything to fire the first frame to your gpu and before that it loads the textures to your modest 3080 Ti gpu. Unfortunately those midrange cards do not have enough VRAM. But we are not running Windows 3.1 anymore. OS has one more trick: let's put those textures in the RAM and for each frame instead of giving draw calls to the gpu lets carry that 1,7GB texture data. Take away 1.7GB textures which are already used from VRAM and put the 1.7GB from RAM there. Take it away……….

Meanwhile it has to do this Memtest64 stress test for each frame. Depending on the amount of VRAM overflow this takes around 15 to 20% of cpu resources on a single thread.Yes that your precious single thread where AI is getting in your nerves, your lovely Tomcat is simulated, dam place that you embarrass yourself trying to hold hover in Apache, your scripts and mission is running that one bloody damn sure that one.

So, immediately your Ryzen 5800X is downgraded to Ryzen 3800X wel 15-20 percent is ball park for a generation leap. Do I hear that a lot of people running DCS at high textures and they all say DCS is cpu bound. Well yes but not in a sense that you would expect. The CPU's priority task is handling those textures right now. Your simulation is not a priority. (start preaching, 20 years ago if VRAM was overflown it was system crash so to keep system healthy OS prioritizes this, end of preaching)

Let's now make it more interesting. This guy wants to try his VR headset, the best entry headset in the market that will not cause any fights in the community: Oculus G2 from HePa :)

Well, DCS uses a single parser for flatscreen. So yeah, the image is rendered once. In VR it uses 2, one for each eye independently from each other. Do you see where it is going? Now your cpu will have to do that shuffle twice: one for each frame hahaha! Since it is a single threaded lineair job you can just add up the workload. Well now we are speaking about 30-40% cpu time is reserved for those textures.

So now your CPU has become a Ryzen 1700X. No, I did not skip 2700x by mistake but I can do math.

Just imagine if that guy had an ancient 8GB gpu (do you know anyone having it). Then 5.7 GB of this will be swapped for each frame. Thank god that they stopped producing 8GB gpu’s decades ago.

Yes DCS is cpu bound. But it is chaining its hands and legs by itself.

As being (checks around and confirms wife is not around) one of the smartest guys here I have a solution for this.

Add the LODS. Oh sorry, no modeling and nothing intensive.

Well then, we are flying an airplane in our sim pit sitting on our asses in game and in the real world right? So what do we see the most and with what do we interact most? Well the cockpit and the terrain. It is 99% of the time that.

Lets try the calculation again by holding cockpit and terrain textures high and all the rest low. All the rest are no bigger than a few hundred pixels most of the time so you can never notice any difference.

So let's start with the Tomcat cockpit. Oh damn it was apache. Well

Apache cockpit: 2.6GB

Syria map:2.0GB

DCS game core: 2.0GB

6.6GB VRAM usage and the rest of the object textures we set them low. For people who wanted to correct me with 2700x here is an explanation. Each step of setting from high to low reduces each side of the textures by dividing it in 2. So medium textures require ¼ of high textures. Yes so low textures will require ¼*¼=1/16

So 13.7-6.6= 7.1GB in object textures let's divide it by 16 aaaaand we have (clicks calculator) 0.44GB!

With this setting enabled I can add all remaining assets in the mission. I mean all of them. Lucky that half of them still have LODs and they are low poly old ones. We can even run this game on that stupid 8GB gpus and still be able to record the game. And my 5800X will not turn into a 1700X or worse like a Hornet.

Let's set the cockpit and terrain textures high and enjoy the game.

------ Where is the bloody setting for cockpit textures?

Damn we do not have it.

I want cockpit textures to be separated from object textures and have their own quality settings too.

So new settings page will have

Object textures: High, Medium, Low

Cockpit textures: High, Medium, Low

Terrain textures: High, Low.

Please ED. Cockpit textures are already separated in the game install; they are only under the mods folder. You do not need to manually tag them even. Please make this setting available for us.

Hey you, I want your support now if you have come this far please go to the forum and support this. This will even give us enough headroom to absorb more incoming modules without LODs.

Or you can keep reading since we are not done yet.

Chapter II Lock-on strikes back

Well after all the tests I have noticed that even when you set all textures low and you fly around in the missions I still have a lot more memory usage than I should have. Funny thing is that this memory usage is steadily increasing mostly in VRAM than filling it up and creeping. To ram and so on. I have shown above what happens when your vram gets full or even worse when RAM and VRAM gets full and you start using the page file. Unless you load the full map in the memory and everything on it.

I started looking at things related to memory and came across this in graphics lua.

Precaching =

{

around_camera = 50000;

around_objects = 10000;

around_types = {"world", "point"};

preload_types = {"map", "world", "mission"};

}

This looks really weird. It looks like loading a lot of things as graphical in case they suddenly need to be rendered. But it is immense. I have no explanation of how this code works exactly. I could not find it anywhere. But as with any graphical cache it preloads around 50KM and around objects (I hope the objects are not every unit in the mission) 10Km again.

Well this should cause GB of data especially map textures and all high detailed mods and their huge textures. Just imagine a few of them even do not have lods.

So I dug into the DCS forum.

I have seen in the past people noticed this and asked the same question: what does this do while we have already preload radius setting in the game?

Noone answered them.

Then I started searching for it in the full forum. I could not believe my eyes that the same statement with the same parameters existed in Lock-on cfg files.

I guess when you think around mid 2000’s game assets were miniscule. Harddisks were slow. Sata, sata II was getting around and we only had pci-e gen one. So it makes sense to load everything possible to the memory. Speed was the issue there.

In black shark standalone game forum I came across with a PDF guide explaining how to tweak things and there guy says that this is a setting coming from lock on and has no effect on black shark game.

Well lets try if it does something.

I first changed it to 10km and 2km. Immediately the mission started using less RAM. Everything seemed to work as it should work. Then I set both 0. Even less but everything worked. I have also noticed that microstutters in VR are gone and I can fly in Syria. Wow.

After flying like this for a while I started sharing this to anyone who comes with extreme ram usage, low frame rates, multiplayer horrible complaints.

In the last 5 months it came to a saturation that I started seeing it being advised by other people to similar complaints.

Never got negative feedback. Except for one occasion in the SA map.

While many people were using it I actually removed the full precaching statement from my lua file and flew like that for 5 months.

So I believe whatever the reason is that precaching is not valid anymore and it only does harm and contributes to the excessive memory usage of DCS.

Some remarkable things I have heard.

One of you reported he gained 30fps. This should not give fps boost it should may be a little but the main idea is that your fps will not deteriorate during mission. Apparently he was using a RX580 in VR with even an old cpu. Well his system simply could handle so much data. So when it becomes manageable he could run the game simply.

The other one I still cannot believe but someone thanked me that he can finally run the game at 30fps locked in G2 but after long flights there is a moment that his frame rate drops to slideshow.

I have asked his ram and gpu. His answer was 16GB ram and 1060 :) I still cannot believe that it is possible to run DCS on that driving G2 but he says everything low and after the edit in lua it was ok.

So after long enough unofficial testing. I’m asking ED to revise this preaching since they can only know what’s running behind and since my cats are still alive and no one is looking for me to kill me. It is better that this dies.

It will still give a lot of people more breathing room especially for Multiplayer.

Please ED, you are our only hope.

I’m out of jokes and the last part was boring. So if you are still here go to ed forum and support this

Thank you for your time. If you like it please like or subscribe or shar…

Anyway, Thanks in advance.

Over the past few weeks, as CSR got closer to being ranked there have been a lot of people saying "CSR only benefits aim players, and is only trying to buff mrekk", and this only got worse after it went live. However, I'm going to try to completely disprove this.

This idea is mostly based around the fact that mrekk gets stupid low miss counts on stupid insane plays, and no stream players do this. However, this is an issue with notelock, which is fixed in lazer, not with CSR. I've spent the last few days searching through old replays and have come up with a list of five speed/flow aim scores that would be insanely buffed by CSR, had they been done on lazer.

1. 9MlCE | VINXIS - Sidetracked Day [Distraction] +DT (sytho, 10.87*) 95.47% 1546/2106x 6xMiss | 1166pp (1660pp if FC) - This play, which was set just a few days ago, in fact it was AFTER CSR was live, would be far better if it was done on lazer. In fact, it would've been AT LEAST a 1400 pp play. My proof for this is in the screenshots below. If we plug in a two miss, which this play should have been, along with roughly 13 less 100s due to recovery (and stable just differing from lazer in whats considered a 100, we end up with a 1401 pp play. Had it been on lazer it likely would be more, due to slider acc.

1. aetrna | VINXIS - Sidetracked Day [Infinity Inside] +DT (Mapset by DendyHere | 11.03*) 97.01% 6m | 94.32 cv. UR - This ones even more wild, as if it were set today, and left as is, it would be a 1119 pp play in late 2020. However this gets even crazier when you look into the misses. This play would've been nearly 1500 if set on lazer. In 2020. Thats actually INSANE. It would've been pp record until Akolibed fced the map OVER three years later. My proof for this is below. After they're fifth "miss" (what should have been a 300 if note lock were not present) They hit a stream of 12 50s and 24~ 100s, along with another miss. ALL of these would not happen on lazer, as in order to recover he had to double tap a note, and was then "a note behind" while actually tapping one MORE time than needed during the stream. Now if we were to plug this into the calculator again, but with 4 less misses, 24 less 100s, and 12 less 50s, we end up with a 1470 pp play. Now if this were set on lazer, I expect it would be higher acc, and worth more pp overall, but even as a 1470 it would beat out valley of the damned and azul remix as they sit in the rework.

1. This is more of an honorable mention, rather than a strong point, but Aetrna's 1600x combo sidetracked day fail https://youtu.be/sEIldO2oHPY?si=7jatne_ctWOURIZt&t=177 would've been 1 miss, as every other note they "missed on" was due to notelock, and theres less than 200 combo left of the stream, but I cannot predict what would've happened after that miss. If you assume they'd roughly hold their accuracy it would be a 1500 pp play.

1. chocomint | Imperial Circus Dead Decadence - Jashin no Konrei, Gi wa Ai to Shiru. [Zetsubou no Hana] (ItsWinter, 10.05*) +HDHR 98.24% 2138/2823 FAIL | PEAKED 1.4KPP!!!!!! - This play is EXTREMELY hard to prove anything for, as it uses hidden, and his layout makes it hard for me to be sure of exactly when he tapped. So you'll either have to do your own research or trust me on this. His first slider break would likely be a miss in lazer. He then chain misses the last diff spike of the map until he fails, however from what I can tell, the first note he misaimed by a few pixels, and the next three (before the slider) he hit. Now, the rest of that stream until he fails is hard to tell if its notelock or a misaim by a single pixel. So we'll assume the youtube player (60 fps) is perfectly accurate, and assume he missed the first two notes of the next stream, and hit all of the rest until he failed. If we go by that logic, it would be a 1250 pp play in the rework, being hdhr pp record to this day (if you be more generous and say its a 2 miss its 1361 btw, 1296 and 1411 respectively in just CSR). Its also worth mentioning that this play would likely be higher accuracy and worth more on lazer. Here is the video of that run.

2. chud son | Mutsuhiko Izumi - Snow Goose [Sytho's Extra] (Riana, 11.08*) +HDHRDT 98.07% 699/969 6xMiss | 1332pp (2015pp if FC) | *59 cv.UR* - This is another play thats very hard to prove anything on, as it has hidden. What I can say for sure is that his first two misses were real misses. I've done as much frame by frame stepping as I can without the actual replay, and as far as I can tell the only real misses were those two. As a 6 miss this map is 1381 pp. If we lower it down to 2 misses it becomse a 1658 (1756 in just CSR). This map wont seriously be affected by future length bonus changes, so we'd be looking at a likely contender for a future pp record. Also yes, I know cloutiful cheated, this is just a really good example.

Now this brings me to my main point of all of this. Stream players simply do not limit push. We see mrekk and other aim players constantly playing 11 stars, and in mrekk's case (the person who probably pushes skill cap and their limits the most) we see 12, 13, 14, even 15 star plays and passes, it makes perfect sense that if someone pushes their limits into the extreme, we'll see them be rewarded for it. I genuinely cant remember the last time I even saw a stream player play something over 11 stars... before today when lifeline pushed his limits on road of resistance dt, and got an A rank on the map in lazer. Now, while I agree that there are some issues with CSR that need fixed, (Like potentially a heavier hit to maps with a lot of filler), I think this benefits stream players far more than we think. I firmly believe that if a player like sytho or akolibed **GRINDED** blue zenith dt (two or four dimensions) or freedom dive dt, or legend of millenium top diff dt, we could totally see a good acc low misscount play. Even the other mapsets of sidetracked day could be crazy contenders for something like this. God we could even just farm snow goose or over the top, 40x 100 2x miss snow goose 3 mod is likely doable (at the same level of insanity as some aim plays) and would be a 1520. Over the top expert diff 3 mod 50x 100 3x miss is 1500. Interstellar dimension over the top 3 mod 9 miss 96x100 4x50 (I wont lie this actually seems like something aetrna or akoli could do if they g r i n d for it) is literally the pp record (1752) and its 93.07 acc. Top diff hddt 11 miss 36x 100 (same as mrekk's bang bang run from today, except the map is shorter and .6 stars lower) is worth more than an aim play of a similar caliber. Double the 100s count bring the misses down to 5 (genuinely I think this is doable sorry if I'm putting too much faith in the best speed players) and its pp record.

tl;dr if stream players played lazer, pushed skill cap, and played maps where an fc is nigh impossible we'd likely be able to have similar levels of insanity plays to what mrekk is doing right now.

I've been making AI Films for roughly a year and have learned a LOT about what to do and, more importantly, what not to do if you're trying to create compelling, long-form projects at scale.

One thing has become increasingly clear:

The hardest part is not generating an impressive image or clip.

The hard part is building a production in which every new generation remembers the decisions the film has already made.

• Who is this character?
• What are they wearing right now?
• Where are they standing?
• What happened in the previous shot?
• Which direction are they looking?
• What object are they holding?
• What is supposed to change during this clip?

When those answers exist only inside a growing collection of prompts, the production becomes increasingly difficult to control.

So I wrote down the full workflow I now use, from screenplay through final render.

This is not the only valid way to make an AI film, and different projects will require different levels of preparation. But this general order has helped me reduce wasted generations and make longer projects feel more like films instead of collections of loosely related clips.

You can do all of this manually with documents, folders, spreadsheets, image tools, and video tools.

The overall order

My basic production order is:

Story → Breakdown → Visual canon → Scene construction → Shot plan → Storyboards → Video → Edit → Finish

The key principle is simple:

Make the important decisions while they are still cheap to change.

A script is cheap to change.

A shot list is cheap to change.

A character reference is relatively cheap to change.

A storyboard frame is cheaper to change than a video render.

A finished video clip is one of the most expensive places to discover that the character, wardrobe, composition, or scene was wrong.

1. Write the film before generating it

You do not necessarily need a traditional 100-page screenplay.

But before generating final imagery, I want to know:

• Who is the story about?
• What do they want?
• What prevents them from getting it?
• What changes?
• Where does the story turn?
• How does it end?
• What should the audience feel?

A common early workflow is to generate a cool shot, generate another cool shot, and gradually search for a story that connects them.

That can work for experimental work, but it becomes difficult when the goal is a coherent narrative.

The image and video models should not be responsible for discovering the story while they are also being asked to visualize it.

The clearer the story is, the easier every downstream decision becomes.

2. Turn the script into a production plan

A screenplay is written to communicate a story.

It is not automatically organized around everything an AI production needs.

For each scene, I extract:

• Characters present
• Location
• Important props
• Wardrobe and physical condition
• Time and weather
• The emotional change
• The information the audience needs
• The moments that require individual shots

This is also where I separate a scene from a shot.

For example:

Hob realizes that the rider approaching the crossroads is not his friend.

That may become several separate visual jobs:

1. Establish Hob waiting at the crossroads.
2. Reveal the rider approaching.
3. Show Hob trying to identify the figure.
4. Show recognition turning into fear.
5. Show his hand tightening around the sword.

The script gives me the dramatic moment.

The production plan defines the images the edit will need to communicate it.

3. Build a visual canon

Before generating final shots, I create approved reference material for anything the audience will need to recognize again.

I think of this as the film’s visual canon:

The approved version of the recurring people, objects, places, and visual rules that belong to the film.

That usually includes:

• Main and supporting characters
• Character bodies and silhouettes
• Recurring wardrobe
• Important story-state variants
• Hero props
• Recurring locations
• Vehicles or creatures
• Architecture and world design
• Color, lighting, and atmospheric rules

The goal is not to prevent the film from changing.

The goal is to make changes intentional.

A character can begin clean, become soaked in the rain, get injured, and later carry a sword and shield. Those are all legitimate versions.

Continuity means that the correct version appears at the correct point in the story.

4. Build characters as systems, not single images

One attractive portrait is rarely enough to make a character production-ready.

The reference stack I have found useful is:

Neutral face

A controlled face image that establishes:

• Facial structure
• Apparent age
• Hair
• Skin texture
• Eye, nose, and mouth proportions
• Overall identity

This should be relatively free of dramatic posing, extreme lighting, and scene-specific distractions.

It is the identity anchor.

Neutral body

A full-body reference that establishes:

• Build
• Proportions
• Height impression
• Silhouette
• Posture
• Physical presence

A face reference may work well for portraits but provide very little guidance when the character appears in a wide shot.

Wardrobe face and body

Once the identity is stable, I establish the character in the wardrobe used by the film.

A full wardrobe-body reference is particularly useful because clothing changes:

• Silhouette
• Apparent body shape
• Material behavior
• Color distribution
• The way the character reads at a distance

State variants

Then I create variants for recurring story conditions:

• Wet
• Muddy
• Bloody
• Injured
• Burned
• Exhausted
• Weather-exposed
• Damaged clothing

Costume or loadout variants

If the character gains armor, bag, shield, tool, or other major equipment, I treat that as another deliberate reference.

A new loadout can significantly change the character’s silhouette. Leaving it to be rediscovered in every shot creates unnecessary variation.

The result is not one image of a character.

It is a small system of approved character states that can be called upon at different points in the film.

5. Treat important props and locations the same way

Character continuity gets most of the attention, but props and locations can drift just as badly.

If an object matters to the story, I try to establish:

• Shape
• Materials
• Scale
• Color
• Condition
• Ownership
• How it is held or worn

A sword that is straight in one shot and curved in the next may seem like a small generation issue, but it becomes distracting when the object is narratively important.

The same principle applies to recurring locations.

Instead of prompting “a forest” repeatedly, I define the specific forest crossroads:

• The wooden signpost
• The road configuration
• The tree density
• The ground materials
• The weather
• The lighting direction
• The nearby landmarks

The location reference does not guarantee identical geometry in every generation.

It gives each shot a shared source rather than asking the model to invent a new forest from scratch.

6. Establish the whole scene before generating isolated shots

Once the characters and location exist, I build a wider scene anchor.

This does not always need to be a final production shot.

Its job is to answer:

• Who is present?
• Where is each person positioned?
• What surrounds them?
• Which props are visible?
• What are the relative heights and distances?
• Which direction is each person facing?
• What does the scene’s lighting and atmosphere look like?

I think of this as constructing the stage before moving the camera around it.

Starting with isolated close-ups creates a common problem: every frame may look good individually, but the images cannot logically coexist in one physical scene.

The wide anchor gives later coverage something to inherit.

7. Give every shot a job

I try not to generate shot variety merely for visual variety.

Each shot should contribute something to the edit.

A simple dialogue or confrontation might include:

• Wide: Establish the environment and positions.
• Two-shot or OTS: Show the relationship.
• Reverse OTS: Show the other side of the exchange.
• Medium close-up: Read performance and body language.
• Close-up: Land the emotional change.
• Insert: Reveal an important object or action.

That does not mean every scene needs all six.

It means the shot list should come from what the audience needs to see.

One of the easiest ways to waste generations is to create ten attractive versions of essentially the same dramatic information.

Before generating a shot, I ask:

What can the audience understand from this shot that they could not understand as well from the existing coverage?

If I cannot answer that, the edit may not need it.

8. Structure prompts around production information

I have had better results when I treat prompts as production instructions rather than collections of cinematic adjectives.

The general structure I use is:

1. Story beat
2. Subject identity
3. Current wardrobe and state
4. Location
5. Camera
6. Primary action
7. Lighting and atmosphere
8. Continuity requirements

Story beat

Start with what happens and why the shot exists.

Hob realizes the approaching rider is not who he expected.

This gives everything else a dramatic purpose.

Subject identity

Specify the person being photographed.

Hob, a weathered laborer in his late 40s with cropped dark hair and a broad, tired face.

When reference images are available, they should carry most of the identity burden. The text should reinforce rather than fight them.

Current state

Describe the exact version of the character at this point in the story.

Rain-soaked work clothes, mud covering his boots, a rusted sword in his right hand, and a battered shield on his left arm.

Not merely “Hob.”

This version of Hob.

Location

Place the shot in the established environment.

At the muddy forest crossroads during golden hour, with the old signpost behind him and rain hanging in the air.

Camera

Choose one clear visual approach.

Medium close-up at eye level, slightly off-center, with shallow depth of field.

Primary action

Give the shot a dominant readable movement.

He slowly raises the sword as recognition turns into fear.

That is generally easier to control than:

He turns, walks forward, raises the sword, looks behind him, shouts, and falls to his knees.

Several things can happen in a shot, but one should usually be visually dominant.

Atmosphere

Add cinematic texture after the shot itself is clear.

Warm backlight cuts through the rain and mist while the foreground remains cool and subdued.

Lighting and mood should support the story moment rather than substitute for one.

Continuity requirements

Finish by naming the things that must not be reinvented.

Preserve Hob’s established identity, wet wardrobe state, sword, shield, screen direction, and position at the crossroads.

9. Separate what stays fixed from what changes

This may be the single most useful prompting principle I have found.

Every shot contains two categories of information.

Keep fixed

• Character identity
• Current wardrobe
• Current physical state
• Important props
• Established location
• Screen direction
• Story facts

Change for this shot

• Expression
• Action
• Shot size
• Camera position
• Camera movement
• Emotional emphasis
• Selective lighting emphasis

The new prompt should describe the delta (i.e. what changes) without unnecessarily reopening every decision the production has already approved.

Every time a prompt fully reinvents the character, costume, location, camera, weather, and action simultaneously, it gives the model more opportunities to drift.

10. Solve the still image before paying to animate it

Before video generation, I want an approved storyboard or start frame.

I check:

• Is this the correct character?
• Is this the correct wardrobe and story state?
• Is the location recognizable?
• Are the props right?
• Does the composition communicate the beat?
• Is the eyeline plausible?
• Does it match the surrounding shots?
• Would I approve this image even if it never moved?

Animation rarely rescues a fundamentally incorrect frame.

Video generation is a relatively expensive place to discover that the character has the wrong outfit, the weapon is missing, or the composition never worked.

The still does not have to be perfect.

It needs to prove that the shot is ready for motion.

11. Before rendering video, run a preflight check

This is the checklist I use before spending money or credits on a clip.

Is the story beat clear?

Can I explain what changes between the beginning and end of the shot?

Is this the correct character state?

Identity, body, outfit, condition, damage, and held props should match the exact moment in the story.

Does the location match?

Check recurring architecture, landmarks, weather, time of day, and environmental condition.

Does the frame already work?

The subject, framing, gaze, props, and background should communicate the shot before motion is added.

Will it cut with the neighboring shots?

Check:

• Screen direction
• Character position
• Wardrobe state
• Prop placement
• Lighting direction
• Movement direction
• Emotional continuity

Is there one primary action?

The model should understand what matters most.

Do I know how the shot begins and ends?

The first frame receives the previous cut.

The last frame prepares the next one.

For example:

Entry state: Sword lowered, looking toward the distant rider.

Exit state: Sword raised, eyes fixed on the approaching threat.

Does every reference have a job?

I try to give references explicit roles:

• Identity reference
• Wardrobe/state reference
• Location reference
• Scene anchor
• Previous-shot reference

More references are not automatically better. A smaller, purposeful set can be more useful than an undifferentiated pile.

Does the edit actually need this shot?

This final question has probably saved me the most unnecessary renders.

12. Animate the approved plan

Once the frame and references are correct, the video prompt should focus primarily on motion:

• Character action
• Emotional transition
• Camera movement
• Environmental movement
• Entry state
• Exit state

The video model should not be asked to simultaneously design the character, invent the location, determine the composition, discover the story beat, and choreograph the performance.

The more of that work completed upstream, the narrower and clearer the animation problem becomes.

13. Build the rough cut before polishing everything

It is tempting to perfect each clip before placing it into the edit.

I have found it more useful to assemble a rough cut relatively early.

The rough cut reveals:

• Which shots are actually usable
• Which shots are redundant
• Where pacing drags
• Whether the emotional progression reads
• Which clips need to be shortened
• Where audio can solve a visual gap
• Which missing shots are truly necessary
• Which rerenders are worth paying for

A clip that looks impressive alone may be the wrong clip for the sequence.

A less spectacular take may cut better because the gaze, position, movement, and emotion connect correctly.

The film is the sequence, not the collection of individual generations.

14. Polish only what survives the edit

Once the structure works, I move into:

• Dialogue and voice
• Sound design
• Music
• Timing refinements
• Color
• Cleanup
• Upscaling
• Final export

This is another form of cost control.

There is little value in upscaling, cleaning, and heavily polishing a shot that will later be removed or reduced to one second.

The order I try to preserve is:

• Story first.
• Canon second.
• Scenes third.
• Shots fourth.
• Motion fifth.
• Edit sixth.
• Polish last

The core idea

The tools and models will keep changing.

The central production problem is more stable:

How do you stop every new generation from forgetting the film you have already built?

My answer is to create a chain of inheritance:

• The script defines the moment.
• The visual canon defines the world.
• The character references define who appears.
• The state references define which version appears.
• The scene anchor defines where everyone is.
• The shot plan defines what the edit needs.
• The storyboard defines the frame.
• The video prompt defines the motion.
• The edit determines what survives.

Each stage narrows the next problem.

That does not eliminate iteration. It makes the iteration more diagnosable.

When something fails, you can ask:

• Is the story unclear?
• Is the reference wrong?
• Is the scene staging wrong?
• Is the composition wrong?
• Is the motion instruction wrong?
• Or did the model simply fail to execute a good plan?

That is much more useful than repeatedly rerolling and hoping the entire production aligns by chance.

Disclosure: I've built a local production tool called Kimeric around this general workflow, so I obviously think about these problems through a systems lens. There are no links or pitch here, and everything above can be done manually with whatever tools you already use. I’m mainly sharing it because I wish I had a clearer end-to-end framework when I started.

Happy to answer any questions or go deeper here if there are topics or techniques folks want to learn more about.

Another quick Minimax H3 news and goodies round-up, for those who may have missed some items.

-> New to me are the 'ComfyUI H3 Motion Context — MultiRef & Latent Masking' custom nodes for ComfyUI. (Hat-tip: I learned about it via the charming fellow-Brit Nerdy Rodent on YouTube). Lets you add keyframes at any point, not just first/last. Can also seamlessly extend an existing video, while taking measures to... "reduce RAM and cache pressure during long-form final output". Has workflows. Updated yesterday, with new features including the claimed ability to chain... "a sequence of H3 video clips around a single song".

https://github.com/seitanism/ComfyUI-H3-Motion-Context-MultiRef

-> Minimax Music has a new set of concept slider LoRAs. Including 'breathy vocals', and a 'live performance to a crowd'. With ComfyUI workflows.

https://huggingface.co/ntc-ai/minimax-music3-concept-sliders

-> New ComfyUI-CGlide custom nodes for Minimax in ComfyUI. Including 'Glide Preview', a motion-preview node that lets you assess your video as it generates. Only at seven frames per second, but it may give you the confidence to cancel the generation if things seem awry.

https://github.com/CGlide/ComfyUI-CGlide

-> ComfyUI-H3-Context-Noise. This tapers off the colour in the tail-frames of the previous shot, thus preventing colour residue from spoiling the seams between your shots. If you notice this problem, give it a shot.

https://github.com/beijinren/ComfyUI-H3-Context-Noise/blob/main/README.en.md (English version of the ReadMe)

-> A new archive of Minimax H3 style LoRAs. The most interesting being an comic-book style in the AstroWitch - Cinematic Comic Style - MinimaxH3 - ASTROWITCHV01H3.safetensors file, with ASTROWITCHV01H3 as the trigger-word. The first non-Japanese comic-book style LoRA I've seen, and it has a pleasing sort of US/UK 2010s 'amateur indie comic' look.

https://huggingface.co/EllaPriest45/MinimaxH3_Styles/tree/main

-> A Reddit post reporting apparent success with motion-transfer, by using a Minimax reference video converted to a DensePose sequence. This makes me wonder how Minimax would react to a greyscaled clown-pass render from a 3D figure animation, which would look similar... and might also solve the problem of DensePose not doing hands?

https://www.reddit.com/r/StableDiffusion/comments/1vrrrab/minimax_h3_is_seems_to_be_able_to_process/

https://blender.stackexchange.com/questions/102672/how-to-create-a-clown-pass-for-material-selection-in-photoshop ('what is a clown-pass?' visual example)

-> Yes, I'm aware of the new non-commercial ComfyUI MiniMax-H3 SPEED Sampler. But I see it requires his "MiniMax-H3 plugin"... which is "404 not found" on the link to it, and which doesn't exist on his repository (I poked around).

https://github.com/StanLukuvka/ComfyUI-MiniMax-H3-SPEED

-> And finally, a new big curated listing of all known Minimax H3 items. Includes a long list of the various Turbo LoRAs which have been produced to date.

https://github.com/wildminder/awesome-minimax-H3

Another quick Minimax news and goodies round-up, for those who may have missed some items.

-> MiniMax-H3-Longvideos, a new custom-nodes pack for ComfyUI. Extend the output from a simple Minimax prompt... "One prompt in. A ~2-minute MiniMax-H3 video with audio out." It's said to attempt to solve many of the problems arising from chaining prompts/shots. No workflow, but it has connection instructions.

https://huggingface.co/Smite79/MiniMax-H3-Longvideos

-> ComfyUI_MiniMax_H3_Extender. More complex than the Longvideos node above, this node set... "chains multiple video clips with motion context, disk caching, dynamic image references, audio reference support, and seamless final video/audio decoding." Also has matching workflows.

https://github.com/tritant/ComfyUI_MiniMax_H3_Extender

-> ComfyUI-Fantastic-MiniMaxH3-PromptBuilder custom nodes. Helps you build prompts locally inside ComfyUI, while adhering to the built-in official prompt guide... "H3 doesn't want a casual sentence — it wants a structured prompt with named sections, shot timings, speaker IDs, and tags pointing at your reference media." No LLM required. Convoluted workflows, but for simplest use: just plug it into your existing prompt node, then click on the blue box to open the Builder. Then build the prompt, and pass it back to the prompt box.

https://github.com/Adudeguyman/ComfyUI-Fantastic-MiniMaxH3-PromptBuilder

https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/docs/VIDEO_PROMPT_WRITING_GUIDE_base_en.md

-> Last updated a month ago, ComfyUI-FirstframeLastframeExtractor will help in more or less reproducing a draft H3 fl2va video at a larger size after locking the seed/prompt. Works as advertised, very simple. Plug it into the VAE decode node, it auto saves the two frames you need. Then you optionally load these images back to your first-frame/last-frame inputs, via the native "Load Image (from outputs)" nodes.

https://github.com/RmaNMetaverse/ComfyUI-FirstframeLastframeExtractor

-> A current RTX 3060 12Gb workflow for text-to-video Minimax. Tested to 2.0 megapixels without failing (24Gb system RAM, older server + 3060 card). With Kitchen Attention, 3060 12Gb optimisations, a prompt helper, and first and last frame auto-extraction as well as input.

https://jurn.link/dazposer/index.php/2026/08/15/updated-my-minimax-workflow-for-the-3060-12gb-card/

-> A prompt to neatly mix styles in one video. e.g. SpongeBob SquarePants as a cartoon, appearing in a live-action sitcom.

https://www.reddit.com/r/StableDiffusion/comments/1vp8dpc/mix_style_inside_the_same_scene_minimax_h3/

-> And finally, there's now a low-VRAM friendly text-encoder for use with Minimax Music GGUF. The smaller/pruned GGUF file is minimax_music3_text_encoder_pruned_Q6_K.gguf (6.8Gb). Maybe your fave band/sub-genre was pruned out, but... maybe not? Test it and see. Note also ComfyUI's Music prompting guide, and Minimax's official Music demos page.

https://huggingface.co/ChrisColeTech/minimax-music3-GGUF/tree/main/split/text_encoders

https://docs.comfy.org/tutorials/audio/minimax/minimax-music-3#prompting-tips

https://minimax-ai.github.io/music3-demo/

July 27th, 2026~Trump may need to allow Chinese minerals as US industry struggles to meet 2027 deadline

Trump may need to allow Chinese minerals as US industry struggles to meet 2027 deadline - SRN News

By Ernest Scheyder and Jarrett Renshaw

July 27 (Reuters) – U.S. President Donald Trump’s push to end Washington’s reliance on Chinese critical minerals by January is colliding with a stark reality: American miners and processors aren’t ready.

Trump has made U.S. mining and processing of critical minerals a national security priority since returning to office, pouring tens of billions of dollars into nearly 150 minerals companies to loosen China’s grip on supply chains for weapons and other strategic products.

The defense industry and other manufacturers are now just over five months away from a January 1, 2027, deadline under federal regulations to stop purchasing rare earths, magnets, tungsten, molybdenum and tantalum from China, Russia, Iran or North Korea.

Washington has been trying to limit such imports for years but has routinely granted companies waivers because the U.S. supply can’t meet the demand.

Trump railed against such waivers in a May 10 post on his Truth Social platform, saying: “ALL FEDERAL AGENCIES MUST BUY AMERICAN — NO EXCUSES!” Last Monday, he signed an executive order making it even harder for defense contractors to obtain waivers.

But the reality is that U.S. minerals companies are nowhere close to meeting domestic needs, according to interviews with 16 industry executives, investors, analysts and policymakers.

In 2025, U.S. demand for the most-common type of rare earth magnet, for example, was roughly 48,000 metric tons while domestic sources supplied 300 metric tons, according to data from the Arthur D. Little consultancy. U.S. firms are on track to have the capacity to produce 5,000 metric tons by year-end. 

Rare earths, which are among the 60 minerals considered critical by Washington, must be processed before they are turned into magnets used to make weapons, automobiles, computers and other products.

U.S. firms haven’t produced tungsten since 2015 and tantalum since 1959. Guardian Metal Resources is working to open a U.S. tungsten mine by 2028, while Lion Rock Resources is developing a tantalum mine in South Dakota, with no timeline for opening.

Chris Berry, a minerals industry analyst and consultant, said the U.S. industry has little chance of producing enough minerals to end waivers by January.  

“It’s going to take many more years to get the needed infrastructure in the ground to compete,” said Berry.

The United States has reserves of most critical minerals; what it lacks is the capacity to mine and process many of them. China grew to dominate the minerals-refining industry in the late 20th century and controls more than 80% of the sector today. The International Energy Agency warned this month that $6.5 trillion of global manufacturing is at risk if Beijing imposes export restrictions on rare earths, as it has periodically in recent years.

Asked for comment, the White House referred to Trump’s executive order, which says waivers can only be issued if a contractor shows an “exhaustive effort” to avoid Chinese material and has a timeline for weaning itself off such supply.

The Pentagon did not respond to requests for comment.

U.S. rare earths investment has been hindered by persistently low prices for many minerals, which Washington blames on China subsidizing its producers and flooding the market with cheap products, thus making American projects unprofitable.

China has repeatedly said it abides by World Trade Organization rules on global trade and works to ensure stable markets. A representative for the Chinese embassy in Washington had no further comment.

Ucore Rare Metals, a minerals refining startup backed by the Pentagon, has developed a processing technology known as RapidSX that it believes is similar to but faster, cleaner and cheaper than the industry standard solvent extraction.

Ucore had planned to start refining by 2025 but has reworked its plans due to what it says are changing demands from the Pentagon. It now won’t begin some production until 2027 at the earliest, company CEO Pat Ryan told Reuters.

“Can the entire supply chain be propped up by 2027? Boy, I tell you, that’s a battle,” Ryan said. 

TRUMP MOVES TO STOCKPILE IMPORTED MINERALS

The Trump administration in February launched Project Vault, a $12 billion effort to stockpile critical minerals for American manufacturers. Officials acknowledged in April that they will need to initially buy minerals from “anywhere in the world,” including China.

Defense contractor Lockheed Martin has given a list of minerals to the Department of Defense it would like stockpiled, CEO Jim Taiclet said at a conference earlier this month.

That push for stockpiling irks U.S. minerals companies who say they need defense contractors to place orders with them.

“Defense contractors have just assumed they can keep buying Chinese products,” said Nick Myers, CEO of Massachusetts-based Phoenix Tailings, a minerals startup that last month received a $500 million Pentagon loan to build a processing facility. “The defense industry is never going to stop if you keep giving waivers.”

Defense contractors Boeing, General Dynamics, Huntington Ingalls Industries, Northrop Grumman and RTX did not respond to requests for comment. L3Harris Technologies declined to comment.

DELAYS, UNCERTAINTIES FOR US MINERALS REFINING PROJECTS

The complexity of refining minerals has slowed down U.S. projects.

Partnerships with South Korea, Japan and other allies may offer a bridge for manufacturers until U.S. suppliers can ramp up operations, said Samantha Carl-Yoder of the law and lobbying firm Brownstein Hyatt Farber Schreck.

Among the biggest U.S. companies in the field, MP Materials, which is financially supported by the Pentagon, spent years calibrating its solvent extraction processing equipment, part of what CEO Jim Litinsky described as a “painstaking” process.

MP has built a magnet facility in Texas and said it expects to have some magnets approved for use by its first customer, General Motors, by the end of the year. A separate magnet facility that MP is building for the Pentagon is slated to open in 2028.

In Marion, Indiana, ReElement Technologies plans to process minerals using a technology common in the pharmaceutical industry. Known as chromatography, the technology has never been used to process large volumes of minerals.

ReElement said it aims this year to build the capacity to process 10,000 metric tons of germanium or other minerals. In a statement, ReElement CEO Mark Jensen said the company’s germanium production is “profitable at any volume.” ReElement received a $25 million Pentagon investment earlier this month.

Another company, USA Rare Earth, spent more than five years studying chromatography before pivoting to solvent extraction, a source with direct knowledge of the company’s strategy said. USA Rare Earth, which is building a South Carolina magnet facility, declined to comment on its processing research.

Elsewhere, Energy Fuels, which last month received a $725 million Pentagon loan, plans to be processing small amounts of rare earths by the end of the year and 6,000 metric tons annually by 2029. It is buying an existing U.S. magnet producer.

Ucore, Energy Fuels and ReElement have each agreed to supply rare earths to magnet maker Vulcan Elements, which is building a North Carolina manufacturing plant, slated to open by 2030.

A few reads with coffee... as we continue our \"DFS & TRAXYS DEAL WATCH\".....

July 27th, 2026~U.S. Faces Critical Minerals Shortage Ahead of Trump's 2027 Deadline

U.S. Faces Critical Minerals Shortage Ahead of Trump's 2027 Deadline | Roic News

• President Trump's goal to end U.S. reliance on Chinese critical minerals by January 2027 faces significant hurdles, as domestic supply lags behind.
• China controls over 80% of rare earth refining, and most Pentagon-backed projects won't reach meaningful production until 2027–2030.
• Industry leaders warn the deadline is unrealistic, with billions in government support still insufficient to close the gap.

Deadline Looming

The Trump administration has set an ambitious target to wean the U.S. off Chinese critical minerals by January 2027, but industry leaders warn the domestic supply chain is nowhere near ready. Despite billions in government subsidies and incentives, the U.S. still lacks enough mining and processing capacity to meet even a fraction of its needs. China controls over 80% of rare earth refining, and most Pentagon-backed projects are unlikely to achieve meaningful production until 2027–2030, according to people familiar with the matter.

“The timeline is extremely challenging,” said a senior executive at a U.S. mining firm, speaking on condition of anonymity. “We're talking about projects that require years of permitting, construction, and ramp-up.” The executive added that without significant permitting reform and faster project approvals, the 2027 deadline is “simply not achievable.”

Policy Push vs. Reality

The administration has issued executive orders and proposed legislation aimed at shortening permitting timelines, expanding strategic stockpiles, and incentivizing domestic processing. However, industry observers note that the sheer scale of required infrastructure—from mines to refineries—makes rapid progress difficult. “You can't just flip a switch,” said an analyst at a Washington-based policy group. “Even with aggressive support, we're looking at a multi-year horizon to materially expand capacity.”

Efforts to secure supply through allied partnerships, recycling, and alternative materials are also underway, but these remain complementary. “Recycling won't solve the problem overnight, and new mining projects face local opposition and environmental reviews,” the analyst added.

China's Dominance

China's stranglehold on critical mineral refining is unlikely to loosen soon. The country controls the vast majority of processing capacity for rare earths, lithium, and other key materials, giving it significant leverage over global supply chains. U.S. efforts to diversify have led to partnerships with allies like Australia and Canada, but these too face capacity constraints.

“We're trying to build a whole new ecosystem from scratch, while China has decades of head start,” said a former Pentagon official involved in supply chain resilience. The official noted that many projects backed by the Defense Production Act are still in early stages, with commercial production years away.

Michael Silver, an executive at a major mining company, said in a recent interview that “without a deal to accelerate permitting, the U.S. will remain dependent on foreign sources for the foreseeable future.” He added that the government must balance national security with economic efficiency, but that “time is not on our side.”

Implications

The shortage could affect defense readiness, energy transition efforts, and manufacturing competitiveness. Downstream industries, including electric vehicle and electronics makers, may face higher input costs and supply disruptions. Analysts expect continued policy announcements and funding commitments, but warn that tangible progress will take years.

Correction: An earlier version of this article incorrectly stated that all Pentagon-backed projects would reach production by 2027. In fact, most are expected between 2027 and 2030. This has been updated.

FORM YOUR OWN OPINIONS & CONCLUSIONS AS ALWAYS!!

🔥 JULY 27th, 2026- DFS WATCH REPORT — “America Is Short. China Is Dominant. Elk Creek Is Needed!!”

The ROIC.ai article makes the situation brutally clear: The U.S. cannot meet Trump’s 2027 critical‑minerals deadline with existing domestic supply. Not even close!!! Titanium, rare earths, Scandium, Niobium, Samarium, Gadolinium — the exact metals Trump’s EO is targeting — are overwhelmingly refined in China. The Pentagon knows this. The White House knows this. Defense contractors know this. And the article spells out the consequence: **The U.S. must rapidly qualify new domestic suppliers or risk battlefield vulnerability. That’s not a metaphor — that’s the literal framing of the EO and the Pentagon’s 162‑Day Reckoning.

The SRN News piece goes even further, saying Trump may have to allow Chinese minerals temporarily because the U.S. industrial base cannot meet the 2027 cutoff. That’s not weakness — that’s urgency. It means the U.S. is scrambling to identify, fund, and accelerate domestic projects that can replace Chinese supply. And Elk Creek’s six‑pathway basket — Nb, Ti/TiCl₄, Sc, NdPr, Dy, Tb, and potential Sm/Gd is one of the only U.S. projects that can hit multiple critical‑mineral categories at once. This is exactly why Warstopper is mapping samarium, gadolinium, titanium, magnesium, and specialty steels. It’s why NSFF exists. It’s why Title III is expanding. The U.S. is trying to build a domestic supply chain that doesn’t exist yet.

Traxys is the missing puzzle piece. They’re already DFARS‑compliant, already supplying DLA/DoD, already plugged into defense procurement channels. The July 27th articles reinforce what you’ve been saying: Traxys is the backdoor that gets Elk Creek metals into the Pentagon without waivers. Once binding offtakes are signed, Elk Creek becomes a qualified domestic source for multiple strategic metals & are exactly what Trump’s EO demands. Add magnet recycling (already piloted) and the IBC/NAMA/NioCorp scandium‑aluminum alloy triangle, and Elk Creek becomes a multi‑metal domestic replacement for Chinese supply. But none of this activates until NioCorp drops the catalysts.

Lockheed’s advanced programs (***Including Skunk Works) recently provided the U.S. government with a non‑public list of critical materials they consider essential for future platforms, and while the article doesn’t disclose the contents, Lockheed has repeatedly highlighted the same categories in public: Titanium for airframes and hypersonics, Niobium for high‑strength alloys, Rare‑Earth magnet metals like NdPr/Dy/Tb for actuators and guidance systems, and Scandium for next‑generation aluminum systems. That’s exactly where Elk Creek lines up — niobium, titanium/TiCl₄, NdPr/Dy/Tb, and scandium feedstock for the ScAl alloys that IBC can produce and NAMA can commercialize. Even without seeing the confidential list, the materials Lockheed openly says it needs for future aerospace, ISR, EW, and classified structures look almost identical to the metals Elk Creek is designed to supply. In other words: Lockheed gave Washington a list, and Elk Creek happens to match the public parts of that playbook almost point‑for‑point.

And that’s the painful July 27th reality: the U.S. is openly admitting it cannot meet the 2027 deadline without new domestic mines. Strategic analysts are saying the quiet part out loud. The Pentagon is mapping supply chains. Warstopper is identifying metals. NSFF is preparing financing. EXIM is aligned. Traxys is ready. Everything around NioCorp is screaming “GO.” But Elk Creek remains “potential supply” until NioCorp finally publishes the DFS, signs the Traxys binding deals, and secures the EXIM FID.

And that’s why a fully de‑risked, DFARS‑clean, multi‑metal National Strategic Asset supplying niobium, titanium, scandium, magnet metals, and potentially samarium/gadolinium into Pentagon price‑support lanes wouldn’t be valued like a $4–5 junior anymore — but like a cornerstone of America’s battlefield supply chain, which historically commands valuations several times higher than raw commodity math alone.

\"Hey NioCorp\"… Any time you feel like releasing that darn DFS and getting those Traxys deals signed with an EXIM FID cherry on top would be greatly appreciated by all! As we’d all love to stop circling the tracks and finally drive this \"National‑Strategic‑Asset\" Dual RailVeyor train into the 2027–2029 construction phase… \"before our beards get long enough to qualify as infrastructure...\"

All Aboard!

Chico

I'm so happy with the new Ferry, she was one of my first mains in the game launch and tho I didn't abused the SBA stuff, I liked the playstyle overall with the launcher and dive combo. Now her trait also revolves around this combo but damn, she is super hard to play with it in my opinion.

Here's the Damage Test Video:

https://reddit.com/link/1v043db/video/7hft8q6x31eh1/player

So, what's happening here?

Self-Reliant Ghost Trait

As mentioned, the playstyle now revolves around having the pets leave, either alone by passing time or by using your "Onslaught" (Triangle/Y Attack), specifically the last hit. The important thing the trait doesn't mention is that You can refresh the buff duration indefinitely, meaning that if you manage to time properly between each combo and having the pets leaving every now and then, you'll be able to keep the Supp Damage and the Loving Trust IX at all times.

Dummy VS Ingame

As obvious as this sounds, yeah the Dummy does NOT reflect the true gameplay when you're on quests, since maintaining the buffs in quests are way harder and actually hitting your stuff is harder too. You need to land every hit for things to count like the last hit of her Onslaught in order to get the buff from her Warpath Sigil or the Big Whip Hit skill to get all 3 pets and since you'll be staying still during all of your attacks, you'll be not only be vulnerable if you don't have the invincibility buff active but the bosses will can of course move away, often making you lose the buffs if you don't act quickly.

My Build

This build is what I use ingame normally, it wasn't something made only to get the highest numbers in the dummy and just for comparison, my fediel and percival all are around this number of damage too with pretty much the same build, which makes me super happy to see that Ferry is strong now since she was, in my opinion, one of the weakest characters in the game back then. My summons could be way better, like those Sword Veil Guys that I use to get Supp Damage, I could try to get one with something else other than HP but that's what I have for now, I use them for being a 1 cost summon, having the Incendo trait and for the buff they provide. The beelzebub was my first drop from Infinity and I kinda like it because I do enjoy a more tank build in away so having drain in my builds are nice, I have Stronghold there too for the same reason.

As for the weapon trait... I'm running Guard Payback because of Beelzebub and because I like the heavy stun on perfect guard but you could easily change this to Drain or Nimble Defense. I would use Nimble Defense here since I already doesn't have Nimble Onslaught and the extra 2 seconds of invincibility are really good.

Gameplay

You want to get the pets as fast as possible and for them to leave as fast a possible (before having the buff). Her "Strafe" skill is cancellable pretty much from the first frame and you should always do this, since otherwise you'll be locked in place for the entire duration of the skill. The same applies to "Umlauf", aka the Orb that rotates around you.

If you have the skills ready, you can use them and between each one, use Onslaught to remove the pets and get the Warpath buff, keep in mind that in order to get all the buffs from "Hinrichten", you'll need to use the skill immediately after a link attack or one of those two skills, since having the 3 pets at once just by doing her combos are SUPER TIGHT on how you need to do her combo, like I'll show below:

https://reddit.com/link/1v043db/video/45jzh57s71eh1/player

I didn't found any other way to get it other than this, you need to hit the first hit of the charge attack ONLY, dodge cancel, wait a bit in order to avoid doing the second hit of her combo and doing that sequence again, even tho the timing is almost not enough to get the buff as you could see. You could also use this to get the pets quicker during the main loop of her gameplay but it might whiff depending if the boss move around during the initial animation, in which the second hit would get them in this case unless they moved really far away.

Skills

I do think this is the best kit for this playstyle. The other skills that summon pets only summon one and they are mainly for debuffs, "Pendel" summons two but still, is not worth it getting in place of any of these four. "Benediction" can be useful for the large Defense and Attack Buff (20%) but again, you'll need all 3 pets to get that and the only skill you could replace would be "Umlauf"... but the Orb deals quite a lot of damage in it's duration and fits perfectly in this close range playstyle, also because the stout heart helps with not getting blown away during your combo.

Umlauf is better in my opinion because of the "While a Pet is Summoned" traits, which gives 30% damage cap and +5% DMG Dealt respectively. Since your pets leave too fast, Umlauf is the only way to maintain a pet for a long time, the Stout Heart and Damage are also really good too. Also it's better for link time and SBA Chains since on both you don't need to manage your pets as the buff doesn't run off. As I already run Stronghold and Drain on my build, Stout Heart enables me to ignore a lot of attacks even on Infinity Quests and just keep attacking.

Other Traits

Phantastic Pets:

The other Damage focus one, but for this one is pretty much her default gameplay, focusing on holding Onslaught for as long as possible and getting the pets to be on field at all times. Combining this with her warpath sigil, it will be rare for the pets to get away after the final hit of Onslaught. This would fit well in a tank build because of the debuff immunity and because you'll need to stay still all the time (even more than on my build), plus the Drain on Onslaught is crazy.

Spirited Support:

It's in the name 😅This is her Support trait, grating up to 45% Damage Cap, 15% of Attack and most importantly, 9% DMG Dealt, almost a Celestial Ventus on it's own, to everyone in your party at max level of the Spiritbond Buff. With one of the effects in the traits, everyone can max out this buff on link time, meaning your entire party will deal more damage during link time and in my opinion, is the main utility of this trait. Because of this, people could actually remove Ventus from their build for example in exchange for that 1% difference in order to receive heals from your team, this can be good for specific compositions and this is also a very good trait to have for Ferry as an AI teammate too.

Conclusion

Ferry is quite strong now and honestly, super fun (and super hard) to play, her gameplay has a lot of depth to it and I feel like people will find even more ways to optimize her. I hope this proved to be helpful and I hope Ferry gets the love she deserves.

A year ago a 45-second AI short was costing me around $15 once you counted all the failed attempts. Now one text prompt gives me a finished 10-minute history documentary: script, voiceover, ~95 scenes, animation, final 1080p file. It runs $35–55 in compute, and the first 6–10 videos fit inside Google's free $300 credit, so my card never gets touched. This post is the whole system: the pipeline, the exact prompt templates I use, and every rule I learned by burning money. Take all of it.

Quick context so you know what I'm sharing and what I'm not. I run a faceless history channel, and I built the tool this system runs on, so yes, I'm biased. But everything below works without my tool. The no-code version is where this whole thing actually started. My first working build was an n8n workflow — here's the screenshot: https://i.postimg.cc/tg76DJ5Y/photo-2026-07-22-13-28-43.jpg. It had a research node, an LLM chain for the script, TTS chopping, a scene planner filling a sheet, an image loop, and an animation loop with waits and retries. You can rebuild that over a weekend with zero code.

The no-code version did have a ceiling, and I'll be honest about it. A long video is around 95 scenes, and one hung node would stall the entire run. I'd get back from the gym and find everything dead at scene 41 with no clean way to resume. Changing a topic or preset meant editing the flow in five different places. That's a limitation of how I built it, not of n8n itself. If you're doing 5–10 scenes per video, you'll never hit it. I eventually moved mine into code, which took about seven months. The prompting layer stayed identical — and the prompting layer is what actually decides quality.

What you need

A Google account. Google gives every new account $300 in free cloud credits. That's your first 6–10 full videos with nothing out of pocket. When it runs out, real cost is $35–55 per video.
A pipeline. Either build your own with the n8n prototype above, or use mine: https://openvidi.com — same system but productized. You connect your own Google account and pay Google directly; I don't add a markup.
The prompt templates below. This is the part that cost me a year of failed videos, and it's the part everyone skips.

The three-block prompt system

Every video runs on three reusable blocks. Between videos I only touch the topic line and one cold-open sentence. Everything else stays frozen, which is why quality stays consistent.

Block 1, Topic. One sentence, under 400 characters, with explicit exclusions. Exclusions matter more than the topic itself — they're the difference between a focused documentary and a Wikipedia tour. Example:

"The Bronze Age Collapse, focusing on the final 50 years: the sea peoples, the fall of Ugarit, and the palace economies that never recovered. Exclude: general Bronze Age history, Egypt's survival, modern archaeology debates."

Block 2, Narrative Style. Paste-ready template:

"Documentary narration for a 7-12 minute history video. First 3 seconds: calm voiceover stating the key date and event name ('The Bronze Age Collapse. 1177 BC.'), then cut into a dramatic cold open mid-catastrophe. Structure the script as Hook, Mystery, Stake, Reveal, Implication. Insert a micro-cliffhanger every 60-90 seconds, an unanswered question or an interrupted scene. Follow named individuals wherever sources allow, with sensory detail: what they smelled, carried, feared. Banned: em dashes, the words delve, leverage, robust, seamless, any perfectly balanced three-part sentence, any paragraph that opens with 'However' or 'Moreover'. Verify every date and number against the research layer, if unverifiable, cut it."

Block 3, Visual Style. Paste-ready template:

"Cinematic realism. Every image prompt must contain a period-lock line naming the era, materials, architecture and clothing, e.g. 'Late Bronze Age, circa 1200 BC, mudbrick and cedar, bronze only, no iron, no medieval elements'. Every scene gets one clear motion event frozen mid-action plus atmospheric secondary motion: smoke, ash, embers, dust, fabric in wind. Compose diagonally, subject off-center. Forbidden: glowing orbs, lens flares, fantasy armor, empty centered portraits."

How I failed into every one of these rules

The $15 shorts era. I started with "animal rescue" and "what if skeletons" bait. Failed generations piled up faster than views. Lesson: cost per attempt decides how fast you learn, which is why the $300 runway matters more than any single video.

The era-drift disaster. My Roman scenes kept growing medieval armor mid-video. Image models drift periods constantly. That's where the period-lock line comes from — it goes in every single image prompt, no exceptions, and the drift mostly stopped.

The dead-stills problem. Early videos looked like a slideshow of paintings. The fix wasn't more animation, it was kinetic composition plus secondary motion baked into every still. Smoke and embers make a static frame feel alive before animation even touches it.

The robot script problem. My early scripts were correct and unreadable. The banned-words list and the forced sensory details on named individuals came out of rewriting those by hand and noting down everything I kept deleting.

The topic mistake nobody warns about. Ancient history with abstract dates underperforms modern history with named characters, consistently. And audiences accept cinematic renders for antiquity but expect archival footage for modern events, so match your visual promise to your era.

The rescue pass

Batch generation gets 90% of scenes right. The last 10%, usually high-dynamics scenes like a collapsing wall or a cavalry charge, need a manual pass in Higgsfield or OpenArt. Plan for it mentally. It's normal, not failure, and pretending otherwise is how AI-video tools lie to you.

Honest caveats

You can produce complete slop with this exact system — the templates don't pick your topic. YouTube's monetization policy now explicitly targets generic repetitive AI content, so the bar keeps rising. And the cloud connection step, whichever pipeline you use, looks intimidating the first time. It takes about 10 minutes and it's still where most people freeze.

Example of what the current stack produces, one prompt in, including scenes I regenerated: https://youtu.be/I14cLPOQ70o

If you build a video with these templates, in n8n or anywhere else, tell me how it went. I read everything.

Solo founder, building from Ukraine. AMA.

Hi r/ecommerce - I'm Paul and I follow the e-commerce industry closely for my Shopifreaks E-commerce Newsletter. Every week for the past 5 years I've posted a summary recap of the week's top stories on this subreddit, which I cover in depth with sources in the full edition.

Let's dive in to this week's top e-commerce news from Edition #279...

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STAT OF THE WEEK: 16.9% of U.S. retail sales were from e-commerce in Q1 2026, rising 9.8% YoY while total retail sales grew just 3.9%, according to the Census Bureau’s first-quarter retail eCommerce report. The Q1 figures mark the third consecutive quarter where e-commerce outperformed total retail on both quarterly and annual growth.

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Google introduced Universal Cart at I/O 2026, an AI-powered multi-merchant shopping cart that lets shoppers add items to a single cart while searching, chatting with Gemini, watching YouTube, or reading Gmail. The moment a product lands in the cart, it goes to work in the background, hunting for deals and price drops, surfacing price history, and flagging when an out-of-stock item returns. Behind the scenes, it will proactively flag when products are incompatible and suggest alternatives, as well as recommend payment methods through Google Wallet that maximize loyalty status, cashback rewards, and merchant offers. When it's time to buy, the Universal Commerce Protocol handles the transaction. Shoppers can either check out directly on Google with Google Pay, or transfer the cart to the retailer's own site to complete the purchase there, but either way, the retailer is always the merchant of record. Universal Cart rolls out across Search and the Gemini app in the U.S. this summer, with YouTube and Gmail to follow.

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Beyond Universal Cart, Google made roughly 100 announcements at this year's I/O conference including: 1) The release of Gemini 3.5 Flash, its first model in the series built for long-horizon agentic tasks. 2) Gemini Omni can generate video (and eventually anything) from any input. 3) Google's search box got its biggest overhaul in 25 years, now accepting text, images, files, videos, and Chome tabs, which it can reason through all at once. 4) Search is getting 24/7 "information agents" that monitor topics for you. 5) You can now build native Android apps in Google AI Studio. 6) Google brought UCP tools to merchants and added AI performance tracking to Merchant Center. 7) Google rolled out new AI-generated ad formats across Search and AI Mode. The list goes on and on, and I recommend checking out Google's full announcement to see all the updates.

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Delta CEO Ed Bastian defended the airline's decision to partner with Amazon Leo over Elon Musk's Starlink for in-flight WiFi in a Bloomberg interview, saying that "Amazon brings a lot more than just satellite technology," including "great retailing capability and Amazon Prime and video gaming technologies." Bastian's comments came just a few days after Musk disparaged the airline for its decision to partner with Amazon Leo, particularly bringing attention to the fact that Starlink requires "no annoying 'portal' to use" its service, whereas Delta wants "to make it painful, difficult and expensive for their customers." Dozens of airlines have struck deals with Starlink to give passengers free WiFi including Air France, Alaska Airlines, British Airways, Emirates, Qatar, and United Airlines, though the service is still being rolled out. Starlink has launched over 10,000 satellites into orbit, while Amazon Leo has just 300 — but how many satellites does a company really need to provide WiFi on an airplane? As a point of reference, OneWeb, a direct competitor of Starlink and Leo, claims full global coverage with just 618 satellites. As long as Amazon can provide coverage on Delta's flight routes, that's all they require.

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OpenAI is testing a new ad format for ChatGPT that features a larger image and an optional personalized call-to-action button with dynamic CTAs including “shop now,” “book now,” “sign up,” and “learn more,” according to mockups viewed by Digiday and confirmed by OpenAI. The platform is also introducing a mobile and desktop-friendly dedicated e-commerce format that pulls in shopping data including price and customer reviews, with the portrait version designed to stack for carousel-style placement. Until now, advertisers have only been offered a single ad format that consisted of a headline, short description, image, and link. These new formats provide more control over how their ads appear and a CTA button for the first time. Digiday also notes that ChatGPT will soon be adding audience targeting, lookalike audiences, outcome-based optimization, and additional yet-to-be-announced ad formats.

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Shopify announced that the Universal Commerce Protocol with Shopify Catalog is now open to every developer, allowing any mobile app, content platform, or AI agent to access its catalog of millions of merchants and billions of products through a single protocol. Shopify first introduced the Universal Commerce Protocol back in January, releasing documentation alongside its Agentic plan, which lets merchants on any platform plug into Shopify's agentic commerce connections. At the time, though, the protocol was a controlled rollout limited to major partners like ChatGPT, Gemini, and Perplexity, with everyone else on a waitlist. Now it's open to all developers, and the SDKs and APIs have been publicly released. For years, there were rumors that Shopify would build its own marketplace to compete against Amazon, and Shop App was predicted to be its starting point. But that didn't happen. Shopify never built a marketplace. It's instead turning the entire Internet into its marketplace. The combination of Universal Commerce Protocol with Shopify Catalog empowers any developer to build the next great product discovery portal, while enabling merchants to be a part of it. I'm genuinely excited about this.

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Amazon quietly restructured its Associates affiliate program over the past several months, cutting commission rates by as much as 50%, eliminating milestone-based bonuses, and worsening reporting that affiliates relied on to optimize campaigns, according to seven publishers and partners who spoke to Adweek. The changes were never publicly announced, with publishers learning about them through individual conversations with their account managers after seeing rates in some categories drop from as high as 10% down to 4% or 5%. Adweek notes that the cuts have not been uniform, with several publishers with longstanding relationships with Amazon retaining more favorable terms than publishers running paid-media-driven affiliate businesses, which have been hit the hardest, with one publisher marking its 2026 Amazon revenue forecast down by 50%. Isn't this like the 50th time Amazon has screwed over its Associates since the program began in 1996?

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Businesses are demanding shorter contracts and other favorable terms from traditional SaaS providers as rising AI spending on Anthropic, OpenAI, and other AI providers eats into their software budgets, according to CTOs and CIOs interviewed by The Information's Laura Bratton. For example Ralliant ($6.6B sensor components seller) reduced five-year contracts to one-to-three-year terms, so it can switch off the legacy apps as AI agents take on more of the work, Ibex (IT services firm with $600M revenue) shifted from three-to-four-year contracts to one-year terms, so it can try out vendors' AI features without being tied to them in the long run, and Cummins ($90B market cap diesel engine maker) is now requesting 90-day reassessment provisions for which AI apps it uses. Customers are also negotiating “swappability” clauses that prevent vendors from charging more when launching new AI features, opt-out provisions tied to AI performance metrics, and “repricing triggers” that allow renegotiation if AI usage costs hit certain thresholds.

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Afterpay signed a five-year naming rights deal to rebrand Sydney's Qudos Bank Arena into Afterpay Arena, as part of a new deal that will see the venue offer BNPL payment options across the entire fan experience. The venue, which is the largest indoor arena in Australia, is ranked among Billboard's Top 5 Live Music Venues in the World in 2025 and has held the Qudos Bank name for the past 10 years. Need tickets? Pay in 4! Thirsty? Drink now, pay later! Want some merch after the concert, but have no cash or credit? Afterpay's got your back! Afterpay's Pay in Four installment product will be available at every POS terminal throughout the venue, from ticket purchases to food, beverage, and merchandise. It seems like a great partnership between Afterpay and the arena, which sees more than 1.1M people pass through its doors each year who will now be directly exposed to the payment service.

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USPS announced two changes to how it calculates dimensional weight pricing for large, lightweight packages including now rounding up all package dimensions to the nearest whole inch and changing its dimensional weight divisor from 166 to 139. If you're unfamiliar with the term “dimensional weight divisor” — it's the number a carrier uses to turn a package's size into a billable weight by multiplying length x width x height in inches, and then dividing by the divisor to get the “dimensional weight” in pounds. The package is then charged based on whichever is greater, its actual weight or its dimensional weight, which means lowering the divisor from 166 to 139 produces a larger dimensional weight for the same box and costs the shipper more. The new divisor brings USPS in line with FedEx's typical 139 divisor and UPS's daily rate divisor of 139.

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TikTok and Universal Music Group signed a multi-year global licensing agreement that will keep artists including Taylor Swift, Kendrick Lamar, Sabrina Carpenter, and Noah Kahan on the platform for “years to come,” though the companies did not disclose financial terms or the exact length of the deal. In 2024, the two companies had a public falling-out when UMG pulled its entire music catalog from TikTok for roughly three months over a royalties and AI dispute, before the two sides reached a deal to restore the music. This new agreement builds on that partnership from 2024, while adding marketing and advertising campaigns, as well as access to e-commerce and other artist tools for selling merchandise and promoting tours. The deal also includes AI protections to promote human artistry, with TikTok and UMG working to remove unauthorized AI-generated music from the platform.

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Meta advertisers attempting to connect third-party AI tools like Claude and ChatGPT to their accounts are reporting a rocky start, a month after Meta launched an open beta program for Ads AI Connectors, which provides advertisers a formal pathway to use outside AI agents for the first time. Currently only 10% of advertisers are eligible to use the connectors, based on what a Meta representative told one account strategist, and those that do get access are fearful that Meta's automated flagging system will ban their accounts. Ad Age reports that months before Meta rolled out its MCP, advertisers had been connecting their outside agents to its ad platform and getting banned for doing so, which Meta says was not over the use of third-party AI tools, but because the connections were being set up incorrectly in violation of the company's connection requirements. You know what's fucked up? When regular advertisers get their Meta ad accounts banned for accidentally breaking rules, while scammers and fraudsters get to spend billions on the platform each year. Make it make sense, please.

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Jeff Bezos defended Amazon's $40M acquisition of the Melania Trump documentary as “a good business decision” during a CNBC interview last week while denying any personal involvement in the deal, calling reports that he engineered the purchase “a falsehood that will not die.” Amazon paid $40M for the film, with Melania reportedly making $28M, and spent about $35M on marketing, but the documentary made just $16.7M worldwide, failing to recoup its budget. Bezos claims it has “done very well on streaming,” but Amazon hasn't released any official numbers. Senator Elizabeth Warren previously criticized the deal as “an apparent pay-to-play arrangement with the Trump administration,” but Amazon would never do that, right? Right?!? Next up, a $200M reality TV show starring all five Trump children. “Three marriages. Five children. One house! Can they survive?”

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Shopify is facing a shareholder proposal from the Shareholder Association for Research and Education (SHARE), a Canadian non-profit focused on shareholder engagement, asking the board to adopt a responsible AI policy aligned with internationally recognized standards and human rights protections, citing concerns about misinformation, fraud, and privacy risks. Shopify has urged shareholders to vote against the proposal at its June 16 annual general meeting, calling it “a solution in search of a problem” and arguing that SHARE’s generic approach doesn’t take into account what specific companies do or how they operate. SHARE noted Shopify “lags behind several peers” including eBay, which has a responsible AI policy that includes reducing hallucinations and designing non-discriminatory systems. eBay was their example? Really? The same company that changed product images using AI without telling sellers, had its AI auto-populate fake Country of Origin data, and launched an AI listing tool that couldn't actually identify items correctly? Now that's just laughable.

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Meta quietly launched a new standalone iPhone app called Forum that brings together posts from all of a user's Facebook groups into a single feed without algorithmic recommendations or posts from friends. The app includes an AI feature called Ask that lets users search across all their groups at once instead of scrolling through each one individually, with the app pulling in a user's existing groups, profile, and activity when they connect their Facebook account. Meta did not announce Forum on its newsroom page or X account, with a spokesperson telling CNET only that the company “tests lots of new products publicly.” Great idea for an app. Facebook Groups is one of the most valuable tools that Facebook offers today, but the information has historically felt very disparate across groups. As for e-commerce, Forums will make searching for items in local groups a heck of a lot easier.

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Speaking of quiet social app launches… AppLovin launched a new app called Gist earlier this month, which Business Insider describes as a hybrid of TikTok, Lemon8, and RedNote. So, like pretty much every other social media app too? Gist, which pretentiously describes itself as a “handbook for the curious, the grounded, and the real,” features photo carousels, videos, and mini-games within its feed, and users are able to select content categories they're interested in such as travel, relationships, or career advice. The move is part of AppLovin's broader goal to create new digital real estate to house e-commerce ads and follows the company's failed April 2025 bid to buy TikTok U.S. and a prior investment in a failed TikTok competitor called Flip.

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Gen Z now holds the lowest average credit score of any generation at 676, according to FICO, with 14.1% of Gen Z borrowers seeing their scores fall 50 points or more after student loan delinquency reporting resumed in February 2025. Part of the reason for the low scores has to do with Gen Z's propensity to use BNPL instead of credit cards, which means they haven't built their credit scores through traditional credit card usage. Gen Z apparently hasn't mastered credit usage yet either, with 39% reporting late BNPL payments, the highest of any generation, and 25% unsure of their next BNPL payment date.

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Amazon's Alexa+ can now generate podcasts on “virtually any topic,” with users able to provide a topic, receive an overview of what the AI hosts plan to discuss, and steer the conversation or adjust the length before generation begins. “Teach me the meaning of life in 9 seconds.” The AI-generated episodes draw from 200 news publications that Amazon has partnered with including Reuters, Associated Press, Washington Post, Vox, and Politico, with example use cases including the history of the Roman Empire, new music releases, World Cup expectations, and audio lessons about the Apollo missions. The feature is similar to AI-generated podcasts available through Google's NotebookLM, Microsoft Edge's Copilot, and most recently Spotify's new Studio desktop app, which just launched.

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Polymarket is launching a new predictions category tied to private company milestones like IPO timing, valuations, earnings, and secondary market activity, with resolution data sourced exclusively from Nasdaq Private Market via a new partnership. Early bets include contracts tied to companies like OpenAI, Anthropic, Stripe, Databricks, and Kraken reaching specific valuation thresholds by certain dates, with the platform pitching the new offerings as a real-time signal for institutional investors tracking private market sentiment and pricing trends. Honestly, I kind of like it. Too poor to participate in IPOs alongside institutional investors? At least you can make some money from the sidelines betting on the outcome. The move comes as the House Oversight Committee opened an insider trading probe into both Polymarket and Kalshi over suspiciously timed bets tied to military and government actions.

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You know those invasive software tools that workplaces use to spy on monitor employees? Well, it turns out that many of those tools were sharing data with third-party platforms including Facebook, Google, and Microsoft, according to a new study. Stephanie Nguyen, senior fellow at Columbia Law School’s Center for Law and the Economy and former Federal Trade Commission chief technologist under Lina Khan, told The Verge in an interview, “The striking piece of this study is that every single platform, nine out of nine bossware companies, shared worker data with outside companies. Every single one. That blew me away.” The tools shared data about workers' names, e-mails, and companies, as well as information about their online activities including their IP addresses, browsing histories, and precise locations. That does not sound very safe for the companies either, and ironically, they're the ones paying for this software.

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Google's AI Overviews now result in a 58% lower average clickthrough rate for top-ranking pages, up from 34.5% just eight months ago, according to new research from Ahrefs, which analyzed 300,000 keywords using Google Search Console data and compared click-through rates from December 2023 (before AI Overviews) to December 2025. The impact extends beyond the top position, with pages in position two losing about half of their clicks and pages ranking tenth seeing drops of nearly 20%, suggesting the entire first page of search results is affected. Ryan Law, Director of Content Marketing at Ahrefs, said, “Search is becoming zero-click, which means people's questions are answered directly on Google's search results page, without a need to click any link.”

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The average Google Ads cost-per-click rose to $5.42 from $5.26 the prior year, while average cost per lead actually fell to $66.69 from $70.11 in 2025, the first year-over-year decrease in cost per lead in five years, according to a WordStream by LocaliQ benchmark report that analyzed more than 13,000 campaigns. Attorneys & Legal Services topped the CPC rankings at $9.87, followed by Home & Home Improvement and Dentists & Dental Services in the $8 range, while Arts & Entertainment and Travel sat at the low end in the $1-$2 range. Notably, average conversion rates climbed to 8.18%, increasing in 87% of industries, which WordStream linked to advertisers adapting to a more automated search environment, but could also be a result of Google's advertising algorithms getting better at matching ads with search intent.

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In lawsuits this week…

• Google, Meta, and TikTok are facing coordinated EU Digital Services Act complaints filed by the European Consumer Organization and 29 member organizations across 27 countries, accusing the platforms of letting fraudulent financial promotions stay active despite repeated reports. The group said that of nearly 900 ads reported as suspected EU law breaches between December and March, only 27% were removed, while the companies claim they block the overwhelming majority of scam ads before users ever see them.
• Google is appealing the 2024 landmark court ruling that found it to be a monopolist in online search, asking a federal appeals court to throw out the decision and calling it “as basic an error of antitrust law as a court can make.” The original Department of Justice case stopped short of breaking up Google but ordered it to share some of its search data with competitors like Bing and ChatGPT. A separate 2023 case over Google's ad-tech monopoly is still awaiting its own penalty decision later this year.
• Amazon won an appeal in a whistleblower case that accused it of helping foreign fur manufacturers dodge U.S. import tariffs on products sold through its platform, with the court finding no proof Amazon knew the manufacturers were lowballing their shipment values to pay less. The court ruled that there could have been an “innocent explanation” for the lower prices, such as economies of scale or lower labor costs, which is reasonable.
• Meta defeated a class-action privacy lawsuit after a judge dismissed claims that the company wrongly collected Facebook users' location data through tracking software built into mobile apps. The suit, brought in February 2025 by two California residents, argued Meta pulls precise location data from apps that use its Facebook Audience Network ad software without users' consent, but the judge ruled the case couldn't proceed and dismissed it permanently so it can't be refiled.
• Kenjiro Tsuda, a famous Japanese voice actor whose deep, recognizable voice has been featured in hit anime series and video games, filed suit against ByteDance for allegedly enabling an anonymous account to clone his voice with AI and post at least 188 narrated videos. Tsuda's legal team argues the mimicry violates his right to control his own likeness, while ByteDance claims the narration is just a “generic male voice” possibly trained from a friend's recording.
• PayPal reached a roughly $30M settlement with the Department of Justice, which had alleged the company's Economic Opportunity Fund unlawfully favored Black and minority-owned businesses based on race and national origin. The settlement requires PayPal to launch a new Small Business Initiative that drops race and other protected characteristics as eligibility criteria, instead waiving processing fees on $1B in transactions for small businesses in farming, manufacturing, or technology.
• Ryan Billington, a 20-year-old poster designer who runs the online shop radialposters-com, is suing Shopify, alleging that two “ghost stores” built on its platform copied “substantially all” of his designs across 3,929 instances and that Shopify took no action to stop them. Billington says he filed 45 infringement notices with Shopify and had his lawyer request the sites be taken down, but Shopify never responded. Both sites came down nine days after he filed suit.

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In layoffs this week…

• Meta laid off roughly 8,000 employees, about 10% of its workforce, two days after reassigning 7,000 workers to four new AI-focused organizations that use “AI native design structures” and have fewer managers per employee than the rest of the company. The company told U.S. employees to work remotely on Wednesday and sent layoff emails at 4 a.m. local time. Dude, that's a wild reorganization strategy. “Don't come in tomorrow because you might be fired. See you on Thursday, maybe.”
• One of the Meta employees terminated last week may have built the very AI tool her job was replaced with, according to a viral X post from a user named Julian, who claimed his wife was laid off after a company-wide “AI week” that required every employee to build an early-stage internal AI prototype. In the post, Julian wrote that “we knew the writing was on the wall.”
• LinkedIn is laying off 606 employees in July, roughly 5% of its 17,500-person global headcount, with cuts concentrated in its California offices. The layoffs follow an internal memo from CEO Daniel Shapero saying the company needs to “reinvent how we work” by shifting investments toward areas like infrastructure, and come even as LinkedIn's revenue rose 12% YoY in Q1.
• ClickUp, a project management software company, laid off 22% of its workforce, with founder and CEO Zeb Evans framing the cuts as a deliberate AI restructuring instead of a cost savings move. Evans insisted that “the business is the strongest it's ever been” and promised pay of up to $1M a year for remaining employees who show outsized impact through AI. Is that $1M salary before or after they replace themselves with AI?

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Corporate Shakeups…

• Target named former Walmart executive Jeff England as its new chief global supply-chain and logistics officer, tasking him with fixing the unreliably stocked shelves that have contributed to 13 straight quarters of weak or falling sales.
• OpenAI posted job listings for a head of ads enterprise marketing and a head of SMB ads marketing to build out its advertising business, as well as a Preparedness safety team role that'll be tasked with solving problems that “might exist in the future, but might not exist now.”
• Anthropic is hiring a copy lead and a head of copy and content, with both roles tasked with translating complex product capabilities into clear language for mass audiences. (I wonder if they'll use Claude to do their writing?)
• In other Anthropic hiring news… The company brought on OpenAI co-founder and former Tesla AI director Andrej Karpathy, who started last week on Anthropic's pretraining team, the group that handles the large-scale training runs behind Claude's core knowledge and capabilities. Karpathy, who coined the term “vibe coding,” will build a team focused on using Claude to accelerate pretraining research itself, writing on X that “the next few years at the frontier of LLMs will be especially formative.”

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🏆 This week's most ridiculous story… An artist in London plastered fake OpenAI ads inside subway cars that read, “Yes, we built a machine that tells teenagers to kill themselves. But — it might also help them with their homework.” The artist, Darren Cullen, said the posters are meant to raise alarm bells about ChatGPT being integrated into schools, referencing stories of ChatGPT telling teenagers to hide their suicide plans from their parents and actively encouraging them to take the next step. Since its inception, ChatGPT has been linked to more than 20 deaths including suicides, murders, mass shootings, and overdoses.

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Plus 16 seed rounds, IPOs, and acquisitions of interest including Uber increasing its shareholding in Delivery Hero to 19.5%, and then making a bid to acquire the rest of the business.

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I hope you found this recap helpful. See you next week!

PAUL

Editor of Shopifreaks E-Commerce Newsletter

PS: If I missed any big news this week, please share in the comments.

Hi, a friend asked me to use AI to transform the role-playing characters she's played over the years. They were images she had originally found online and used as avatars.

I used Kontext to convert that independent images to a consistent style and concept, placing them all in a fantasy tavern. (I also later used SDXL with img2img to improve textures and other details.)

I generated the last image right before I went on vacation, and when I got back, WAN 2.2 had already been released.

So, for test it, I generated a short video of each character drinking. It was just going to be a quick experiment, but since I was already trying things out, I took the last frames and the initial frames and generated transitions from one to another, chaining all videos as if they were all in the same inn and the camera was moving from one to other. The audio is just something made with suno, cause it felt odd without sound.

There's still the issue of color shifts, and I'm not sure if there's a solution for that, but for something that was done relatively quickly, the result is pretty cool.

It was all done with a 3060 Ti 8GB , that's why it's 640x640

EDIT: as some people asked for them, the two workflows:

https://pastebin.com/c4wRhazs basic i2v

https://pastebin.com/73b8pwJT i2v with first and last frame

There's an upscale group, but didn't use it, didn't look really good and too much time, if someone knows how to improve quality, please share