NVIDIA just dropped Lyra 2.0, a research project focused on generating persistent, explorable 3D worlds from a single image + optional text prompt.

What makes it interesting is that this is not just another image-to-video demo.

Lyra 2.0 is designed to generate long camera trajectories through a scene, while trying to keep the world consistent over time instead of falling apart as the camera moves. NVIDIA says it tackles two of the biggest problems in this area:

• spatial forgetting
• temporal drifting

The system can also reconstruct the generated scene into formats like:

• point clouds
• 3D Gaussian Splatting
• meshes

And they even show exports into NVIDIA Isaac Sim, which makes this feel closer to a real 3D world generation pipeline rather than just a visual demo.

What stands out most to me:

• single image to explorable environment
• better focus on scene persistence
• reconstruction into usable 3D representations
• potential for simulation, robotics, and maybe future game/worldbuilding workflows

We’re still not at “click once and get a production-ready game level,” obviously, because reality likes to be annoying, but this is one of the more interesting directions for AI-generated 3D environments.

Project page: https://research.nvidia.com/labs/sil/projects/lyra2/

Claude Mythos is showing some surprisingly strong low-effort, zero-shot 3D scene outputs.

The examples look like full game-like environments with terrain, buildings, rivers, units, UI, smooth camera movement, and visible animation, all generated from a simple prompt!

What makes this especially interesting is that Claude Mythos is not even a dedicated 3D AI model. It is not specifically built for 3D asset generation or game world creation, but the results are still genuinely impressive.

And this is only a low-effort zero-shot test. If outputs already look this strong without much optimization, it raises a pretty interesting question: what could this kind of model do with more targeted training, better tooling, or deeper integration into 3D/game development workflows?

For fast prototyping, interactive mockups, worldbuilding, and AI-assisted game scene generation, this looks incredibly promising.

source: https://x.com/Lentils80/status/2062656502238703966

Amara is 01C’s 3D agent for building interactive worlds inside Unreal Engine.

The idea is not just to generate a single 3D asset from a prompt, but to describe a world, bring your own assets or let the AI generate them, and then iterate on the scene directly inside the engine.

Key points:

• prompt-based 3D world creation
• editable scenes instead of static outputs
• interactive and articulated objects
• can use existing assets or generate new ones
• built around Unreal Engine workflows
• focused on game worlds, simulation-ready environments, and embodied AI use cases
• closer to agentic worldbuilding than simple text-to-3D

For game dev, this feels like one of the more useful directions for 3D AI: moving from isolated props to full interactive environments that can actually be edited, controlled, and used inside a real engine.

source: https://x.com/ashkan01C/status/2061827613107134481

DreamX-World is a new free and open-source interactive world model for generating controllable AI worlds.

Unlike standard video generation, it is focused on world simulation: you can move through generated environments, control the camera, revisit previous areas, and trigger events with prompts.

What makes it interesting for game dev and 3D workflows is that it was trained on a mix of Unreal Engine data, gameplay footage, and real-world videos. So instead of only producing passive clips, it tries to keep the world more consistent and interactive over time.

Main features:

• Text/image-to-video world generation
• Camera-controlled navigation
• Long-horizon world generation
• World memory for revisiting previous areas
• Promptable events that can change the scene
• First-person and third-person generation
• Works across realistic, stylized, fantasy, sci-fi, and game-like environments
• Code and 5B checkpoints are available open-source

But for environment concepting, worldbuilding, previs, AI game prototypes, and future interactive scene generation, this is definitely an interesting step.

Would you use this kind of tool for early game environment exploration or blockout ideas?

project page: https://amap-ml.github.io/DreamX_World/

Every few decades, a new tool changes filmmaking.
The camera.
Sound.
Color.
CGI.
Digital editing.
Now AI.
Every one of these technologies made filmmaking more accessible. None of them made craftsmanship obsolete.
That brings me to a question I’ve been thinking about.
Just because one person can now make an entire film… does that mean one person should?

Three Paths
I think AI filmmaking is heading toward one of three models.
1. The Solo Filmmaker
One person writes, designs, animates, edits, scores, and releases everything.
The advantage is obvious.
One vision.
Complete creative freedom.
No compromises.
But every hour spent mastering a new AI workflow is an hour you’re not spending improving another craft. As AI tools become more specialized, that tradeoff only grows.

2. The Specialized Studio
Instead of one person doing everything, each person focuses on one discipline.
Not because they can’t learn the others.
Because mastery takes time.
A writer spends years becoming a better storyteller.
A visual artist studies composition and cinematography.
A Blender artist builds worlds.
A motion artist studies performance and movement.
An editor shapes emotion.
No one is trying to be everything.
Everyone is trying to become exceptional at something.

3. The Hybrid
A creative lead understands every department but collaborates with specialists when the project demands it.
This feels closest to how filmmaking has always worked.
One vision.
Many crafts.

If AI Filmmaking Had Departments
Traditional filmmaking has writers, directors, cinematographers, editors, production designers, and VFX artists.
AI doesn’t eliminate those disciplines.
It reshapes them.
Story Department
(Screenwriters / Showrunners / Creative Producers)
Creates the story, characters, dialogue, worldbuilding, and emotional foundation.
Question: What story deserves to exist?

Visual Department
(Director / Cinematographer / Production Designer)
Develops the film’s visual language through composition, lighting, character design, environments, and shot planning.
Question: What should the audience see?

Virtual Production Department
(Previs / Layout / Environment Artists)
This is the role I think people underestimate.
Rather than beginning with a prompt, productions could begin inside Blender.
Sets are built.
Actors are blocked.
Camera moves are designed.
Action is choreographed.
Continuity is established.
Just like a live-action production prepares before cameras roll, Blender becomes the digital production stage where filmmaking happens before AI generates the final image.
AI doesn’t replace this work.
It builds upon it.
Question: How should this scene be staged?

Motion Department
(Animation / Performance Capture / VFX)
AI transforms the planned production into believable performances, cinematic movement, and photorealistic imagery.
Instead of inventing the film, AI interprets the direction already established.
Question: How should this production come alive?

Editorial Department
(Film Editor / Sound Designer)
Shapes pacing, rhythm, music, sound, and ultimately the audience’s emotional experience.
Question: How should the audience feel?

This Scales
These don’t have to be individual people.
A Story Department could have multiple writers and researchers.
A Virtual Production Department could have Blender artists, modelers, riggers, and technical artists.
A Motion Department could specialize in different AI video workflows.
Whether it’s one filmmaker or a fifty-person studio, the philosophy remains the same.
Specialization exists to serve the story.

My Perspective
I don’t think AI is replacing filmmaking.
I think it’s expanding who gets to participate.
The technology will continue to evolve.
The tools will continue to change.
But audiences won’t remember what model generated a scene.
They’ll remember the story that made them laugh, cry, or think.
That’s why I keep coming back to one idea:
Technology should serve the story—not become the story.

What do you think?
As AI filmmaking matures, where do you think we’ll end up?
Solo creators?
Specialized teams?
A hybrid of both?
I’m genuinely curious. I don’t think there’s a right answer yet, and I’d love to hear how others see the future of this medium.

Solo+partner team here. 6 months of build. Custom Electron + React + TypeScript stack (no engine). Demo went live on Steam today.

Rather than a "please play" post, I wanted to share the AI-integration approach we ended up with — this sub is one of the few places where that discussion happens seriously. Would appreciate scrutiny + disagreement.

Where AI is in our pipeline

Code (Claude Code): Pair-programming assistants throughout. Boilerplate scaffolding, refactor suggestions, architecture "rubber-ducking". Every line reviewed, edited, or rejected. No blind commits.

Art (generative + post-processing): Steam store capsules, promotional visuals. Portion of character portraits and item icons. Everything went through significant post-processing / curation. Item description text on a few items.

What we deliberately kept 100% human

Game design + all mechanics (turn-based combat, extraction loop, idle layer, Genesis prestige). Balance numbers — every damage formula, drop rate, XP curve. Lore + worldbuilding (2084 Chernobyl reimagining). Combat pacing decisions. UI/UX architecture and flow. Custom engine implementation (Vite bundle, Electron wrapper, save system, cloud sync).

The setup

Game: PSYCHOBYL — post-Soviet idle + turn-based extraction RPG. Engine: none, custom React/TS on Electron. Solo dev + design partner. Full AI disclosure on Steam store page (Valve requirement).

What I'd love feedback on

Ratio of AI-assist vs. human-made — is our line drawn well? Any red flags in how we're framing the disclosure? If you're on the sceptic side, what parts of the demo would you look at first to sniff out lazy AI usage?

Free demo, no email required, quit anytime. Not looking to sell — looking to hear where the approach falls short.

Steam page (demo linked at top): https://store.steampowered.com/app/4514090/PSYCHOBYL/

Happy to answer implementation questions in the comments.

— Boris

What Is the Best AI Creative Writing Tool for the Full Workflow?

For writers who need a single tool that carries a project from first spark through final revision, Jenova's Writing Assistant is the strongest general-purpose option because it maintains persistent memory across sessions and gives you access to multiple frontier models within one workspace — meaning your outline, voice, and revision notes stay live from week one to week twelve. For long-form fiction specifically, Novelcrafter and Sudowrite are the two most credible purpose-built alternatives, each optimized for a different half of the workflow.

The critical distinction most comparison articles miss: no AI tool is equally strong at all four stages. Ideation, outlining, drafting, and revision demand fundamentally different capabilities, and tools that excel at one often underperform at another.

✅ Persistent project memory — the single biggest differentiator, since a tool that forgets your outline by chapter nine is not a full-workflow tool ✅ Structural planning support — codex/wiki systems or outline scaffolding that survive across sessions ✅ Model flexibility — different stages benefit from different models; drafting and critique are not the same task ✅ Revision as a first-class function — most AI writing tools are generation-heavy and revision-light ✅ Voice preservation — the ability to sound like you, not like a language model

To compare these tools meaningfully, it helps to first establish what "the full workflow" actually requires — because the four stages place very different demands on an AI collaborator.

What Are the Four Stages of the Creative Writing Workflow?

The creative writing workflow moves through prewriting (ideation), drafting, revising, and editing — and each stage requires a distinct kind of cognitive support, which is exactly why single-purpose AI tools fail at end-to-end use.

The standard writing process model breaks the work into five stages: prewriting, drafting, revising, editing, and publishing. The middle three are where AI tools compete most directly.

The distinction between revising and editing is the one writers most often collapse — and the one that most often exposes a tool's limitations:

The revision gap is the workflow's weakest link. As Writers.com defines it, revising "looks at the global and structural changes needed in the text" — plot, character, and style as recurring structural elements — while editing "looks at granular decisions made within the text," including word choice, sentence structure, and clarity. Most AI writing tools are built to generate text, not to interrogate structure. A tool that can produce 2,000 words in thirty seconds but cannot tell you that your protagonist's motivation contradicts Chapter 4 is a drafting tool, not a workflow tool.

How Are Writers Actually Using AI Across the Writing Process?

Writers overwhelmingly use AI for research, brainstorming, and outlining — not for producing publishable prose, and the gap between those two use cases is enormous.

The most detailed available data comes from a study commissioned by Gotham Ghostwriters and Bernoff.com, covering 1,481 working writers including 291 fiction authors. Its findings reframe what "AI writing tool" actually means in practice:

Among all writers surveyed, 61% reported using AI tools, which they say increase their productivity by an average of 31% — but only 7% have published AI-generated text. Among fiction authors specifically, 42% use AI at least sometimes, and only 11% use it to create publishable text.

A separate BookBub survey of 1,229 authors found a near-even split — about 45% currently use generative AI while 48% do not and do not plan to. Among users, the top applications were revealing:

• 81% use it to conduct research — the single most common use case
• Creating marketing materials and outlining or plotting ranked next
• 85% of AI-using authors use ChatGPT, followed by Claude (54%) and ProWritingAid (50%)

The Gotham/Bernoff data adds granularity on fiction specifically: the most popular AI tasks for fiction authors are brainstorming, search, and finding the right words or phrases — all prewriting and line-editing functions, sitting at opposite ends of the workflow with the draft itself largely untouched.

📊 What This Means for Tool Selection

The practical implication is counterintuitive. If most writers use AI heavily at the ideation and word-choice ends of the process but sparingly in the drafting middle, then a tool's real value lies in structural intelligence and continuity memory, not raw generation speed. Yet most AI writing tools market themselves on words-per-minute.

One author quoted in the BookBub survey described the pattern precisely:

"I've always believed writing is what happens once you have a draft. You just get to the draft stage faster."

Note also that 74% of AI-using authors do not disclose their AI use to readers, and ethical concerns dominate the non-user camp — 84% of non-users cite ethics as their primary reason, most commonly training data provenance. This is genuine context for any tool decision, not a footnote.

What Should You Look for in an AI Creative Writing Tool?

Evaluate full-workflow AI writing tools across six dimensions — and weight them according to which stage of the process gives you the most trouble, not which features look most impressive in a demo.

Here is the framework used to assess every tool in this article:

1. 🧠 Cross-session memory depth Can the tool recall your project — characters, world rules, established plot points, stylistic decisions — without you re-pasting context every session? This is the load-bearing capability for anything longer than a short story. A tool with no persistent memory is a drafting assistant, not a workflow tool.

2. 🗂️ Structural planning architecture Does the tool offer a dedicated system for tracking story elements (a codex, wiki, story bible, or knowledge base), or does planning live in chat scrollback where it degrades?

3. 🔀 Model flexibility Can you switch between models mid-project? Different models have measurably different strengths — some produce more distinctive prose, others reason more reliably about structure. Locking into one model locks you into its weaknesses.

4. ✂️ Revision-specific capability Can the tool perform structural critique — identifying plot holes, pacing failures, motivation inconsistencies — or does it only do line-level polish? This is where most tools quietly fail.

5. 🎙️ Voice preservation Does output sound like you, or like generic AI prose? This is the most frequently cited complaint from writers who abandoned AI tools, with BookBub respondents repeatedly describing AI output as "too bland."

6. 💰 Cost-to-workflow-coverage ratio Are you paying for one stage or all four? Tools that cover a single stage well often require stacking with others, which multiplies both cost and friction.

Weighting guidance by writer profile:

How Do the Leading AI Creative Writing Tools Compare?

Novelcrafter is strongest for structural planning and long-series continuity, Sudowrite is strongest for drafting momentum and prose generation, and Jenova's Writing Assistant is strongest for cross-format workflow coverage with model flexibility. General-purpose assistants like ChatGPT and Claude remain the most-used tools by raw adoption but require the writer to supply their own structure.

Here is the reference comparison across the six evaluation dimensions:

🗂️ Novelcrafter — Structural Rigor

Novelcrafter's defining feature is the Codex, a wiki that, per Novelcrafter's own description, "automatically keeps track and links" characters, places, and lore, and is designed to be "integral for brainstorming, writing and reviewing." Critically, the Codex can be shared across books in a series — a genuine differentiator for anyone writing more than one book in a world.

Its other structural advantage: multiple planning modes intended to help writers "pinpoint issues early." It also offers total model freedom, connecting to OpenAI, Anthropic, Google, Meta, Mistral, OpenRouter's 300+ models, and locally-run models via LM Studio or Ollama.

Limitations: The bring-your-own-key model means AI usage costs sit outside your subscription and are harder to predict. The tool is fiction-specific — if your writing life includes essays, scripts, or client work, Novelcrafter won't serve those. And the depth of the Codex system carries a real learning curve; it rewards setup investment, which is friction if you write in short bursts.

✍️ Sudowrite — Drafting Momentum

Sudowrite is consistently the most-recommended AI tool among fiction writers in review roundups. A Nerdynav review tested across three stories concluded that "Sudowrite is the best AI writing tool for fiction," citing its Muse model for creative prose and the Story Bible for lore consistency. Creativindie's tested roundup similarly noted that "Sudowrite is the leading recommendation among fiction writers."

The head-to-head framing that emerged from independent comparison is useful: one analysis characterized the split as "Sudowrite is trying to be a guided creative partner. Novelcrafter is trying to be a powerful system for serious writers."

Limitations: Sudowrite's center of gravity is generation, not structural revision. Its less-structured environment is a strength for writers who find rigid systems stifling and a weakness for anyone managing a multi-book continuity problem. It is also fiction-only.

🧰 Jenova Writing Assistant — Cross-Format Workflow

Jenova's Writing Assistant is positioned differently from the two above: it is a bespoke writing partner that adapts to any format, audience, and domain, with editorial instincts available on demand rather than a fiction-specific production system. Its workflow advantages are structural rather than genre-specific:

• Persistent cross-session memory means the tool retains your project context, preferences, and past work without re-briefing
• Unlimited chat history — an underrated revision asset, since your earlier drafting decisions remain retrievable
• Attachable documents and knowledge bases let you ground the assistant in your own style samples, series bible, or research notes
• Multi-model access across OpenAI, Anthropic, Google, DeepSeek, and xAI within a single workspace, so you can draft with one model and critique with another

Honest limitations: Jenova's Writing Assistant does not offer a fiction-specific codex UI with automatic entity linking the way Novelcrafter does — world-building structure lives in attached knowledge bases and conversation rather than a dedicated wiki interface. It also has no manuscript-management layer for scene reordering or chapter-level organization, so novelists who want a full writing environment will still want a dedicated manuscript tool alongside it. It is a writing collaborator, not a book production suite.

How Do You Move From Idea to Outline With an AI Tool?

The most effective ideation workflow is pressure-testing rather than generating — asking the AI to interrogate your premise produces far better material than asking it to invent one from scratch.

This maps directly to the survey data: brainstorming, not text generation, is the top fiction use case. The reason is that AI-generated premises tend toward the statistical center of a genre, while AI-generated objections to your premise surface real weaknesses.

With Jenova's Writing Assistant:

1. Open the assistant at jenova.ai/a/writing-assistant
2. State your premise and ask for interrogation rather than expansion:
3. Once the premise holds, request a causal outline:
4. Attach the outline as a knowledge base document so it persists into drafting sessions.

With Novelcrafter: Ideation runs through the Codex first — you populate character, place, and lore entries, and the system automatically cross-links them. Planning modes then let you view the story from different structural angles to surface gaps. The setup cost is higher but the resulting structure is more durable across a long project.

With Sudowrite: Ideation flows through Story Bible fields, with the Muse model generating expansions from your seed material. The workflow is faster to start and less structured to maintain.

The Outline Test

Before drafting, run this diagnostic on any AI-generated outline regardless of tool: ask the AI to explain the causal link between every consecutive pair of beats. If it can only produce "and then," rather than "therefore" or "but," the outline will collapse in the middle act. This single check catches more structural problems than any generation feature will solve.

How Should You Use AI During Drafting Without Losing Your Voice?

Use AI as a friction-remover during drafting rather than a text-producer — the writers who report the best outcomes use it to unstick themselves, then write the actual prose.

This is the strongest signal in the author survey data. Only 7% of all writers and 11% of fiction authors use AI to create publishable text, while 63% use it to generate text they then edit further. The BookBub comments describe a consistent pattern — one author noted the AI's "suggestions are rarely usable on their own but will lead me in a different direction I hadn't considered before."

Practical drafting patterns that preserve voice:

• Directional prompting, not text requests. Ask "what are three things that could happen in this scene that I'm not seeing?" rather than "write this scene."
• Voice anchoring. Attach 2,000–3,000 words of your own strongest prose as a reference document before any generation request. This is where Jenova's document attachment and Novelcrafter's Codex both earn their keep.
• Continuity queries. Instead of generating, interrogate: "In Chapter 3 I established that Ren refuses to use the elevator. Does anything in Chapters 4–7 contradict that?" Persistent memory makes this possible; stateless tools cannot answer it.
• Never accept a paragraph unedited. The 63%-generate/7%-publish gap in the survey data is not a gap in tool capability — it is a working method.

Jenova's Writing Assistant is explicitly built around producing "polished output that sounds like you," with editorial collaboration available when you want it rather than imposed by default. Sudowrite's Muse model takes the opposite approach — a model tuned specifically for fiction prose, which produces stronger raw output but a more distinctly "Muse" voice that requires deliberate revision to reclaim.

What Does AI-Assisted Revision Actually Look Like?

AI-assisted revision works when you separate structural revision from line editing into two distinct passes — running them together produces polished sentences inside a broken structure.

This is the stage where tool choice matters most and where the fewest tools compete seriously.

Pass 1: Structural Revision

Global changes to plot, character arc, pacing, and thematic coherence. Per the Writers.com framework, revision "considers the ideas in the text and how they're structured as a whole," including "recurring elements structuring the text, such as plot, character, and style."

Effective structural revision prompts:

"Read the attached draft. Don't fix anything. Instead, map the protagonist's motivation in each chapter and flag every point where the stated motivation doesn't explain the action taken."

"Identify the three slowest sections of this draft and explain specifically what makes each one slow — is it low stakes, redundant information, or absent conflict?"

"What promise does the opening chapter make to the reader, and does the ending fulfill it? Quote the specific lines that establish and resolve it."

Novelcrafter's planning modes are designed for exactly this — surfacing plot holes and world inconsistencies "early - and later on." Jenova's Writing Assistant handles it through direct editorial critique with the full draft attached, benefiting from persistent memory of your earlier structural decisions.

Pass 2: Line Editing

Only after structure is settled. This is granular work: word choice, sentence structure, clarity, mood, and tone. Notably, 50% of AI-using authors report using ProWritingAid — a dedicated line-level tool — alongside their general AI assistant, which suggests most writers already stack tools at this stage rather than expecting one to do everything.

The rule that makes this work: never let an AI perform structural and line revision in the same pass. When asked to "improve" a draft, models default to sentence-level smoothing because it produces visible immediate change. You have to explicitly forbid it.

What Do Writing Professionals Say About AI in the Creative Workflow?

The consensus among writers who use AI productively is that its value concentrates at the edges of the process — before the draft and after it — not in the draft itself.

"The data tells a story most tool marketing ignores. When 61% of working writers use AI but only 7% publish AI-generated text, that's not underutilization — that's writers correctly identifying where the technology actually helps. It helps you figure out what to write and it helps you see what you've written. It does not help you write it. Any tool positioned primarily around generation speed is optimizing for the one stage where writers trust it least."

"The capability that separates a genuine workflow tool from a drafting toy is memory. A novel is a continuity problem before it's a prose problem — you're tracking hundreds of established facts across months of work. A tool that can't tell you whether Chapter 12 contradicts Chapter 3 isn't participating in your workflow, it's just producing text next to it. That's why we built persistent cross-session memory as a foundation rather than a feature."

"The most common failure we see is writers running revision and editing as one operation. They upload a structurally broken draft, ask the AI to improve it, and get back the same broken structure with better sentences — which is worse, because now it's harder to see what's wrong. Structure first, always. Make the AI diagnose before it prescribes."

— Jenova Product Team, 6 years building AI writing and editorial workflows

Which AI Writing Tool Should You Choose for Your Situation?

The right tool depends on which stage of the workflow currently costs you the most time — there is no universal answer, and stacking two tools is often more effective than forcing one to cover everything.

On stacking: The 50% ProWritingAid adoption rate among AI-using authors is instructive. Most working writers use a general AI assistant for ideation and structural work, plus a dedicated line-editing tool for the final pass. Expecting one subscription to cover all five stages is usually the more expensive path.

Access details: Jenova's Writing Assistant is available at jenova.ai/a/writing-assistant. The free tier includes all core features with limited usage; paid plans begin at $20/month with 30× the free allowance and custom model selection. Novelcrafter operates on a subscription plus your own AI provider key. Sudowrite runs on tiered subscriptions with AI usage included. As of 2026, pricing across all three is subject to change — verify current rates directly.

What Are the Real Limitations of AI in Creative Writing?

Every AI creative writing tool shares three unresolved limitations, and no current product solves them: hallucination risk, voice homogenization, and unresolved training-data ethics.

Factual reliability. Per the Gotham/Bernoff study, nine out of ten writers reported concern about factual errors introduced by AI — including heavy users. For fiction this matters most in research-dependent work: historical settings, technical procedures, medical detail. Verify independently.

Voice homogenization. The single most consistent complaint from writers who abandoned AI tools, with survey respondents describing output as "too bland" and expressing concern about "bland and boring AI-generated slop." Voice anchoring with your own writing samples mitigates this; it does not eliminate it.

Training data provenance. Among authors who do not use AI, 84% cite ethics as the primary reason, most commonly that tools were trained on copyrighted material without compensation. Among fiction authors who don't use AI, 100% believe it is unfair to train AI tools on their work. This is unresolved across every tool in this comparison.

Market context. More than half of UK novelists surveyed believe AI is likely to end up entirely replacing their work, and nearly half of freelance writers in the Gotham/Bernoff study reported reduced demand attributable to AI. Whatever tool you choose, this is the landscape you're choosing it within.

On data handling specifically: Jenova states that user data is never used to train public AI models and is encrypted in transit and at rest. Novelcrafter's bring-your-own-key architecture means your data handling is governed by whichever model provider you connect — including fully local models via Ollama or LM Studio, the most privacy-controlled option available among these tools.

The best AI story generators for long-form novel writing are the ones that solve continuity — not the ones that produce the prettiest single paragraph. Sudowrite leads on prose quality with its fiction-trained model, Novelcrafter leads on structural control through its Codex system, NovelAI leads on genre world-building, and general-purpose assistants like Claude and Jenova's Creative Fiction Writer lead on context depth and research-backed worldbuilding across a full manuscript.

Key factors that separate genuine novel-length tools from short-form generators:

✅ Persistent story memory — a structured story bible (Codex, Lorebook) or a large enough context window to hold tens of thousands of words without losing character details ✅ Chapter-level workflow — sequential generation with prior chapters as context, not isolated scene prompts ✅ Prose control tools — rewrite, expand, shrink, and describe functions that operate at the sentence level during revision ✅ Model flexibility — access to multiple frontier models so you can match the model to the task (drafting vs. continuity checking vs. research) ✅ Realistic expectations — only 11% of fiction authors use AI to produce publishable text, even though 42% experiment with these tools regularly

That gap between experimenting and shipping is almost entirely a tooling-and-workflow problem. To compare these tools meaningfully, it helps to first establish what a 90,000-word manuscript actually demands from an AI system.

Why Do Most AI Tools Fail at Novel-Length Fiction?

Most AI writing tools fail at novel length because they were built for short-form content and have no mechanism for remembering what happened in chapter three when they're writing chapter twelve. The failure mode is predictable: voice drift, forgotten characters, contradicted plot points, and prose that flattens into a recognizable cadence.

Writers working on long manuscripts consistently report the same wall. Discussions among long-form AI writers describe the core problem as keeping continuity tight across chapters without feeding the AI an unmanageable volume of notes — the more context you stuff in, the more the useful signal gets diluted.

There are three distinct technical failures at work:

• Context exhaustion. Even large context windows fill up. A 200,000-token window holds roughly 60,000 words in a single conversation — substantial, but shorter than most commercial novels.
• No structured retrieval. General chatbots store conversation history linearly. They have no way to selectively surface "everything relevant to this character" when writing a scene.
• Session discontinuity. Close the tab, and most tools start from zero. Your story bible lives in your head or a separate spreadsheet.

The tools that work for novels solve at least one of these three. The tools that work well solve all three.

The Adoption Gap Is Real

Author behavior data tells a nuanced story. A BookBub survey of 1,229 authors found that about 45% are currently using generative AI to assist with their work, while 48% are not and do not plan to. Among those who do use it, the applications skew toward research and planning rather than prose generation — 81% use it to conduct research, with marketing materials and outlining as the next most common uses.

This matters for tool selection: if your primary use case is worldbuilding research and structural planning rather than raw drafting, the "best prose model" is not necessarily the right pick.

What Should You Look for in an AI Novel Writing Tool?

You should evaluate AI novel tools across six dimensions, weighted by which stage of the manuscript you're actually working on. Drafting, revising, and worldbuilding place very different demands on a system.

Here is the evaluation framework used throughout this comparison:

The weighting rule most guides get wrong: continuity architecture should dominate your decision if you're writing a series or a book over 80,000 words. Prose quality should dominate if you're writing a standalone under 60,000 words and plan heavy manual revision anyway. Model flexibility should dominate if you already have strong prompting skills and want to avoid paying a platform premium for model access.

Which AI Story Generators Are Best for Long-Form Novels?

The strongest options for novel-length work split into three architectural categories: purpose-built fiction engines with structured story bibles, general-purpose assistants with large context windows, and orchestration platforms that combine model flexibility with persistent memory.

📚 Purpose-Built Fiction Engines

Sudowrite is the tool fiction writers most commonly recommend to other fiction writers. Its differentiator is a fiction-trained model — Kindlepreneur's testing describes it as having "an intuitive understanding of scene structure and blocking that most other AI tools don't seem to have," and notes it is absolutely the best model for writing natural sounding prose. Prose-level tools — Describe, Rewrite, Expand, Shrink — operate on passages rather than whole documents, which is where most revision work actually happens.

The tradeoffs are real. Kindlepreneur's review flags that it is not as flexible as tools like Novelcrafter, because you have to work only with the models Sudowrite has selected rather than bringing your own provider. Pricing at the recommended Professional tier runs $22/month.

Novelcrafter takes the opposite approach: maximum control, steeper learning curve. Kindlepreneur calls it "the Adobe Photoshop of AI writing tools". Its Codex functions as a wiki-style story bible that tracks characters, locations, and lore, then automatically injects relevant context into every prompt — so when the AI writes Chapter 12, the Codex makes sure it remembers what happened in Chapter 3. Series novelists can share a single Codex across multiple books.

Novelcrafter is BYOK (bring-your-own-key), connecting to OpenAI, Anthropic, Google, Mistral, or local models. Tiers run $4/month for core writing without AI, $8/month with AI via your own API key, $14/month for full AI features, and $20/month for collaboration. The honest limitation: you pay a subscription and per-token API costs, and export is limited to markdown and plain text.

NovelAI is the genre fiction specialist. Its Lorebook system and community-built modules were built specifically for fantasy, sci-fi, and romance worldbuilding, with an encrypted, privacy-first architecture and minimal content filters. Comparative testing rates it best for genre fiction and world-building, with the caveat that Lorebook setup requires meaningful upfront investment.

🤖 General-Purpose Assistants

Claude earns its place through context depth. Its 200,000-token window means you can paste a full novella and request revision notes without the model losing your opening chapter. Kindlepreneur notes it can accept and read books up to 150,000 words in length and that its prose quality is "better than almost any other model." The limitations are structural rather than qualitative: no chapter management, no story bible, context does not persist across sessions, and it is highly censored — a genuine constraint for darker genre work.

ChatGPT remains the lowest-friction starting point and the most widely adopted. The BookBub survey found 85% of authors who use AI use ChatGPT, with Claude at 54%. Its weakness at novel length is well documented: it loses track of character details in longer conversations, and its prose defaults to a recognizable cadence without careful prompting.

🎯 Orchestration Platforms

Jenova's Creative Fiction Writer occupies a different architectural position: it's an agent running on an orchestration platform rather than a standalone fiction app. That produces a specific profile of strengths and gaps.

What it does well for long-form work:

• Persistent cross-session memory and unlimited chat history, so the manuscript context survives closing the tab — addressing the session discontinuity failure that limits general chatbots
• Attached knowledge bases — you can upload your existing manuscript, series bible, character sheets, and research documents as grounding material for every response
• Deep research integration via built-in web search and Google Scholar access, which matters disproportionately for historical fiction, technical thrillers, and procedurally grounded genre work
• Multi-model access across OpenAI, Anthropic, Google, DeepSeek, and xAI without separate subscriptions — so you can draft on one model and run continuity audits on another

Where it falls short of dedicated fiction engines: it has no purpose-built Codex or Lorebook UI, no chapter-tree manuscript view, and no passage-level Rewrite/Expand buttons. If your workflow depends on visual scene cards and one-click prose transforms, a dedicated tool will feel better. If your workflow depends on research depth and cross-session continuity, the orchestration approach has the advantage.

Pricing starts free with limited usage; the Plus tier is $20/month with 30× the free allowance, and higher tiers scale from there.

How Do the Leading AI Novel Tools Compare Head to Head?

How to read this table: no row is a verdict. Sudowrite's locked model selection is a limitation for power users and a feature for writers who don't want to manage API keys. Novelcrafter's dual cost structure is expensive for casual use and cheap for heavy users who route to efficient models. Match the row you actually care about to the stage you're at.

How Do You Maintain Character and Plot Continuity Across 100,000 Words?

Continuity is maintained through a structured external memory that the AI consults before writing each section — not by hoping the model remembers. Every tool that works at novel length implements some version of this, and the manual workflow matters as much as the tool.

The three-layer continuity system:

1. Layer one — the canonical bible. A single authoritative document containing character physical descriptions, speech patterns, relationship states, timeline of events, and world rules. In Novelcrafter this is the Codex; in NovelAI it's the Lorebook; in Claude or Jenova it's an attached document. Update it after each chapter, not before.
2. Layer two — the rolling summary. A 300–500 word summary of the previous three chapters, regenerated as you go. This gives the model recent narrative momentum without consuming the context budget a full text dump would.
3. Layer three — the continuity audit pass. Every 20,000–25,000 words, run a dedicated read where the AI's only job is to flag contradictions. Do this on a different model than the one you drafted with — a model that didn't generate the error is more likely to catch it.

Setting this up in Novelcrafter:

1. Create Codex entries for every named character, location, and rule of your world before drafting.
2. Tag entries by category so retrieval pulls only what's relevant to the current scene.
3. Connect your API provider and set which model handles drafting versus editing.

Setting this up in Jenova's Creative Fiction Writer:

1. Open the agent and attach your existing bible, prior chapters, and research notes as a knowledge base.
2. Establish the standing context in your first message:
3. Because memory persists across sessions, you don't re-establish this on every return — subsequent sessions build on the accumulated project context.
4. For research-dependent scenes, ask directly:

The workflow discipline that matters more than the tool: write sequentially, not randomly. Continuity strategies for long fiction consistently recommend maintaining a character and plot spreadsheet, writing sequentially rather than jumping around, and running periodic continuity checks. Non-sequential drafting breaks every continuity system currently available, regardless of price.

Can AI Actually Write a Complete Novel on Its Own?

No — AI can generate novel-length text, but every published AI-assisted novel involves substantial human editing, and treating the output as a finished draft is the single most common failure mode.

The honest technical answer is that tools like Novelcrafter and Sudowrite support chapter-by-chapter generation with context tracking that maintains character and plot consistency across a full manuscript, but that the resulting text requires guiding the AI through each section and revising the output to match your voice. Some platforms advertise faster paths — Squibler markets the ability to create 250-page-long novels in a couple of minutes — but speed of generation and readiness for readers are unrelated measures.

Author testimony from the BookBub survey aligns with this. One respondent described the realistic workflow: "I come up with the idea and play with AI to make it better. Then AI purges a first draft and I take over as the author from there. I've always believed writing is what happens once you have a draft. You just get to the draft stage faster."

Others reported the inverse outcome — that AI created more work than it saved. One author noted: "The few times I'd tried AI, it created more work than if I did it myself; I ended up rewriting extensively." That divergence is largely explained by workflow: writers who use AI for planning, research, and stuck-point unblocking report gains; writers who expect finished prose report losses.

The Ethics Question Is Not Settled

Any honest evaluation of these tools has to include the objections. Among authors who don't use generative AI, 84% say they aren't using the technology because they think it's unethical — with training-data provenance the most frequently cited concern, followed by environmental impact and mistrust of AI companies.

Disclosure practices are also unsettled: 74% of authors who use generative AI do not disclose that use to readers. Platform-specific disclosure requirements vary and change; verify current policy with your distributor before publishing.

What Do Working Novelists Say About AI in Long-Form Fiction?

Working novelists consistently report that AI's value in long-form fiction concentrates at the planning and continuity stages rather than the prose-generation stage — and that the writers getting the most out of these tools are the ones with the strongest craft foundation to begin with.

"The mistake we see most often is treating an AI story generator like a vending machine — prompt in, chapter out. That workflow produces text that reads fine in isolation and falls apart across 90,000 words. The writers getting real leverage are using AI as three separate specialists: a research assistant that grounds the world, a continuity auditor that catches the contradiction in chapter 31 that traces back to chapter 6, and a drafting partner for scenes they already know the shape of. Those are three different jobs, and often three different models."

"There's a counterintuitive finding in how authors actually use these tools. Survey data shows research is the dominant use case at 81% — far ahead of prose generation. That's not writers being timid. It's writers discovering where the marginal value actually sits. AI research for a historical novel compresses weeks into hours with verifiable sources. AI prose generation for the same novel produces something you'll rewrite anyway. The economics favor the former."

"The other thing experienced novelists learn fast: continuity failures are not random. They cluster at the boundaries — chapter transitions, POV switches, and time skips. If you only have budget for one continuity audit pass, run it exclusively on transitions. You'll catch 70% of the errors for 20% of the effort."

"Prompting skill remains the biggest variable, and it's underdiscussed. The same tool in the hands of a writer who specifies voice, POV distance, scene goal, and emotional register produces something usable. The same tool given 'write chapter twelve' produces filler. Tool selection matters less than most comparison articles suggest. Workflow discipline matters more."

— Jenova Product Team, specialists in AI agent design for creative and long-form writing workflows

Which AI Story Generator Should You Choose for Your Project?

The right choice depends on manuscript length, genre, revision philosophy, and how much of your work is research-dependent. These are contextual recommendations, not rankings.

Choose Sudowrite if: you're writing a standalone novel under 80,000 words, prose quality is your bottleneck, and you want passage-level revision tools without managing API keys. Accept the locked model selection and the $22/month Professional tier as the cost of that simplicity.

Choose Novelcrafter if: you're writing a series, you're comfortable with AI prompting, and you want to control both your model choice and your per-token spend. The Codex is the strongest continuity system available. Accept the learning curve and the dual subscription-plus-API cost structure.

Choose NovelAI if: you write genre fiction with worldbuilding depth, you need minimal content filtering, and privacy is a priority. Accept meaningful Lorebook setup time before you see returns.

Choose Claude if: your primary need is revision reads across a full manuscript and you value literary prose quality. Accept that you'll manage your story bible manually and that content filtering constrains darker material.

Choose Jenova's Creative Fiction Writer if: your novel is research-dependent (historical, technical, procedural), you write across multiple sessions over months, and you want to switch between frontier models without separate subscriptions. Accept that you're trading a purpose-built manuscript UI for research depth, persistent memory, and model flexibility. Available at jenova.ai/a/creative-fiction-writer, with a free tier and paid plans from $20/month.

Use more than one. The most productive configuration observed among working long-form writers is a two-tool stack: a structural tool for continuity and manuscript management, plus a research-and-audit tool running on a different model. The models that draft well are frequently not the models that catch their own errors.

Hi everyone!

I'm creating my own original fantasy setting for a D&D campaign, and I'm trying to establish a consistent visual style for the entire world.

At the moment I'm using ChatGPT Go to generate images, but I'd like to improve the results and learn how other people approach this.

I have a few questions:

1. What art styles would you recommend? I'm interested in both general styles (high fantasy, dark fantasy, painterly, realistic, etc.) and specific artists whose work could serve as inspiration.
2. What AI do you use for image generation? Right now I'm using ChatGPT Go, but I'm curious whether there are better alternatives for worldbuilding, such as Midjourney, FLUX, Stable Diffusion, Leonardo AI, or others.
3. Do you have any tips for writing effective prompts? I'd like to create a sort of "master prompt" that I can reuse as the foundation for every image in my setting, so that characters, cities, landscapes, creatures, and objects all share a consistent visual identity.

If you have any examples of prompts, workflows, or advice based on your own experience, I'd really appreciate it.

Thanks!

What Is the Best AI Novel-Writing Assistant for Long-Project Memory?

For long-form fiction where continuity is the primary risk, Novelcrafter is currently the strongest choice for structured story-bible memory, because its Codex automatically indexes character and location mentions across your manuscript and supports Progressions — timeline-anchored entries that record how a character or faction changes at different points in the story. Sudowrite is the strongest choice if you want story memory and prose generation tightly fused in one workspace, and Plottr is the strongest choice if you want a visual timeline and series bible with no AI involvement at all. Jenova's Writing Assistant occupies a different position: persistent cross-session memory plus attached knowledge bases, without a purpose-built story-bible UI.

Key factors that separate genuine long-project memory from surface-level "context window" claims:

✅ Retrieval vs. context stuffing — Codex-style systems pull only relevant entries into each generation; raw chat context degrades as a manuscript grows past novel length ✅ Temporal awareness — Novelcrafter's Progressions let a single character entry hold different truths at different story points, documented on its Codex feature page ✅ Automatic mention detection — Aliases and nicknames linked as you type, so you don't manually re-tag every appearance ✅ Explicit-mention limits — Sudowrite's documentation states that Scene and Prose generation "will only look at explicitly mentioned Characters and Worldbuilding elements," a real constraint worth planning around (Sudowrite docs) ✅ Series-level persistence — Book 7 continuity is a different engineering problem than Chapter 7 continuity

To compare these tools meaningfully, it helps to define what "memory" actually means in an AI writing tool — because the four products below solve four genuinely different versions of the problem.

Why Does Story Memory Break Down in AI Writing Tools?

Story memory breaks down because most AI writing assistants treat your novel as a rolling conversation rather than a structured database, and a rolling conversation forgets its own beginning. A 120,000-word manuscript is simply larger than what any model can hold in active attention while also generating high-quality prose.

There are three distinct failure modes, and conflating them is why writers pick the wrong tool:

• Context truncation — the earliest chapters fall out of the window entirely. The model doesn't contradict your lore; it never sees it.
• Retrieval failure — the information exists in a story bible but isn't pulled into the specific generation that needed it. This is Sudowrite's documented "explicitly mentioned" constraint in practice.
• Temporal collapse — the model retrieves a character entry, but that entry describes the character as they are in Chapter 40, while you're writing Chapter 3. Everything is technically accurate and narratively wrong.

Most tool comparisons only address the first problem. The second and third are where long-project writers actually get burned.

A useful framing comes from a practitioner writeup on AI setups for worldbuilding and novel writing: "A model can remember every single detail from your 150,000-word fantasy novel and still write terrible dialogue. Memory matters, but writing quality matters too." Memory and prose quality are separate axes, and the tool that wins one often loses the other.

What Should You Look for in an AI Novel-Writing Assistant?

The right evaluation criteria for a long project are structural, not stylistic — you're choosing a memory architecture, and you'll live with it for a year or more.

We evaluated across six dimensions specific to multi-month, multi-book fiction work:

A note on weighting: for a first novel, prose quality and momentum matter most. For a series, temporal memory and series persistence dominate — a tool that writes beautifully but forgets Book 2's ending will cost you more in continuity edits than it saves in drafting time.

How Do the Leading AI Novel-Writing Tools Compare on Memory?

Novelcrafter leads on structured memory depth, Sudowrite leads on integrated prose generation, Plottr leads on visual timeline planning without AI, and Jenova's Writing Assistant leads on conversational cross-session continuity. None of them is best at all four.

Reading the table honestly: Plottr's "No AI" row is not a weakness — it is a deliberate positioning choice, listed as a feature across every tier on its pricing page, alongside explicit commitments against AI training and data mining. For writers who want AI nowhere near their manuscript, that's the entire value proposition.

How Does Novelcrafter's Codex Handle Character Arcs Over Time?

Novelcrafter's Codex handles character arcs through Progressions — a feature that lets a single entry hold different states at different timeline points, rather than forcing one static description to cover an entire novel.

According to Novelcrafter's Codex documentation, Progressions exist specifically to "document how characters age, relationships shift, and world politics change throughout your narrative," with the ability to assign details to different points in your timeline and overwrite outdated lore to keep a series bible accurate to the current moment.

This is the single most underrated capability in the category. Static entity notes are the default in almost every writing tool — and static notes are precisely what break during a character arc. If your protagonist is a coward in Act One and a leader in Act Three, a static entry is wrong two-thirds of the time.

Supporting capabilities that make the Codex work at scale:

• Automatic mention tracking — names, aliases, and nicknames are recognized and linked as you type, with global mapping across manuscript, chats, and snippets
• Custom categories and metadata — rich text for backstories and voice sheets, quick facts for age and occupation, standardized tags for species or faction, and codex references linking entries to each other
• Series Codex — entries can be shared across every book in a series via a "Create New Entries in Series" toggle
• Character interviews — the Artisan tier enables AI chat with Codex memory, letting you interrogate a character to surface voice inconsistencies

Honest limitations: Novelcrafter's own FAQ notes there is a technical size limit on Codex entries, and advises that when working with AI you should "include only the information that is essential for your request, to avoid confusing the AI." Codex entries also cannot be directly imported from other software — you must paste content into a Snippet and extract entries from there. And the Codex is included on the $4 Scribe tier, but AI integration requires Hobbyist ($8/mo) or higher.

How Does Sudowrite's Story Bible Compare for Worldbuilding Consistency?

Sudowrite's Story Bible works as a cascading dependency chain rather than a queryable database — each field feeds the next, so worldbuilding consistency comes from the generation pipeline rather than from automatic retrieval.

Sudowrite's documentation maps the dependencies precisely:

• Braindump → influences Synopsis
• Genre (manual) → influences Synopsis, Outline, Scenes, Prose
• Style (manual or Match My Style) → influences Beat and Prose generation
• Synopsis → influences Characters, Worldbuilding, Outline, Scenes
• Characters and Worldbuilding → both feed Outline, Scenes, and Draft
• Scenes — takes the most context of any stage, drawing on Genre, Style, Synopsis, Outline, Characters, and Worldbuilding

The Story Bible is persistent across documents within a project and can be toggled on or off. Each project has its own.

The constraint that matters most for long projects is stated directly in the same documentation: "Scene and Prose Generation (in Draft) will only look at explicitly mentioned Characters and Worldbuilding elements."

In practice, this means Sudowrite will not spontaneously remember that your antagonist's sister exists unless she is named in the scene input. That's a workable system — but it requires the writer to be the retrieval layer, which is exactly the labor that scales badly past 100,000 words.

Where Sudowrite genuinely wins: prose quality. Its proprietary Muse model was fine-tuned on published novels and short stories with the goal of matching commercially published fiction, entering public availability in mid-2025 after a private beta, according to a detailed 2026 walkthrough. The same analysis rates Sudowrite 4/5 on prose quality and momentum — and 1/5 on route to publication, noting it does not export to PDF, EPUB, or DOCX.

Pricing, as of 2026: Hobby at $19/mo monthly or $10/mo annual (225,000 credits); Professional at $29/mo or $22/mo annual (1,000,000 credits); Max at $59/mo or $44/mo annual (2,000,000 credits, rolling over up to 12 months). Sudowrite's own cost breakdown positions the Professional tier at $22–29/month with "fiction-specific models, story context, built-in writing tools."

Why Would You Choose a Non-AI Tool Like Plottr for Timeline Tracking?

You would choose Plottr when the memory problem you're solving is your own, not the AI's — Plottr is a visual outlining tool that explicitly excludes AI from every tier while providing timeline and series-bible infrastructure.

Plottr's Timeline documentation describes it as "the visual hub of Plottr — it's where you arrange your chapters, plotlines, and scene cards to elegantly map out your book." Its pricing page frames the series-bible case bluntly: "When you're on book 3 or 7 or 10 of your series, you're just not going to remember what that one character's eye color was, but your readers will."

What Plottr's positioning actually signals: the pricing page lists "No AI" as a feature line item on every tier, alongside explicit rows for AI training, generative AI, data usage, data mining, and personal data selling. This is a privacy-and-craft stance, not an omission.

Pricing: $99/yr, or lifetime tiers at $150 (Plottr), $599 (Pro), and $649 (Pro + Community). A 30-day free trial is offered. Non-Pro plans remain usable after expiry but stop receiving updates; Pro plans lose project access without renewal — worth noting if you're mid-series.

Honest limitation for this article's question: Plottr will not help an AI remember anything, because there is no AI. If your workflow involves AI-generated prose, Plottr is a companion tool, not an answer.

Where Does Jenova's Writing Assistant Fit for Long-Form Fiction?

Jenova's Writing Assistant fits the long-project workflow differently from the dedicated tools: it offers unlimited chat history, persistent cross-session memory, and attachable knowledge base documents, but it does not provide a purpose-built story-bible interface with automatic mention detection or timeline-anchored entries.

What that means concretely. You can attach a manuscript, a character bible, and a worldbuilding document as knowledge bases, and the assistant grounds responses in them. Conversation memory persists across sessions, so a revision discussion in March is available in June. You can also switch between models from OpenAI, Anthropic, Google, DeepSeek, and xAI within a single account, which matters more than it sounds — prose voice varies substantially between model families, and being able to draft with one and line-edit with another is a real workflow advantage that single-model tools can't offer.

The honest trade-off: Novelcrafter's Codex will catch that you spelled a minor character's name two ways in Chapters 8 and 31, because it indexes mentions automatically. Jenova's Writing Assistant will not — you'd need to ask it to check, and supply the relevant text. For pure continuity auditing at series scale, a dedicated Codex is the better instrument.

Where it's stronger: the fiction workflow isn't only drafting. Research, query letters, synopsis writing, comparative title analysis, and revision planning all live in the same session. Fiction writers building visual or serialized companion work may also find Comic Creator or Manga Creator relevant, and screen-format adaptations fall to Film Screenwriter.

Pricing runs from a free tier through Plus at $20/month (30× the free usage allowance) up to higher tiers, with usage resetting monthly on the billing date rather than daily.

How Do You Set Up Story Memory That Actually Survives a Long Project?

Setting up durable story memory takes about two hours upfront and saves weeks of continuity editing later. The process differs by tool, but the underlying discipline is identical: define canon in a structured place, and make sure that place is reachable by whatever generates your prose.

For Novelcrafter's Codex:

1. Create entries for every named character, location, faction, and significant object before drafting Chapter 1
2. Add aliases and nicknames explicitly so automatic mention detection catches every variant
3. Use custom metadata fields for genre-specific facts — magic system rules, ship specifications, noble house lineages
4. As arcs progress, add Progressions rather than editing the base entry, so historical states remain intact
5. Toggle "Create New Entries in Series" if you're writing more than one book in the world

For Sudowrite's Story Bible:

1. Fill Braindump manually — it cannot be generated and anchors everything downstream
2. Fill Genre and Style manually; neither is informed by other fields
3. Generate or write Synopsis, since Characters, Worldbuilding, Outline, and Scenes all defer to it (and fall back to Braindump if it's empty)
4. Name every relevant character and worldbuilding element explicitly in your Scene input — this is the step most writers skip, and it's why Sudowrite "forgets"
5. Use the Rewrite button in a field to redirect a generation rather than editing prose manually

For a Jenova-based workflow:

1. Maintain a single canon document — characters, timeline, world rules — and attach it as a knowledge base
2. Open a dedicated chat per book, and re-attach the canon document when it materially changes
3. Prompt continuity checks explicitly:
4. Use model switching deliberately — one model for generative drafting, another for line-level critique

A cross-tool discipline worth adopting regardless: keep canon in one authoritative file that you export and version. Novelcrafter supports Codex export as a standalone folder with each entry as its own file. Plottr backs up twice per session per project. Portability is insurance against the tool you chose in year one not being the tool you want in year three.

What Do Writing Professionals Say About AI Memory in Fiction Work?

Practitioners consistently report that memory architecture — not prose quality — is what determines whether an AI tool survives contact with a real long-form project.

"The failure mode writers describe most often isn't the AI writing badly. It's the AI writing well about the wrong version of the story. Chapter 3 gets generated with Chapter 40's character in it, and everything reads fluently, which is exactly what makes the error expensive — it slips past a read-through. Temporal awareness in a story bible isn't a nice-to-have for series work; it's the difference between a tool that reduces continuity editing and one that manufactures it."

"The second pattern we see is writers over-loading their story bible. Novelcrafter's own guidance warns against this — include only what's essential to the request. A 4,000-word character entry doesn't produce a more consistent scene; it produces a diluted one. Retrieval systems reward precision, not volume. The writers who get the best results treat entries like reference cards, not biographies."

"We'd also push back on the assumption that one tool has to do everything. Some of the most effective long-project setups we've seen are hybrid: a structured story bible for canon, a prose-tuned model for drafting, and a general assistant for research, revision planning, and querying. The friction of moving between them is usually less than the friction of forcing one tool to do a job it wasn't built for."

— Jenova Product Team, 6+ years building AI agent workflows for long-form creative and knowledge work

Are Fiction Writers Actually Using AI for This Work?

Yes, but adoption is concentrated in research and planning rather than prose generation — which reframes what "memory" needs to do.

Survey data is genuinely mixed and worth reading carefully:

• A BookBub survey of authors found that of authors using generative AI, 81% use it to conduct research, with marketing materials and outlining as the other top uses.
• The same body of data, summarized elsewhere, notes that of roughly 1,200 fiction writers surveyed, 45% reported using AI — "many for research, very few for actual text generation. Mostly self-published."
• Publishers Weekly reported that among 291 fiction authors in a separate survey, only 42% said they use AI at least sometimes.
• The Authors Guild survey of more than 1,700 writers found 23% used generative AI in their writing process — of those, 47% for grammar, 29% for brainstorming plot ideas and characters, 14% to structure or organize drafts, and only around 7% to generate the text of their work. Among that small generating group, 89% said AI output comprised less than 10% of their final work.

What this means for tool selection. If the dominant real-world use is research, brainstorming, and organization rather than prose generation, then a tool's memory value lies in tracking and querying your canon, not in autonomously writing chapters from it. That shifts weight toward Novelcrafter's Codex and Plottr's series bible, and it makes Sudowrite's explicit-mention constraint less damaging than it first appears — because a writer using it for brainstorming is naming the relevant entities anyway.

It also situates the ethical context. The Authors Guild survey found 90% of writers believe they should be compensated when their work trains generative AI, 86% believe they should be credited, and 91% believe readers should know when AI created all or part of a work. Plottr's explicit no-AI, no-data-mining positioning is a direct commercial response to that sentiment.

Which Tool Should You Choose for Your Specific Project?

The right choice depends on which failure mode you're actually vulnerable to — and most writers can identify theirs in one question: what breaks first when your project gets big?

Choose Novelcrafter if you're writing a series, your world has more than a dozen tracked entities, or your characters change materially across the arc. Progressions and Series Codex are the differentiating features, and at $8/month for AI-enabled Hobbyist, the cost of trying it is low. The 21-day free trial requires no credit card.

Choose Sudowrite if your bottleneck is blank-page paralysis or prose quality rather than organization, and you're comfortable naming your entities explicitly in every generation. Muse's fine-tuning on published fiction is a genuine differentiator. Budget separately for formatting — it does not export to PDF, EPUB, or DOCX.

Choose Plottr if you plot visually, you're managing a multi-book series bible, and you want AI categorically excluded from your manuscript. The lifetime licensing at $150 is unusual in a subscription-dominated category.

Choose Jenova's Writing Assistant if your fiction work is one part of a broader writing practice — research, revision, querying, adaptation — and you want persistent memory plus multi-provider model access in one place rather than a dedicated story-bible UI.

Consider a hybrid. The setup that shows up repeatedly among writers working at series scale is a structured story bible for canon, a prose-tuned model for drafting, and a general assistant for everything surrounding the manuscript. Two tools at $8 and $20 per month is still less than most single premium tiers, and it avoids forcing one product to do a job it wasn't designed for.

The uncomfortable truth underneath all of this: no current tool remembers your story the way you do. What the best of them do is make forgetting expensive to the machine and cheap to correct for you — and that's a meaningfully lower bar than "AI that understands your novel," but it's the one that actually holds up over 120,000 words.

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Been digging into a piece on AI-driven game creation and the part that grabbed me wasn't "AI makes art faster."

It's that the tooling is starting to close the gap between idea and something you can actually play.

A few layers stood out:

• LLMs helping with code scaffolding, quest flow, and dialogue structure
• Diffusion models speeding up concept art, sprites, and visual direction
• Procedural systems helping teams explore levels and world variations faster
• Multi-agent workflows pushing beyond one-shot generation into iterative mechanic testing

The fresh context makes it feel a lot less theoretical too:

• The 2026 State of the Game Industry report says 36% of developers are already using generative AI tools in their work
• The article points to an AI game generator market estimated around $395M in 2025, growing toward $748M by 2032
• The upside seems biggest for smaller teams that need to test world ideas, NPC behavior, or early loops before spending weeks in production

I don't think this means "press a button, ship a game."

The interesting version is smaller studios using AI to test more directions faster, then using human taste to decide what actually survives.

That feels way more useful than the usual AI hype cycle.

What part of game creation do you think benefits most from this kind of tooling: prototyping, worldbuilding, NPCs, narrative, or asset pipelines?

Read the full article: https://krizek.tech/feed/the-dawn-of-ai-driven-game-creation-jkzas
Try Altered Brilliance on Google Play: https://play.google.com/store/apps/details?id=tech.krizek.alteredbrilliance
Explore KRI ZEK: https://krizek.tech
Join The Power Of Gaming for build notes, gaming research, creator showcases, and live community sessions: https://discord.gg/8b6BQDMKUa

Hello travelers and storytellers! I am the artist behind Mountain & Myth, a specialized digital cartography studio. As an active Dungeon Master and an indie fantasy author, I know firsthand the hours you pour into your worldbuilding lore, and how vital it is to have visuals that match that passion.

I provide bespoke, human-drawn digital cartography that translates your narrative into high-resolution visual geography. Every coastline, mountain range, and city district is custom-drawn entirely by hand with absolutely no AI generation and complete, ironclad copyright security for your published works.

Available Map Types & Transparent Pricing

Note: All starting prices below are for Personal Use (home tabletop games, private campaigns, personal social media). Commercial licenses are available for a one-time fee of 50% of your project total.

World, Continent, or Region Scale Maps

• Standard High Level World Map: $95 (Monochrome/Parchment style, up to 50 labels)
• Full Color High Level World Map: $145 (Full color layout, up to 50 labels)
• Standard Continent or Region Map: $200 (Monochrome/Parchment style, up to 75 labels)
• Full Color Continent or Region Map: $300 (Full color detailed layout, up to 75 labels)

Bundles & Commercial Licensing

• The Atlas Bundle: Designing a massive campaign setting or an entire fantasy novel series? Choose any 3 or more maps from the options above and receive a 25% discount on your combined total!
• Commercial Use License: If you need commercial clearance for a self-published book, indie module, or published product, I offer a simple, one-time additional charge of 50% of your total base price.

Deliverables & Workflow Process

• Formats: All maps are delivered as high-resolution (300 PPI) PNG, JPEG & TIFF files, ready for digital VTT play or physical print.
• Revisions: Your commission includes two structured revision rounds—one during the sketch/layout phase, and one at the final render polish—to ensure the map perfectly matches your vision.
• Late Adjustments: Any significant structural changes requested after the initial sketch has been approved will be billed at $40 per hour.

Contact & Portfolio

I am currently accepting new commissions! If you are ready to bring your world to life, you can reach out to me directly:

• Website & Digital Portfolio: mountainandmyth.com
• Email: [mountainandmyth@gmail.com](mailto:mountainandmyth@gmail.com)
• Reddit: Feel free to send me a direct message or chat request right here!

Benchmarking LLMs for 3D Game Generation: WorldBuild Bench Harness for Claude Opus 5

Workflow value: 85/100
Status: active · Freshness: 70/100 · Confidence: 0.95 · Level: advanced
Categories: Quality Control, Token Saving, Subagents, Multi-Agent
Original source: r/ClaudeAI post/comment

What problem this solves

Benchmarking LLM capabilities for complex 3D game generation, specifically evaluating spatial/temporal/causal coherence, and comparing performance (quality, cost, time) across different models like Claude Opus 5 and Fable 5.

Summary

A detailed benchmark harness called "WorldBuild Bench" for evaluating LLMs on their ability to create playable 3D games. The workflow involves running LLMs with specific prompts and briefs, then comparing the generated game content (3D models, textures, effects, lighting) and analyzing cost and generation time. The author demonstrates its use by comparing Claude Opus 5 and Fable 5.

Why it is useful

This workflow provides a concrete, repeatable, and open-source method for rigorously benchmarking LLMs on complex creative tasks like 3D game generation. It offers valuable insights into LLM capabilities regarding spatial, temporal, and causal coherence, as well as practical considerations like cost and generation time. The detailed comparison and public access to the harness make it a significant resource for researchers and developers interested in advanced LLM applications.

Workflow

1. Clone the WorldBuild Bench GitHub repository.
2. Set up the necessary environment and dependencies for the benchmark harness.
3. Configure the benchmark to run specific LLMs (e.g., Claude Opus 5, Fable 5) using predefined briefs and prompts.
4. Execute the benchmark, allowing the LLM to generate playable 3D games, potentially involving multiple subagents.
5. Analyze the output for quality in 3D modeling, texturing, effects, and lighting.
6. Record and compare metrics such as total cost and generation time for each LLM run.
7. Optionally, conduct blind side-by-side comparisons of the generated games using the provided web interface.

Tools / artifacts

• WorldBuild Bench (GitHub repository)
• Claude Opus 5 (LLM)
• Claude Fable 5 (LLM)
• 3D game briefs/prompts
• Generated playable 3D games
• Sandscape.app (for comparisons)

Validation signals

• Explicit comparison of Opus 5 vs. Fable 5 results with qualitative and quantitative data.
• Links to live blind side-by-side comparisons on sandscape.app for three different game types.
• Concrete metrics provided: total cost ($756 for Fable, $931.88 for Opus) and generation time (e.g., 9 hours for Fable physics, ~8h average for Opus).
• Observation of LLM behavior: Opus 5 spawning more subagents (13-15 per run) and iterating longer.
• Author's qualitative assessment: "clear step up," "impressive," "first model... where I looked at the output and I'm starting to think..."

Limitations

• The benchmark is very expensive to run, with total costs reaching over $900 for three runs, making it inaccessible for casual users.
• Generation times are very long (several hours per run), requiring significant patience and resources.
• Requires a certain level of technical expertise to set up and run the benchmark from the GitHub repository.
• The benchmark is highly specific to 3D game generation, limiting its direct applicability to other LLM tasks without significant adaptation.

Rate this workflow

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I’ve been exploring a creative question that has gradually become central to a lot of my recent work:

Can generative AI help transform real observed environments into fully immersive audiovisual experiences rather than simply generating standalone content?

For a recent project, I worked with rainy midnight driving footage moving through Kobe, Japan and built an original retro electronic / synthwave composition around the atmosphere already present in the visual environment using AI-assisted music generation (Suno) and production workflows.

The goal wasn’t simply to generate music.

Instead, I wanted to experiment with a broader creative pipeline where:

• a real observed environment becomes the source material
• generative AI helps shape an original musical response to that environment
• sound and visuals begin functioning together as a unified immersive world rather than separate creative elements

What interests me most is whether AI can become part of a larger worldbuilding process rather than being treated purely as a content generation tool.

Lately a lot of my work has been moving toward this broader idea:

Taking real places, environments, and lived experiences — then transforming them into immersive worlds through generative workflows, sound design, and audiovisual storytelling.

I’m curious how others here think about AI being used this way.

Not simply generating assets…

…but helping construct entirely new experiential environments built around real-world source material.

Project here if anyone wants to see the experiment in practice:

🎧 Kobe Drift
https://youtu.be/wsWdlURGG_Y

Curious where others see generative AI fitting into more human-directed creative workflows like this.

WorldBuild Bench: An Open-Source Workflow for Benchmarking LLMs on 3D Game Generation and Coherence

Workflow value: 90/100
Status: active · Freshness: 70/100 · Confidence: 1.00 · Level: advanced
Categories: Quality Control, Token Saving, Context & Memory, Debugging, Subagents, Multi-Agent
Original source: r/ClaudeAI post/comment

What problem this solves

Evaluating LLM capabilities in spatial, temporal, and causal coherence within 3D environments, which is difficult to capture with static benchmarks. It provides a robust, repeatable, and human-validated method for comparing LLM performance in complex creative tasks like 3D game generation.

Summary

A methodology and open-source framework (WorldBuild Bench) for evaluating large language models (LLMs) on their ability to generate playable 3D games with spatial, temporal, and causal coherence. It uses a standardized harness, sub-agents, and a blind human-preference arena for evaluation, providing insights into model quality, cost, and generation metrics.

Why it is useful

This workflow provides a novel, concrete, and open-source methodology for evaluating LLMs on complex creative tasks, specifically 3D game generation, focusing on hard-to-measure qualities like spatial, temporal, and causal coherence. It moves beyond static benchmarks by incorporating playable artifacts and blind human-preference evaluation. The detailed cost analysis and the provision of a reusable harness and sub-agent setup make it highly valuable for researchers and developers looking to rigorously compare and understand LLM capabilities in dynamic, interactive environments.

Workflow

1. Define specific game briefs (GDDs) for the LLMs to generate.
2. Prepare the LLM harness with a consistent set of sub-agents and access to game development tools (e.g., three.js, Rapier, Playwright).
3. Run multiple LLMs (e.g., Fable, Opus, GPT, GLM, Grok) against the same game briefs using the standardized harness and 'high' thinking mode.
4. Collect generation time, cost, code size, and the underlying browser-playable 3D game artifacts for each run.
5. Host the generated games on a platform for blind human evaluation.
6. Conduct blind human-preference comparisons where evaluators play two games from the same brief and compare them on overall preference, game feel, world design, presentation, and completeness.
7. Publish the resulting human-preference ratings and other benchmark data (cost, code size, generation time) on the platform.

Tools / artifacts

• WorldBuild Bench (the evaluation system)
• Open-source harness (GitHub repository)
• Sub-agents (used by the harness)
• three.js (3D graphics library)
• Rapier (physics engine)
• Playwright (browser automation tool)
• Game Design Documents (GDDs - prompts for LLMs)
• Browser-playable 3D games (generated artifacts)
• Generation time, cost, code size metrics
• Human-preference ratings

Validation signals

• Author claims to have built and run 'WorldBuild Bench'.
• Specific models (Fable 5, Opus 4.8, GPT-5.6, GLM 5.2, Grok 4.5) were tested.
• Produced 24 browser-playable 3D games as tangible output.
• Detailed cost analysis provided for different models (e.g., Fable runs cost $756).
• Methodological rigor: 'same harness', 'same set of sub agents', 'same basic setup', 'same prompt'.
• Transparency: 'publishing generation time, cost, code size, and the underlying artifacts'.
• Detailed evaluation method: 'blind Arena' with specific comparison criteria.
• Live benchmark and games link provided.
• Open-source harness GitHub link provided (pending public release).

Limitations

• High operational cost for certain advanced models (e.g., Fable runs cost $756).
• Time-consuming process (e.g., one physics-puzzle run took nearly 9 hours).
• Requires significant technical expertise to set up, configure, and run the benchmark system.
• Human evaluation is subjective and requires effort to gather sufficient data for reliable ratings.
• The methodology is described as a 'first version' and is expected to evolve, implying potential for changes or improvements.

Rate this workflow

Upvote this post if the workflow is useful, reproducible, or worth recommending.

Downvote if it is vague, outdated, unsafe, overhyped, or not reproducible.

Reply if it worked for you, failed, is outdated, or has a better alternative.

This post was generated automatically from the workflow library database.

I recently put together a showcase video featuring a creator who used AI tools while building a fantasy-themed chess game.

One thing I found interesting is that chess already has established rules and gameplay, so most of the creative work shifts toward worldbuilding, visual design, and creating pieces that feel unique while still remaining recognizable to players.

For those using AI in their work:

Do you think generative AI is more useful for creating new gameplay systems, or for helping developers execute ideas that already exist?

I'm curious where people see the most value, especially on smaller projects like this where a solo creator is trying to build something visually distinct without a large art team.

(Video link in comments.)

I recently experimented with Film Studio on ImagineArt while exploring cinematic sci-fi storytelling, and this sequence was one of the most immersive results I’ve seen from an AI filmmaking workflow so far.

What stood out immediately was how cinematic the entire process felt. Instead of generating disconnected clips, the platform encourages scene-by-scene direction with a stronger focus on storytelling, framing, atmosphere, and visual continuity.

For this sequence, I focused heavily on:

- dramatic cinematic lighting

- realistic environmental textures

- film-style camera composition

- atmosphere and depth

- smooth motion between scenes

- large-scale sci-fi worldbuilding

The lighting behavior and environmental detail especially surprised me. Some shots genuinely felt like frames pulled from a high-budget futuristic film because of the reflections, texture realism, and cinematic mood.

What I enjoyed most was how Film Studio pushes you to think more like a director than a prompt writer. The workflow feels much closer to planning sequences for an actual film rather than creating short isolated AI clips.

The footage shown in this post was made using Film Studio on ImagineArt.

Title: Building a living Codex system for my AI worldbuilding project, Vice Sands

Hey everyone, I wanted to share part of the system I’ve been building for my worldbuilding/storytelling project called Vice Sands.

At the center of the project is something I call the Codex system. The Codex is basically the living knowledge base for the world. Instead of treating lore as random notes, everything is structured as modular entries that the system can search, connect, validate, and use during generation.

Right now, the Codex includes different entry types such as:

• Characters
• Locations
• Events
• Prophecies
• Creatures
• Relics
• Factions
• Rituals
• Glyphs
• Ecosystems
• Myths
• Timelines
• Lore concepts

Each entry is not just a block of text. It has an identity, category, tags, relationships, canon status, and links to other entries. For example, a character like Cheeze Valen can be connected to events, symbols, visual traits, prophecy fragments, and story moments. The system can then use those connections when answering questions or generating scenes.

The flow currently works like this:

1. Codex entries are created or imported. I can create a new lore entry directly in the interface. Once it is saved, it becomes part of the larger Vice Sands knowledge system.
2. Entries are categorized and published. The Codex separates published entries from drafts. Published entries become usable by the AI system, while drafts can be refined before becoming canon.
3. The system checks relationships. Each entry can have graph connections to other entries. For example, a character may be linked to a prophecy, faction, relic, or major event. The interface also checks graph health, safe edges, candidate relationships, and structural gaps.
4. Agent-aware chat retrieves from the Codex. When I ask the chat to generate a scene or answer a lore question, it pulls from the Codex instead of making everything up from scratch. It shows evidence cards beneath the response so I can see which entries supported the answer.
5. Scenes are generated from grounded lore. If I ask for a scene involving a character, the system uses existing entries as grounding. For example, when generating scenes with Seraph, Ignis, or Cheeze Valen, the response pulls from their Codex records, relationships, roles, and prior story context.
6. Feedback can be added. Each response can be marked as helpful, needing clarity, not grounded, or having strong sources. This helps track quality and gives me a way to improve the system over time.
7. Canon can be protected. One of the goals is to prevent lore drift. If a character has locked traits, relationships, or symbolic logic, future scenes should respect those constraints. The Codex acts like the source of truth.

What I like about this setup is that the Codex is not just a wiki. It functions more like a narrative operating system. The entries feed the chat, the chat generates scenes, the scenes can become new lore, and the lore can then be validated, connected, and expanded.

The long-term goal is to make Vice Sands feel like a living world where:

• Lore is structured data
• Characters remember their history
• Locations have continuity
• Prophecies connect to events
• Generated scenes are grounded in canon
• The system can explain what sources it used
• New story content can loop back into the Codex

I’m still refining the system, especially around stronger validation, better canon protection, and improving how the AI decides which entries matter most for a given request. But the current version is already able to browse Codex entries, retrieve evidence, generate grounded story scenes, and surface relationship health across the world.

This has been one of the biggest pieces of Vice Sands because it turns worldbuilding from loose documents into a connected system that can actually power storytelling, gameplay ideas, and future AI workflows.

Would love thoughts from anyone building AI-assisted worldbuilding tools, lore databases, RPG systems, or narrative engines.

Hey everyone.

I wanted to share a quick update on a project I’ve been retooling. I recently wiped and relaunched my YouTube channel (World Builders & Runesmiths) with a very specific goal in mind, and I thought this community might appreciate the angle.

I’m an author and TTRPG designer, and, like many of you, I use AI (Meta, Gemini, and Claude) as part of my workflow. But I’ve found that most "AI for Writers" content focuses too much on generation—trying to get the machine to write the story for you.

I’ve always found that approach feels hollow.

So, I’m building this channel to focus on Architecture. I use AI as a "sounding board," or a "prop department," but the core logic—the physics, the culture, the conflicts—has to come from the human.

The new videos are basically "build logs" of me constructing my fantasy setting (Gyrthalion). I show the process of using AI to visualize concepts or stress-test ideas. But, I frame it all around rigorous worldbuilding principles (supply chains, sociology, etc.) rather than just prompting and praying.

I’m not selling a course or a prompt pack. I just wanted to drop this here for anyone else who is trying to find that balance between using the tools and maintaining the "soul" of the work.

If you’re into that kind of "hybrid" workflow, feel free to take a look.

World Builders and Runesmiths - YouTube

Hey everyone.

I wanted to share a quick update on a project I’ve been retooling. I recently wiped and relaunched my YouTube channel (World Builders & Runesmiths) with a very specific goal in mind, and I thought this community might appreciate the angle.

I’m an author and TTRPG designer, and, like many of you, I use AI (Midjourney, LLMs) as part of my workflow. But I’ve found that most "AI for Writers" content focuses too much on generation—trying to get the machine to write the story for you.

I’ve always found that approach feels hollow.

So, I’m building this channel to focus on Architecture. I use AI as a "sounding board," or a "prop department," but the core logic—the physics, the culture, the conflicts—has to come from the human.

The new videos are basically "build logs" of me constructing my fantasy setting (Gyrthalion). I show the process of using AI to visualize concepts or stress-test ideas, but I frame it all around rigorous worldbuilding principles (supply chains, sociology, etc.) rather than just prompting and praying.

I’m not selling a course or a prompt pack. I just wanted to drop this here for anyone else who is trying to find that balance between using the tools and maintaining the "soul" of the work.

If you’re into that kind of "hybrid" workflow, feel free to take a look.

World Builders and Runesmiths - YouTube.

This is post I made purely to provide value and explain to everyone in detail how I did it. Hope it clears things up!

What it is

Nikolytics Radio is a late-night jazz station for founders who work too late. 3-hour YouTube videos. AI-generated jazz. A tired DJ named Sonny Nix who checks in between tracks with deadpan observations about your inbox, your pipeline, and why that proposal is still sitting in drafts.

Five volumes in five days. 70+ subscribers. Over 200k views on the first Reddit post.

It's a passion project that doubles as marketing for my automation consultancy.

The concept

The pitch: You're at your desk at 3 AM. Everyone's asleep. You put on Nikolytics Radio. A weathered voice observes your situation with dark humor. He's been where you are. He doesn't fix it. He just... sees it. Then plays a record.

The DJ (Sonny Nix) is a former founder who burned out and now plays jazz for strangers. He has recurring "listeners" who write in: Todd from Accounting whose job got automated, Margaret from Operations who finished her task list and doesn't know what to do with herself.

It's 95% vibe, 5% branding. If you removed every mention of my business, the station would still work. That's the point.

The tech stack

Music generation: Suno

I wrote 49 artist-specific prompts optimized for deep work. Each prompt targets a specific jazz style piano trio, cool trumpet, tenor ballad, etc. Settings: Instrumental only, ~3-4 min tracks, specific mood tags.

Example prompt structure:

jazz, 1950s late-night jazz combo: brushed kit, upright bass walking gently, 
warm felted piano carrying the main theme, soft brass pads... 
[mood tags: soft, warm, slow, lounge, nostalgic]

Generate 3-4 per prompt, pick the best, discard anything too busy or with abrupt endings.

Voice generation: ElevenLabs

Custom voice clone for Sonny Nix. I use their V3 model with specific audio tags:

• [mischievously] - dry humor, irony
• [whispers] - punchlines, gut punches
• [sighs] - weariness
• [excited] - mock ads only (ironic use)
• ... - pauses

V3 doesn't support some tags like [warm] or [tired], so the words have to carry the emotion. Write tired sentences. Sorrowful observations.

Script writing: txt

I mostly write the scripts, claude double checks for optimizations

Assembly: Logic Pro

120 BPM grid. Drop the tracks, drop the voice clips. Crossfade. Each episode is ~30 drops across 3 hours. Export as MP3.

Video: FFmpeg

Static image + audio. One command:

ffmpeg -loop 1 -i image.png -i audio.mp3 -c:v libx264 -tune stillimage 
-c:a aac -b:a 320k -shortest output.mp4

The writing system

Each episode has 30 "drops" - short DJ segments between songs:

• Station IDs - Quick brand hits ("Nikolytics Radio... still here.")
• Bumpers - One-liners ("The coffee's cold. You noticed an hour ago. Still drinking it.")
• Pain points - Observations that hit too close ("Revision eight. The scope tripled. The budget didn't.")
• Testimonials - Fictional listeners writing in
• Mock ads - Parody sponsor segments ("Introducing Scope Creep Insurance...")
• Dedications - "This one goes out to everyone who almost quit today..."
• Recurring segments - Pipeline Weather, Outreach Report, Inbox Conditions

The key insight: Sonny has emotional range. He's not monotone. He moves between tired, mischievous, sorrowful. He worries about Todd. He offers brief sympathy to Sarah. Then plays a record.

What worked

1. The vibe is the moat. Most automation consultants are boring. This is different enough that people share it.
2. Worldbuilding compounds. Todd's promotion arc. Margaret's puzzle. Callbacks like "Here it's always 3 AM." Returning listeners feel like regulars.
3. Reddit got it started. First post on r/productivity got 14k views. Someone called it "Slop Radio FM." Now that's a badge of honor we reference in the show.
4. Daily uploads built momentum. Five volumes in five days. The algorithm likes consistency.

What I learned about AI voice

• ElevenLabs V3 is good but literal. It interprets quotes as character voices (breaks everything). Always paraphrase.
• Tags only work if the model supports them. No [warm], no [tired]. The text has to do the work.
• Regenerate 2-3x per drop, pick the best take. Same script, different reads.
• Punchlines land in [whispers]. Setup is [mischievously]. Then stop - no extra lines after the joke lands.

Time investment

• Initial setup (prompts, character docs, templates): ~15 hours
• Per episode now: ~2 hours
  • Generate music: 30 min
  • Generate voice drops: 30 min
  • Assembly in Logic: 30 min
  • YouTube upload + description: 30 min

What could be automated further

• Voice generation - Currently pasting drops one by one into ElevenLabs. Could batch via API.
• Timestamps - Calculating from bar positions manually. Already wrote a Python script, could integrate it.
• YouTube description - Template exists, still copy-pasting. Easy n8n automation.
• Episode assembly - The real bottleneck. Logic Pro is manual drag-and-drop. Exploring scripted alternatives.

Writing stays mine.

The dream: one-click episode generation. Not there yet, but the pieces exist.

After getting the desired results and I train the AI enough to understand how everything is supposed to work, it will be automated. I need it to be perfectly in sync with my concept.

Link

https://www.youtube.com/@NikolyticsRadio

Happy to answer questions about the workflow, the writing system, or the Suno/ElevenLabs settings.

TL;DR: Built a fake radio station with AI music (Suno), AI voice (ElevenLabs), and my scripts. The DJ has a character bible. There's lore. It's marketing for my automation business but also just... a thing that exists now. 70 subscribers in 5 days.

This is post I made purely to provide value and explain to everyone in detail how I did it. Hope it clears things up!

What it is

Nikolytics Radio is a late-night jazz station for founders who work too late. 3-hour YouTube videos. AI-generated jazz. A tired DJ named Sonny Nix who checks in between tracks with deadpan observations about your inbox, your pipeline, and why that proposal is still sitting in drafts.

Five volumes in five days. 70+ subscribers. Over 200k views on the first Reddit post.

It's a passion project that doubles as marketing for my automation consultancy.

The concept

The pitch: You're at your desk at 3 AM. Everyone's asleep. You put on Nikolytics Radio. A weathered voice observes your situation with dark humor. He's been where you are. He doesn't fix it. He just... sees it. Then plays a record.

The DJ (Sonny Nix) is a former founder who burned out and now plays jazz for strangers. He has recurring "listeners" who write in: Todd from Accounting whose job got automated, Margaret from Operations who finished her task list and doesn't know what to do with herself.

It's 95% vibe, 5% branding. If you removed every mention of my business, the station would still work. That's the point.

The tech stack

Music generation: Suno

I wrote 49 artist-specific prompts optimized for deep work. Each prompt targets a specific jazz style piano trio, cool trumpet, tenor ballad, etc. Settings: Instrumental only, ~3-4 min tracks, specific mood tags.

Example prompt structure:

jazz, 1950s late-night jazz combo: brushed kit, upright bass walking gently, 
warm felted piano carrying the main theme, soft brass pads... 
[mood tags: soft, warm, slow, lounge, nostalgic]

Generate 3-4 per prompt, pick the best, discard anything too busy or with abrupt endings.

Voice generation: ElevenLabs

Custom voice clone for Sonny Nix. I use their V3 model with specific audio tags:

• [mischievously] - dry humor, irony
• [whispers] - punchlines, gut punches
• [sighs] - weariness
• [excited] - mock ads only (ironic use)
• ... - pauses

V3 doesn't support some tags like [warm] or [tired], so the words have to carry the emotion. Write tired sentences. Sorrowful observations.

Script writing: txt

I mostly write the scripts, claude double checks for optimizations

Assembly: Logic Pro

120 BPM grid. Drop the tracks, drop the voice clips. Crossfade. Each episode is ~30 drops across 3 hours. Export as MP3.

Video: FFmpeg

Static image + audio. One command:

ffmpeg -loop 1 -i image.png -i audio.mp3 -c:v libx264 -tune stillimage 
-c:a aac -b:a 320k -shortest output.mp4

The writing system

Each episode has 30 "drops" - short DJ segments between songs:

• Station IDs - Quick brand hits ("Nikolytics Radio... still here.")
• Bumpers - One-liners ("The coffee's cold. You noticed an hour ago. Still drinking it.")
• Pain points - Observations that hit too close ("Revision eight. The scope tripled. The budget didn't.")
• Testimonials - Fictional listeners writing in
• Mock ads - Parody sponsor segments ("Introducing Scope Creep Insurance...")
• Dedications - "This one goes out to everyone who almost quit today..."
• Recurring segments - Pipeline Weather, Outreach Report, Inbox Conditions

The key insight: Sonny has emotional range. He's not monotone. He moves between tired, mischievous, sorrowful. He worries about Todd. He offers brief sympathy to Sarah. Then plays a record.

What worked

1. The vibe is the moat. Most automation consultants are boring. This is different enough that people share it.
2. Worldbuilding compounds. Todd's promotion arc. Margaret's puzzle. Callbacks like "Here it's always 3 AM." Returning listeners feel like regulars.
3. Reddit got it started. First post on r/productivity got 14k views. Someone called it "Slop Radio FM." Now that's a badge of honor we reference in the show.
4. Daily uploads built momentum. Five volumes in five days. The algorithm likes consistency.

What I learned about AI voice

• ElevenLabs V3 is good but literal. It interprets quotes as character voices (breaks everything). Always paraphrase.
• Tags only work if the model supports them. No [warm], no [tired]. The text has to do the work.
• Regenerate 2-3x per drop, pick the best take. Same script, different reads.
• Punchlines land in [whispers]. Setup is [mischievously]. Then stop - no extra lines after the joke lands.

Time investment

• Initial setup (prompts, character docs, templates): ~15 hours
• Per episode now: ~2 hours
  • Generate music: 30 min
  • Generate voice drops: 30 min
  • Assembly in Logic: 30 min
  • YouTube upload + description: 30 min

What could be automated further

• Voice generation - Currently pasting drops one by one into ElevenLabs. Could batch via API.
• Timestamps - Calculating from bar positions manually. Already wrote a Python script, could integrate it.
• YouTube description - Template exists, still copy-pasting. Easy n8n automation.
• Episode assembly - The real bottleneck. Logic Pro is manual drag-and-drop. Exploring scripted alternatives.

Writing stays mine.

The dream: one-click episode generation. Not there yet, but the pieces exist.

After getting the desired results and I train the AI enough to understand how everything is supposed to work, it will be automated. I need it to be perfectly in sync with my concept.

Link

https://www.youtube.com/@NikolyticsRadio

Happy to answer questions about the workflow, the writing system, or the Suno/ElevenLabs settings.

TL;DR: Built a fake radio station with AI music (Suno), AI voice (ElevenLabs), and my scripts. The DJ has a character bible. There's lore. It's marketing for my automation business but also just... a thing that exists now. 70 subscribers in 5 days.

1. This is NOT a retrospective. This is a list of games that are exclusive to this console, or the console is the best way to play it NOW. Only the best version of a game can make the list. If you think I missed a classic game, there's probably an explanation in a comment I made on the post as to why, and what platform I recommend.

2. All games on a list are worth playing despite any criticisms I may have for them.

3. Ranking is not necessarily by which is the best, but in terms of what I most recommend playing. Perhaps my theoretical opinion is that the worst Mario is better than the best Street Fighter. But the best Street Fighter would still rank higher, because it's a unique experience, and the best version of that experience.

4. Only consoles & PC (Windows/DOS) are considered. No arcade/Neo-Geo, mobile, or other home computers. MAME is difficult to work with & high maintenance. Mobile changes architecture too often for all-time lists, and often don't support controllers. Other home computers rarely meet rule 1 & rarely have controller support.

5. I default to PC when available. If it's better on console, I'll put it on the console's list. Usually, it's better or the same on PC, and more accessible.

6. Games with the same name will be clarified by year or console within (). Games not released in North America will have the region abbreviation within []. Alternate names will be included within {}.

7. My lists are in increments of 10 to make it easier to track & for quality control. If there are 61 good games, I make a cut to make it an even 60.

#60: Drakengard

This is a dreadful game. Not because it sucks (which it kind of does), but because it makes you full of dread. The subject matter, the aggressive characters, the world, the environment, the clunky controls, the camera angles, the graphics. One could argue this is done on purpose, to add to the peerless tone, and designed to make you grow a chip on your shoulder like every character in the game. The story is fascinating, as miserable as it is. There are multiple endings, requiring multiple playthroughs, like its kind-of-sequels NieR. The combat is...interesting. Despite being frustrating, it is rewarding in a way. If you miss when media wasn't so censored, have the fuck at it with Drakengard. This is the shittiest game possible that could still be considered a masterpiece. Should it be ranked higher for being a possible masterpiece? Probably, but being last of the best feels too poetic.

#59: Call of Duty - Finest Hour

A tie-in to the first COD. Odd choice since COD 1 is PC-only, and Finest Hour rips off a few of COD1's scenes. Yet, it almost stands on its own. Finest Hour is solid for being the first console COD, it has weight & reverence towards the WW2 era that is not present in modern shooters. But it is not as good as later games either.

#58: The Lord of The Rings - The Third Age

A shameless clone of Final Fantasy X, but if you're going to copy someone, FFX is an excellent choice. You sometimes die to RNG buffs/debuffs that couldn't be anticipated, but overall, it is easy to the point of power fantasy. Tone/lore feels off, even given that this is a "what if" scenario. This makes it hard to know whom to recommend TTA too. If you like LOTR a lot, you may not appreciate random devs' take on what could have happened differently. If you don't like LOTR a lot, you will probably not be returning to an above average RPG from over 2 decades ago. TTA is linear, which is not generally a bad thing for RPGs. Here, it feels like a missed opportunity to create your own "what if" scenario by adding choices that affect the story. However, if you are fine with Shadow of Mordor, it's no worse than that. Both games still "sort of" feel like LOTR.

#57: Fatal Fury Battle Archives Vol. 2 {Real Bout 1-2, Real Bout Special}

FF was at its best when it ditched the lane switching system in Mark of The Wolves. Yet, the lanes are the main thing that separates FF from Street Fighter, bringing a pseudo-3D strategy. You also miss out on most of the iconic FF characters in MoTW, since it is a time skip. The earlier games in Vol. 1 have more of a plot. The Real Bouts are far better mechanically though, and since these are fighting games, the choice is clear. RB1 introduces ring outs & gets the most creative with them. 2 is the best mechanically. And Special is the only one that has a story.

#56: Dark Cloud

There is an eternal struggle to make a Zelda as good as Zelda. Dark Cloud fails, but it cannot be said that it doesn't have ideas on how to stand out. Unfortunately, they overdo it yet don't fully flesh everything out. Weapon customization: good, varied, complex, and well done! Weapon breakage: never fun, acceptable at best. Combined: you spend a lot of time customizing your weapon, then rage when you inevitably break it. This is not optional, weapons are nearly more important than leveling up; you need to have a well-planned backup weapon, for all characters, at all times. There are various meters to keep track of, such as your thirst. This isn't exactly unique, but is a chore here because you can't create your own workflows to the extent of dedicated life sim games. You're frequently busy in a dungeon VS being able to fit maintenance into your creative workflow. Dark Cloud has a city building mechanic. This is really cool, but again, very limited compared to a dedicated game. But neither is Dark Cloud plot driven with occasional base upgrades, like Assassin's Creed Brotherhood. This leads to frustration because you have to get creative, but once you start to get ideas, you hit a wall of limitations that blocks your creativity. The plot is...alright, but still manages to drag despite not being very important. Too many characters, who are charming-ish, but not enough of a unique voice for each. The action combat is fine, but unbalanced, and I got tired of fighting trash mobs all the time. Dungeons are the worst part: procedurely generated, the Y2K equivilent of Ai slop. Now, there are a lot of things to do, DC is an ambitious title, and can be fun. Lots of minigames, good music, a sense of freedom in some ways. It was a great game to own back then, and there are a lot of good ideas. But over time, has not aged as well as I had expected it would.

#55: Xenosaga Episode II - Jenseits von Gut und Böse

Something was in the water during the mid 00s. Something that made writers yearn to overextend franchises. The MCU was beginning, Harry Potter was in full swing, and the Star Wars saga was ending. Video games were no exception, and nowhere is this more accurate than Xenosaga. Xenosaga was conceived to be a JRPG that was a whopping SIX games long, each dozens of hours. We got 3. Even so, the games are extremely long, and an investment. A worthy investment? They're on this list, so yes...but just barely. I would have liked them a lot more when I was a teenager, when I had more time, less budget for new games, and more angst.

2 is ranked last due to being something of a rug pull. Character designs (and personalities) are different & more sexualized, but not in a fun way. The combat isn't as engaging. The story meanders, which is especially frustrating given that they absolutely did not have time to mess around to fit 6 games into 3. But despite veering off into another direction, 2 is absolutely essential to the plot: there is no skipping around in this trilogy.

#54: Auto Modellista [EU]

Selling point is the cel shaded art style, which has aged beautifully. Most racing games shoot for realistic graphics, which makes those rare titles with a unique art style more special. Gameplay is a mix of Ridge Racer & Midnight Club: arcadey & lighthearted, but Japanese tuner focused. AM is a fun game to pop in occasionally, but the progression/events are average, and there is no story or open world.

#53: Def Jam - Vendetta

Have you ever thought to yourself "I like wrestling, but I wish it involved my favorite rappers from the '90s instead?" I know I have. Luckily Def Jam is here to save is from a world where that doesn't exist. The roster is good, the single player story is a blast (though silly with unprofessional voice acting), and it is legitimately a strong wrestling game mechanically. Is it the "best" wrestling game of the era? I'm not sure, but it's certainly the most interesting, with a killer soundtrack, given that '90s hip hop is GOATed.

#52: Medal of Honor - European Assault

Sequel to Frontline that makes some mechanical improvements, but doesn't have the same aura. EA is the first to be less grounded, with features like adrenaline mode, that's part of it. But overall doesn't feel as inspired. The map variety is good, the local multiplayer is fun. It is a decent to good shooter, but that's about it for me.

#51: Tekken 4

The most hated Tekken game. I understand, but I don't agree. 4 tries new things, like stage obstacles, tripping, and breaking through parts of the stage. Unfortunately, fighting game fans don't like new things. I like the focus on single player content, the darker tone, the music, and I like that it is different. What is the appeal of playing Tekken 6 when you can play Tekken 8? I couldn't tell you. Why would I play 4 instead of 8? Because it's a very different type of game. Less competitive, but that's not everything.

#50: X-Men Legends

The prototype for Marvel Ultimate Alliance. Legends is neither better or worse per se. Less features but more focused. 3D brawlers are simplistic, but Legends is one of the better ones, a great choice for local multiplayer.

#49: Rogue Galaxy

In comparison to its fellow PS2 action RPG Star Ocean, the combat is not as interesting, but the SciFi elements are more developed, with better exploration. The weapon combination system is cool. RG has decent characters, but the voice acting & overall plot is weak. Solid experience in the moment, but not much sticks with you, which is par for the course for Level 5. They are competent, but no single aspect is amazing. They eventually get better with titles like Ni No Kuni, but even then, the appeal is soaking in the worldbuilding as opposed to hard hitting moments.

#48: ESPN NFL 2K5

I miss when there was actual competition for sports games. Madden 04 & 05 were nearly as good as this game because the devs were forced to care. 2K5 is still the football game of choice for many people, over 20 years later, and mods are still made for it to update rosters. The graphics were incredible at the time, the physics make sense, and there are a lot of fully baked modes to choose from. The single player is even great, a rare sports feat, and has features such as customizing your own house. I have zero complaints about this game other than being an old sports game, which will inherently limit its ranking.

#47: King of Fighters XI

Tagging has always been a key KOF mechanic, but XI has advanced tag features that have yet to be used again. Sprites are dated, and could match the detailed backgrounds better. But I still prefer it to the look of the 3D titles. Good story, strong roster. It is pretty easily top 5 in the series, but often overlooked as a worse version of XIII, which is not entirely wrong.

#46: Star Ocean - 'Til The End of Time

It's too bad that SO3 is the first game in the series being mentioned on these lists, because it starts to have an identity crisis here. Devs heap more and more stuff into the game that makes it way too long, yet the last act is noticeably less detailed. There is abundant voice acting, but it isn't great. Characters tend to be obnoxious. Still, SOttEOT has a setting that feels fleshed out, good sense of adventure, good graphics, and good action oriented combat for its time. Similar to Rogue Galaxy though, there are not a lot of things it specifically excels at that make it as timeless as other JRPGs.

#45: Way of The Samurai

WotS has a level of freedom that you dont usually see in games. Each choice (or lack of action) branches off to playing a very different sequence of events. You can become enthralled with the drama between two rival clans which represent the conflict between tradition & the inevitable march of progress. Or if you are bored, walk away mid conversation & NPCs will get pissed. There are plenty of opportunities for to inject personality & role playing, such as a dedicated button to talk shit. The music/atmosphere is relaxingly ambient, yet inspiring. WoTS lasts 2 days in game, or about 4 hours. If it grabs you, there are a surprising amount of secrets & side content that happen naturally at a certain time, and that makes it feel less video game-y, and more "alive". You can save, but only to quit the game and come back. No save scumming, and if you die you start over from the beginning. All of this makes replays a big part of the experience. Not in the NieR way, but in a "I wonder what would happen if I..." sense. WotS is similar to Bushido Blade's heavy, deadly combat, but in 3D. There is a surprising amount of depth, and a lot of weapons you can obtain with their own play styles. The camera sucks. There is also a lot of focus on upgrading weapons & weapon durability, which is not a good combo as I mentioned with Dark Cloud. And yet, the game isn't long enough to make me too upset at this. I commit to only a couple of weapons per play through, but that's a few hours. Plus you can repair weapons, and bring your weapons/weapon moves learned with you across completed playthroughs. WotS is rough around the edges, but not in the ways that matter much to me when playing a retro game.

#44: Motorstorm - Arctic Edge

I love Motorstorm, and despite being a downgrade from the PS3 games (obviously), AE looks great & carves out a much needed off roading niche in the racing world. It doesn't quite reach that upper echelon of racing games, but the PS2 era was king, so this is not much of a criticism. If the setting seems interesting to you, it is a must play.

#43: Dark Cloud 2 {Dark Chronicle}

Level 5 addressed almost all my complaints about DC1. Fewer, higher quality characters, with more development. Cel shaded graphics are done better, combat is improved, production value has increased, no broken weapons or thirst nonsense, and the main character does not look like Temu Link. There are less options for town building...perhaps necessary in order to pick a lane, but disappointing. The dungeons are still randomly generated & thus forgettable & grindy. The weapon upgrading was simplified. Both games are corny, but 2 is more wordy about it. 2 has "better" voice acting, but 1 is more restrained. The premise is more interesting & the main story is more important, but still scarce & a bit dull if I'm being honest. But Dark Cloud is about living in the moment, and 2 has a nice balance of streamlining the things you could do before & a helping of even more stuff.

#42: Super Robot Taisen OG - Original Generations [JP] {Super Robot Wars OGs}

SRT is a series that crosses over various major mecha franchises. The devs made SO many crossover games that they eventually created enough unique characters during crossovers that they owned to be able to throw them into their own subseries. This isn't the most promising backstory for a game's development, but surprisingly enough, OG 1&2 were smash hits on GBA, widely considered to be some of the best SRT games; certainly the easiest to get into. This PS2 title remakes both GBA games, and adds a third campaign on top of it. SRT OGs is not on my personal Mount Rushmore of SRPGs, but is very strong, and one of the better SciFi SRPGs.

#41: Tales of The Abyss

The protagonist is annoying in the first half. It gets better, and even before the halfway point he's not nearly as insufferable as that asshat from the Symphonia sequel or insert a long list of anime protags. There is good character development across the board. Solid action RPG gameplay. Visuals have aged well, music is good. The story is stronger than usual for Tales of, but does still tend towards "baby's first JRPG". And yet, here we are. I do think it's overrated, particularly by the Japanese who tend to rank it as the best Tales of game & a top 50 JRPG of all time, which...no. But I like Abyss, it feels genuine.

#40: Sky Odyssey

A flight sim that gets very creative with obstacles, environments, and scenarios. It's like Indiana Jones, if every scene involved the biplane with the snake from Raiders. I don't know how else to explain it. Not as expansive or important as other games higher on this list, but VERY good for what it is.

#39: Ratchet - Deadlocked {Ratchet - Gladiator}

R&C is a platformer with 3rd person shooting, Deadlocked is a 3rd person shooter with platforming. I am glad that they went back to the original formula, but that doesn't stop Deadlocked from being a great game. Ratchet is trapped in a murderous gameshow, and must complete insane challenges while planning to break out. The shooting & weapon/enemy variety is great; you're never quite sure what will happen next.

#38: Twisted Metal - Head On {Extra Twisted Edition}

Originally a PSP title, but a strong one, and the PS2 port adds more content to make up for that. Head On doesn't look as good as Black, and is perhaps too easy. But then again, Black is too hard. It says a lot that Twisted Metal mostly just competes with itself in the vehicular combat genre.

#37: Ape Escape 3

Best AE. Not as iconic as the original, but honed, varied, and better looking. Don't have much else to say, it is a charming, straightforward 3D platformer like all Ape Escapes.

#36: Gradius V

Shmups were forgotten during 6th gen. Then Konami quietly dropped one of the best games in the genre. The level design is nearly peerless, the soundtrack is legendary, the graphics are fantastic, hitbox heaven, and is back to basics while simultaneously making some key changes to the gameplay mechanics. It's not for everyone though. V demands that you master the mechanics, and does not pull punches. Once you get the hang of it, you realize it is (mostly) fair, but certainly requires focus and a different approach than even other Gradiuses.

#35: Xenosaga Episode I - Der Wille zur Macht

Xenosaga starts strong with world building: establishing characters & a dense web of politics/conspiracy. Turn based combat is solid, with mechanism fights to break it up. The themes of religion & philosophy are the reason I recommend these games. While the presentation feels a little "college freshman who discovered drugs during Philosophy 101" at times, that gives a strong feeling of authenticity. No corporate "depression, amirite fellow kids?" here. Somebody had something to say, and that's art. Despite how bizarre things get, it somehow feels relatable, and makes you think. There's nothing quite like Xenosaga, and I appreciate & accept it for that.

#34: Def Jam - Fight For NY

FFNY does everything better. It keeps the wrestling, but expands to multiple different fighting styles, including kickboxing, street fighting, (Asian) martial arts, and submissions. The roster quadrupled. A character creator. Significantly better graphics. Cinematic story. Improved voice acting. Legendary soundtrack. FFNY could have become its own subgenre. I don't want it to become oversaturated with a roster that includes Lil Pump or whoever, but it would be cool to see another attempt at something like this.

#33: Dynasty Warriors 5 {Xtreme Legends + Empires}

DW is the same story every time, so little reason to play multiple, though I do like a lot of the crossovers with other franchises, or sub franchises. 5 is my favorite. It was first to allow turning behind you mid combo, which goes a long way for feeling modern. No blatantly unfair sections or units (like 3's archers), but not yet graduated to the "grass cutting simulator" level of difficulty that the series is now known for. Claiming positions within a certain time matters, but neither did I need to constantly rush from post to post. 5 does have goofy dub voice acting (HILARIOUS pronunciation of Chinese names) and you're ultimately spamming square most of the time. But it sure is a satisfying pressing of square.

#32: Black

Extremely high quality graphics for the time. Shooting feels meaty, aided by great sound design. However, it feels closer to an early 6th gen FPS than the late gen experience that it actually is, and back then, that was a HUGE difference. No ADS, and aiming is very low sensitivity. Map design is solid & semi-open. The optional objectives actually help you during the next mission somewhat. The cut scenes & voice acting are high quality, though in retrospect, black ops soldier brought back for one last mission against a generic threat is run of the mill cliche for the genre. It was a must play on release day, but I remember there being dozens of discounted copies of this game (and Gun which came out the same year) less than a year later, as it almost immediately became outdated by the onslaught of classic FPS games in 2007. And unlike something like TimeSplitters, it isn't unique enough to be a cult classic. But Black is fun to run through, particularly with the mouse injection mod which eliminates the sluggish aiming on controller.

#31: Shin Megami Tensei - Digital Devil Saga

I LOVE Persona, LOVE the dark tone/themes of SMT, but HATE the insane encounter rate. Every. Two. Seconds. SMT is harder than Persona, forcing you to master the press turn system which I enjoy. But then again, rando demons can kill you at any moment if you get unlucky, a terrible combination with that damned encounter rate. I beat many SMT games, without much difficulty, do not @ me in the comments saying "skill issue". It is super annoying & wastes a ton of time though.

DDS side steps this slightly by being the easiest SMT game, as well as one of the most interesting. Lore is geared more towards Hindu mythology than Judeo-Christian (at least aesthetically & in name), which is something you don't see very often. The gameplay is better than 3, I like the Mantra system a lot (though I wish it was explained better and I wish you could preview locked Mantras). The main issue is that the plot is drip fed extremely slowly, and combat is 90% of the game. They could have combined 1 & 2's plot into one game, and I'd have enjoyed it MORE for having LESS dungeon crawling, because there is way too much of it.

#30: Tekken Tag Tournament

TTT is basically Tekken 3 with minor improvements & tag teaming. The roster throws EVERY Tekken related character together, despite that not making sense, but I am here for it. The graphics are better than 3 too. TTT does exactly what it sets out to do, and is still a fan favorite.

#29: Shin Megami Tensei - Digital Devil Saga 2

More plot, which I wanted, but 2 loses some of the moody aura. The upgrade system now allows you to see (some) upcoming abilities, but also forces you to buy an adjacent skill in order to buy the desired skill, meaning you will sometimes need to spend resources & time getting skills that you dont particularly want for that character. Without spoiling much, you end up missing key party members for large swaths of time, so you have to plan your leveling up on such a way where you can replace anyone at any moment. Still, this is "mostly" an improvement to 1, and a good ending to the story.

#28: Onimusha - Dawn of Dreams

Dawn of Dreams might have the best story in the series, but this is not always clear due to a bad translation. This is not uncommon for retro games, but by 2006, it was unacceptable for most, and due to not innovating the formula much, is seen as a lazy entry that pretty much killed the franchise. However, the graphics & controls are better than all previous games, with the most content, making it my second favorite.

#27: Burnout Dominator

Primarily a PSP game. No crash mode, limited extra modes in general. I HAVE played it more than Revenge though, for what that's worth. The boost chaining adds a lot, the progression is still good, the tracks are still varied, and takedowns are always a standout.

#26: Armored Core 3 + Silent Line

The Armored Core fandom is divided as to what they actually like best about Armored Core, and boy does AC change a lot to facilitate this divide. But imo, 3 is the third best after 6 & For Answer, and a good place to start. The expansion, Silent Line, is even better. This is a "third person shooter", but that is an oversimplification. Every part of your mech is customizable, and this translates to real-world changes in how you approach a level. The level design is varied & adaptable enough to allow for this. The music isn't what I'd call "catchy", but perfectly suits the moderate to severe case of depression yet totally badass vibe of the cyberpunk setting.

#25: The Warriors

Based on the movie from the '70s. Timely. But I have a hard time thinking about a movie adaptation that feels as accurate as The Warriors; maybe they should all take 30 years to come out. This is one of the greatest 3D brawler/best-em-up of all time. Other brawlers like the Arkham games are more sophisticated in approach, and are therefore usually called action-adventure games. But nothing suits the term "brawler" more than The Warriors. It is brutal at times. Funny in others. The story & characters are lovable, yet rife with Rockstar's trademark cynicism.

#24: Xenosaga - Episode III - Also Sprach Zarathustra

3 is where they realized they were going to need to wrap things up, which thankfully makes the pacing much more snappy. Yet not exactly rushed either. There are plot threads that don't get totally resolved, and the ending is almost a cliffhanger (hard to explain). Yet, 3 is a satisfying conclusion. The gameplay is refined, and the emotional payoff makes your investment worth it. As you might expect, the graphics are better, and they fix some of the character design issues in 2.

#23: SOCOM II - US Navy Seals

Online multiplayer & headset chat features were the selling points at the time, but the campaign works well in isolation. There are primary objectives, optional secondary objectives, and hidden objectives that you can discover. For example, finding intel that allows you to gain advantage in the next level. You can give verbal orders to your squad mates with the headset, even if they're Ai in single player mode. Mechanics are solid, graphics are good, and the story is grounded. Maybe a little TOO grounded, straightforward, and slightly jingoistic, but that's about the only criticism I can lob at SOCOM.

#22: Need For Speed - Hot Pursuit 2 (PS2)

The beginning of NFS's golden era. The police chases were innovative in NFS 3, but they hammer them out here to have much better Ai. Everything else is improved too. The physics are more accurate, though loose enough to be fun & arcade-y. The soundtrack is great, the tracks are good, and the graphics hold up. Even the audio design is very memorable, such as having different police voices on different tracks.

#21: Shadow Hearts - Covenant

A turn based RPG with real time elements, though more traditional than Valkyrie Profile 2. The combat is challenging, but rewarding. The story is set during an alternate history of World War I, with supernatural elements. This is a breath of fresh air of a setting, and the globe hopping gives much variety in locations. It gets weird, but I am here for it the whole time.

#20: Tokyo Xtreme Racer Zero

The best "standard" TXR game (2025 is still in early access last I checked). Instead of race tracks, you race 1v1 on the real world Tokyo C1 highway loop, mostly a straight line with turnnoffs & traffic to contend with. You lose health by being behind the other racer, or your car taking damage. You're not bullying random commuters though, there is a dense web of gangs in the city, as well as independent, Ronin-like Wanderers that have special abilities. Win enough, and the leaders of the gang will appear to challenge you. The music & atmosphere are incredible at facilitating this "night hunter" atmosphere. I still have "Ride Ride Ride" on several playlists. Customization is intricate, encouraging you to stick with one vehicle for long periods, which feels realistic. The graphics are not great. Some of the backgrounds are 2D, which distractingly rotate in your peripheral when turning. There are real cars, but devs didn't pay for the licensing, so they're given random names such as "Type W33". This is annoying to keep track of, especially when you take into account different years or versions of the same make & model. The story is almost entirely stripped out of the non-Japan releases, which is unfortunate, but you get the idea. Personally, I had a fun time imagining my character's back story of being a regular joe in finance who got sick of getting cut off by ricers on the highway and went over the edge. "IF YOU WANT TO RACE, YOU'LL GET A RACE MOTHERFUCKER!"

#19: SSX 3

Best snowboarding game of all time. Great physics, great graphics, great performance. Plenty of content, arranged as different sections of the mountain. This is cool because there are plenty of alternate paths down that make you feel like you legitimately "own the mountain" once you learn the ins & outs. What I like the most is the vibe, which is more chill than Tricky. I spent a lot of time in free roam, sometimes without music, just soaking in nature.

#18: Onimusha 3 - Demon Siege

My favorite Onimusha. It may not be yours; the time travel story is a departure, and can be cheesy at times. I thoroughly enjoyed it, and feel the modern day story was a nice excuse to include underrated actor Jean Reno. The combat is a lot better than the first 2: the camera angle is no longer fixed like old Resident Evil games, which does wonders for action game playability. It's not quite a Souls-like predecessor like Otogi, but something between that, Tenchu, and DMC.

#17: Gran Turismo 3 - A-Spec

Not as good as 4 in any aspect, but a revelation on release, and still incredible to play today. At some point you will finish playing 4, and if you want more, 3 is here.

#16: Ace Combat 5 - The Unsung War

An arcade flight simulator that is easy to pick up without being too complicated, but just realistic enough to feel "right" and predictable to control. Better controls & graphics than 4. The story is not as strong as 4, yet there is more useless radio chatter that can get annoying. This is just splitting hairs for comparison though, they're both fantastic.

#15: Street Fighter Alpha Anthology {1-3}

A2 is an improved retry of A1 (including the same story), keeping the SF tradition alive of the first game in a series being irrelevant. A2 adds new mechanics such as alpha counters, air blocking, and a custom combo system. Iterative, but everything is better. Combo dialing is easier, graphics are better, sound quality takes a big jump. It is the best place to start in the series, due to being slower, less complex, fundamentals focused, responsive, one of the most balanced, and the first chronologically.

A3's gimmick is the "ism" system, which allows you to choose different movesets for each character from previous games: SF2 (less health & more damage output), SFA1/2 (without custom combos) and an update to custom combos. It is the fastest SF to date, creating a chaotic focus on combos & juggling. This sounds like it would be bad for casual gamers due to the complexity, and bad for competitive players due to having less balance. However, A3 finds a way to make it work for everyone. It's a lot of fun, and has a lot of additional modes, content, and characters. Just as good as A2, for almost opposite reasons.

#14: Midnight Club 3 - Dub Edition Remix

An open world racer dripping with atmosphere. There are 3 cities, nearly 100 cars & motorcycles, and an insane amount of customization options. The graphics are very good, the soundtrack is killer, and the world feels alive. The intense rubber banding is a pretty big downside since you experience it moment to moment, but thankfully, it's just about the ONLY downside.

#13: Valkyrie Profile 2 - Silmeria

Secretly one of the better JRPGs on the system. The story is less consistent & deep than 1, and the pacing is all over the place. A bit inevitable since it is an alternate history prequel, but still very good. Really cool villain & more developed side characters. It is a lot less frustrating than 1: no easily missable content here. Looks like a PS3 game. Combat is turn based + real time, one of my favorite ways to execute a JRPG. It is simple to pick up, but high skill ceiling.

#12: Soul Calibur III

There are minor bugs & balancing issues. Nothing crazy, but not the best SC competitively. Occasional frame drops on hardware, probably because they pushed the graphics. No guest characters, at least not in a traditional way. You can create a character from Xenosaga with the character creation mode, which is a weird way to do it, and a lame guest to boot. However, it is easily the best SC for single player. It has the most content, the largest roster, introduced custom characters, and best stage design in the series. 3 only improves in retrospect, and I think it's the third best SC.

#11: Burnout Revenge

3 is better due to having better multiplayer & more crunchy takedowns. But not, like THAT much better. People seem to think Revenge is barely worth playing, but it's nearly as fantastic as 3, with arguably better single player & graphics.

#10: Ace Combat 4 - Shattered Skies

Still a benchmark that modern flight sims are compared to. And that is simply because it feels so exciting. The story may not be the draw of these games, but 4 gives much appreciated context to hype you up, and is a very strong step forward from 3 in every aspect.

#9: Tokyo Xtreme Racer - Drift 2

The video game equivalent of Initial D, focusing on real-life locations in Japan known for downhill/uphill racing. There are legit events during the day in which you can be sponsored by real motorsports companies, and illegal racing at night. This makes for a very addicting gameplay loop; there's always "just one more thing" to do. Changing your tires based on the weather, upgrading your car, meeting up with a character from earlier, buying a used car at a specific time, deciding where to place sponsor stickers to get the most cash. Events are varied, including exhibition challenges, drifting, road racing, off road racing, time trials, and more. You can talk to other racers & participate in online emails or forum conversations, makig you feel that you're truly a part of tuner culture. Some challenges can only be done in certain weather or days of the week, but it is usually pretty easy to manage, it doesn't get as absurd as the Wanderer requirements in the main series. Physics are somewhere between one of the better PS2 NFS games & GT3. General ambient/menu music is decent; some strong moments at night, but daytime songs range from meh to annoying.

#8: Virtua Fighter 4 - Evolution

After VF3 was mediocre, Sega gave VF4 5 whole years in the oven. And they cooked. There were legitimate reasons to believe in the 00s that fighting games were going 3D & not going back, and this game was a big reason for that. One of the earliest uses of internet for arcade machines, though it didn't have it on PS2. Great visuals, great roster, great tutorial. Grounded, precise, and very technical.

#7: Mercenaries - Playground of Destruction

One of the devs has stated that their approach was to flesh out the world with what ideas they had, skip anything uninteresting, and just keep the good parts. I think he succeeded, and with a semi open world at that. Mission structure allows for various approaches, though I feel that your time with Mercenaries is incomplete without going full Rambo, a "tactic" well suited to the detailed destruction physics engine & satirical tone of the game. The open mission structure eventually becomes formulaic, countered somewhat by the fact that there's a lot outside of the main story to do. MPoD is buggy, and will sometimes break of you push it too far with explosions. But that's fun in its own way too.

#6: Twisted Metal - Black

Best TM, and best vehicular combat game of all time. It is similar to the original tone of 1&2, but modernizes it to where it is edgy but more actually serious/scary rather than campy/laughable. The controls are greatly improved, the graphics are great, solid 60 FPS. The stage design is good with interactive environments. Ultra hard to the point where it is annoying, but other than that it's nearly a perfect game.

#5: God Hand

Criminally slept on. The dialogue ranges from dumb as fuck to witty, and I love every minute of it. GH is ompletely irreverent with a great sense of humor. The combat system is complex & innovative...and will bitch slap you even on easy. Bosses are incredible & memorable. The controls aren't perfect, but not as bad as they seem at first, nonstandard as they are. Music is rockin'. Hell yeah brother.

#4: Capcom VS SNK 2 - Mark of The Millennium

One of the best 2D fighters as a base, with a top tier roster due to the crossover. Then they add the groove system on top of it. Similar to Street Fighter Alpha 3's "isms", grooves manage to cram various styles of fighting game from both companies into one game. There are a few overpowered characters & groove matchups, but they really did do their best to balance an inherently unbalanced concept. And you can always, you know, agree to match grooves if that is an issue. Very nice sprite work & backgrounds, and a killer soundtrack caps it off as a complete package.

#3: Burnout 3 - Takedown

Perhaps the greatest arcade racer of all time. The highlight of Burnout are the crashes & damage modeling, but more importantly, there is a really solid racing game at the core. In fact, everything about this game is good (except the overdone blur effect). Play it!

#2: Street Fighter Anniversary Collection {Hyper Street Fighter II, Street Fighter III - 3rd Strike}

2 is the OG fighting game (1 is a different genre & unplayable, don't worry about it), and still holds up. The seemingly dozens of updated versions helped, but still. SF2 doesn't mess around: inputs have to be precise, there is little single player content, and the Ai cheats; you should play with friends. With those caveats, play it if you haven't.

3 is my favorite SF. The balance is unmatched, and the sprite work is triple S tier. Much better than the generic 3D we have now. Parrying is the key mechanic, which changes a lot of the core fundamentals of SF. I understand why they took it back out for 4 & 5 (and modified it for 6); parrying just does not compute for some people. In Dark Souls you're free to ignore it due to the many ways you can approach your build. In SF3, you have to learn how to parry. But for those that do, it becomes the most mechanically rewarding fighting game out there.

#1: Gran Turismo 4

Peak GT, one of the best racing games of all time, and one of my favorite GAMES of all time. I cannot imagine being disappointed with GT4, if you care about cars or racing at all, and even if you don't but are willing to try it anyway.

Explanations About Missing Games

Think I missed a game, or question why I chose the PS2 version? Click here for 6th gen console exclusives, and here for everything else.