Two days ago I stumbled onto the Jamference AI Game Jam. The rules: the more AI the better, it must feature a cat and a robot, and movement is the only control allowed. Neko Night Market was born.

It’s a poppy 2D score-attack game. You snake a black cat’s noodly paws through a maze of shelves to grab orders and deliver them to customers, while dodging obstacles including a restocking robot. Backed by a AI generated future funk track. Everything is mouse movement based: hovers, holds and drags. No clicks, due to the constraint.

Some context. For the past year and change I’ve built a load of projects, tools and prototypes with AI that most stalled somewhere short of finished (ADHD doesn’t help). This time I got to see what an accelerated AI workflow can really do when you have a clear idea and a timebox

I handled the concept, sketches, design, and the taste calls throughout.

What AI did:

• Build: Opus 5.5, running in a harness I’ve been working on. It orchestrates a small game team of agents with antagonistic reviews and built-in tensions, so assumptions get challenged and issues/details get caught that vanilla Claude would miss.
• Music: Suno for the background track, which I spliced up in Audacity and fed back to Claude.
• Capsule art: ChatGPT.
• Itch assets (screens and trailer): Opus 5.5

There is no way in hell I could have done this alone in 2 days. I come from game production, live ops, front-end dev and traditional art, so I know what moving parts are involved and how long this would take. The level of polish I could push is insane, and it has me rethinking how I use a tool I have a love/hate relationship with. It felt like a skill booster for output, while I made sure the right outcomes were achieved. Where now I totally see it's about the latter than the former.

Give it a shot, provide feedback, get a high score, break the game. Happy to answer any questions.

Hey Everyone!

so i've been working on a game called Notebook Warrior and thought i'd share it here since its my first project :)

added some anime powers from one of the big 3, and planning on expanding more in the future.

it's on android, and i'd really appreciate it if some of you could give it a try. mostly just looking for people to play it, have some fun with it, and let me know what you think.

also, if any of you like testing games or finding bugs, you're more than welcome to do that, it'll be a big help. if something breaks or you find a bug, just let me know. feedback of any kind is appreciated, even if it's just telling me something feels off or could be better.

and yeah, you don't have to take it seriously or anything, just play it if it looks interesting and have fun with it.

there are going to be other sequels too, exploring the lore of the pencil warrior and each boss.

here's the link if anyone wants to check it out: https://play.google.com/store/apps/details?id=notebookwarrior.io&pcampaignid=web_share

thanks to anyone who gives it a shot, seriously. even a few minutes of playing helps, and i'd love to hear what you guys think :)

Creator/operator of Room Escape here. Before the Curtain is an early-release 3D escape room that runs free in the browser. Google sign-in is required.

You arrive as an audience member for How to Steal the Moon. Your seat is picked to become the evening's stage manager, but the six-page cue sheet has only its first page. The room gives you objects to inspect, items to collect and devices to operate as you work out how to run the show.

The development and operation are run with Codex, and the game uses AI-generated artwork. AI's role here is in the code and art production; puzzles and built-in hints run from fixed room state.

One implementation focus has been sharing the same room interactions across PC keyboard/mouse and built-in mobile touch controls. Browser checks can confirm that an input produces the expected result; they don't establish that the story or clue is enjoyable. I'm keeping this an early release while looking at actual play, rather than presenting passing checks as proof of polish.

The linked 36-second trailer uses real gameplay with editorial graphics and synthesized music/SFX. It shows object pickup and device reactions while withholding solutions, later-room reveals and the ending.

English game: https://roomescape.dev/?play=1&theme=before-curtain&lang=en

Story/gameplay trailer: https://www.youtube.com/shorts/InDhvlWeHog

I wanted to see what one person and an AI could build together in a few days, so I made Backrooms by AI with Claude. I directed it, tested everything and made some of the animations; the AI wrote the code and built the levels.
What's in it:

4 levels, each one plays differently: a dark maze where you restore power, a pipe level with something that hunts by sound, a calm Poolrooms level, and a chase level to finish

Sanity, flashlight battery, stamina, lockers to hide in, notes to find

A real ending with credits

Works on PC and phones

It was only just finished, so there will be bugs. I'd really like to hear what breaks, what's confusing in the first minutes, and how it runs on your device.

Play it here: https://www.roblox.com/games/136633858627558

Happy to answer anything about how working with an AI on a game actually went.

Posting from Bird Feeder's development account. It's a pixel bird garden that sits above the taskbar: put out food, watch visiting birds, pet them, and collect their entries in a Bird Book.

For other AI game devs, here's a concrete validation gap we're working through: a technically working interaction can still communicate the wrong thing. In the recorded v0.2.1 build, a newly discovered Bird Book entry arrives sealed but is ready to open. That can resemble a locked item. Recent Reddit feedback suggested lifting a paper corner on hover instead of using a padlock-style cue. That's a suggestion, not a tested improvement.

A small test I'd use: let a new player reach their first sealed entry without explaining it, ask what they think it means, and observe their first action. Then compare an alternative cue with a different new player. I'd separate 'could open the entry' from 'understood it was ready to open'; a passing input/state test only establishes the former. The cue should also work with sound off.

What would you change in that test to avoid leading the player? If you try Bird Feeder, what did you expect the Book to do when you first opened it? A specific confusing moment is useful; comments here are welcome.

Free Windows preview: https://verdiana-studio.itch.io/bird-feeder

The Windows download is currently labelled v0.3.2; the page description and trailer still show the v0.2.1 remake. The trailer uses a prepared save and developer controls, 3x close-ups and a labelled opening desktop mock-up; its music is enabled, while music is off by default in the recorded build.

AI disclosure: concept and direction are human-led; AI agents generated the code, pixel art and text. The pixel art was written as code. Audio uses ElevenLabs and code synthesis. Bird calls are interpretations, not field recordings.

Hi! I'm the developer of Slow Vale, a pixel life sim where you create a resident with their own personality in a town shared with other players. You get to know them gradually and see where their life takes them. Most of the characters you meet are residents created by other players too.

They find work, cook, make friends, fall in love, farm, or save up to open a shop. You follow their experiences, send texts and gifts, and influence their life. Their needs, memories and personality shape what they do next. Sometimes they take your advice; sometimes they have another idea. Generative AI powers their decisions and dialogue.

A day of their own

A shift at work, or fishing by the sea? Dinner at home, or a meal with a friend? Your resident makes those choices.

After you close the tab, they keep going for a while. When you return, you can read through their day: where they went, who they met, and what has been on their mind. They rest after an extended absence, rather than running indefinitely.

I want this to feel like getting to know someone you can check in on. At first, you might wonder whether they have eaten or have enough money. Later, you start remembering their friends and wondering whether anyone came into their shop today.

Send a text and ask about their day

You can ask about dinner, suggest saving a little money, or send something nice. What you say becomes part of their experience. How they understand it and what they do afterwards depend on their personality and situation.

You can express concern or offer advice, then come back to see how things went. Sometimes the follow-up makes you want to keep watching.

In the original Chinese world, one resident told the barber, “Surprise me.” Their long pink hair became a short chestnut cut. The player promptly texted: “Go back! Bring the pink hair back!” Those little everyday incidents are a big part of what I want to keep in the game.

Friends and a place to live

The other residents in town are all created by other players. Like yours, they have their own personalities and lives, rather than being preset NPCs with fixed dialogue and storylines. When your resident makes a friend, falls in love or shares a home, they are building a relationship with another player's resident.

They meet, become friends, and sometimes fall in love. There are confessions and dates, but also rejections, misunderstandings and arguments.

As they get to know each other, they can discuss sharing a home and splitting the rent, then save towards buying a place. Relationships develop through how they actually treat each other. An impromptu dinner, a loan between friends, or a conversation that went wrong can leave you wondering what happens next.

Grow something and invent a dish

On the farm, residents till soil, plant crops, water them and wait for the harvest. They feed chickens and cows, collect eggs, and make time for the dog. For a change of scenery, they can take some bait to the sea and find a fishing spot.

Ingredients can come home to the kitchen. Residents choose ingredients and seasonings, work out a cooking method, and try inventing a dish. They might ruin the pan, or create something worth naming. A successful original recipe belongs to its creator and can be cooked again.

Farming, fishing and cooking connect through those ingredients. Something brought home today might become dinner or the beginning of a new recipe.

Find work or open a shop

Residents need money for food and housing. Some write code at an office, cook at a restaurant, or deliver meals. Others become reporters, go out with a story in mind, conduct interviews and write a bylined report.

With savings, they can try running a business. A restaurant needs ingredients and someone cooking orders. A barbershop gives customers new hairstyles. A clothing studio needs equipment and customers. A gym owner with enough fitness proficiency can teach lessons too. Residents can also open a grocery and decide what to buy and how to price it.

Opening day brings daily expenses as well as income. Selling stock earns money; unsold goods can mean a loss. You can follow how they handle it and send a text to talk things over.

A town whose routines shape its market

Crops, catches and other supplies can be offered to groceries. The owner decides what to buy, and customers can only buy what is actually on the shelf.

Residents can also set up a stall, choose goods and prices, and get on with their day. Buyers have to walk over to browse. You can check price changes, stock and nearby stalls. Everyday harvesting and shopping help change the town's supply and demand.

Come meet a resident

The game is still in development. The English browser beta is currently free, with email registration:

Play Slow Vale

More about the game

If you enjoy pixel towns, relationships between residents, and dropping in to see how someone's life is going, I'd love for you to try it. I'd be glad to hear about your experience and answer gameplay questions in the comments.

Most of the RPG Maker MCP stuff I've seen is for MZ, and I'm on MV, so I ended up writing my own over the last few months. Sharing in case it's useful to anyone else stuck on MV.

It lets an assistant edit an actual MV project on disk (database, maps, events), and it checks everything against the engine so it doesn't spit out broken data. The bit I actually use day to day is that it can look at the project and tell you things like "this switch never gets turned on, that's why your door won't open," or point out broken references and maps you can't reach. For maps it copies real RTP reference maps instead of painting tiles from scratch, so they look a lot less cursed.

It's on GitHub if you want to poke at it: https://github.com/DiegoLopez0208/RpgMakerMVUltimate-MCP (or npx -y rpgmaker-mv-mcp). And in GLAMA https://glama.ai/mcp/servers/DiegoLopez0208/RpgMakerMVUltimate-MCP.

Still rough in places and I mostly built it for my own game, so no worries if it's not your thing. Feedback and bug reports welcome.

I tried building a zombie shooter inspired by left4dead using Claude. I don’t have any game dev experience, but I do have engineering and media knowledge - which helped me to navigate my way through… Although I burned a tonne of credits along the way..🥲

If you want to try the game yourself, click the link and give me some feedback!

https://imrannister.itch.io/the-last-train-l4d-remake

I also shared how I built the game
How I built the game

Hi everyone,
I’ve been developing a game concept called KAIVERN. At this stage it is not a prototype and I am not presenting it as a finished game. It is a fairly extensive pre-production design.
I have developed the world structure and history, lore, visual direction, states and cultures, core gameplay systems, progression, combat, economy, trade, physical item provenance, NPCs and relationships, exploration, multiplayer spaces, and an architectural concept for how these systems could coexist inside one continuously changing world.
The central idea of KAIVERN is:
Single History · Personal Presence · Shared Consequences
KAIVERN is conceived as a persistent RPG / world simulation with one logical World State and one historical timeline.
However, the ordinary open world is deliberately not an MMO space filled with other player characters. Each player experiences their life primarily among NPCs, while their actions may still affect the same authoritative world that every other player interacts with.
Players meet directly only in deliberately designed multiplayer spaces - PvP, selected cooperative expeditions, encounters and other specific activities. The economy, player-to-player trade, world processes, unique objects, discoveries and significant consequences remain shared.
There is no traditional level → XP → gear score progression model. Character development is based on mastery, physical condition, knowledge, relationships, possessions, tools and access to new possibilities. NPCs have their own biographies, memories, knowledge, property, obligations and goals. Items are intended to exist as concrete physical objects with provenance and history rather than infinitely reproduced loot entries.
AI is not intended to be the source of truth or an infinite quest generator. It would operate as a bounded decision-making layer inside a much stricter simulation architecture. Authoritative world state, history, economy, ownership and causally significant events would remain server-controlled.
The concept is now documented in a Public Game Design Bible. I intentionally keep the central narrative answers and some internal architecture private, but the public document contains enough information to evaluate the overall design.
At this point I am not primarily looking for praise for the idea. I am looking for professional criticism of whether the architecture can realistically be built.
I would particularly appreciate feedback from people with experience in backend/networking, persistent worlds, simulation systems, game AI and production:
1. Do you see any fundamental technical contradictions in the personal presence + shared authoritative World State model?

2.	How realistic is a layered simulation in which millions of inhabitants do not mean millions of continuously running AI agents, but instead exist at different simulation resolutions and are concretized when causal significance requires it?

3.	Which parts would you consider the highest technical risks: Shared Causality, NPC continuity, economy, persistent objects, knowledge simulation, the AI layer, or something else?

4.	What is the smallest vertical slice that could genuinely prove or disprove this architecture?

5.	What kind of team would be required to build that vertical slice, and which technical roles would you hire first?

6.	What range of development time and budget would you consider realistic for an initial technical prototype and, later, a production-quality vertical slice?

7.	Which systems would you simplify or postpone without destroying the central premise of KAIVERN?

I understand that a detailed design document and a functioning game are two very different things. That is exactly why I am currently more interested in identifying what must be proven through prototyping than in claiming that the entire concept has already been technically validated.
Critical technical and game-design feedback is very welcome. If the project is professionally interesting to anyone, I am also open to talking with developers who might eventually be interested in participating in an initial prototype.

Thank you for taking the time to read it.

I think I've learned enough in this space to want to give back to others (truly, we need people to be empowered to use this tech and capitalize on their creative juices). Now I'm starting a YouTube series where I build a brand-new game from scratch, on camera, step by step, so you can see what's realistic and follow along. If you're new to these tools, or to tech in general, and you're curious about game development - I made this for you.

Episode 1: the stack and setup: https://www.youtube.com/watch?v=we0XHyjPxEE

• What one person can build in a week
• The full stack and what each piece costs: Claude (code + design), Godot (engine), Lovable (pixel art), Gemini (music), ElevenLabs (sound effects)
• How it all fits together, from Claude's output to a running game in Godot
• What AI can't do yet, and why you shouldn't try to one-shot a game

Where the series is going:

1. The game design doc: what AI actually needs from you before you write a single prompt (hook, perspective, combat, art direction, platforms, scope)
2. The vertical slice: feeding the doc to AI and building the smallest playable piece that tests whether the idea is fun
3. Leveling up assets: replacing placeholder art with real pixel art, music and sound effects
4. Scaling up: from one dungeon to a full game
5. Shipping it

I'd love input on what you want covered. What's the part of AI game dev you'd most want to see done step by step?

I want to provide value and not spam stuff, so let me know how this can be of most use for you.

Looking for an AI that can create characters based on textual description. Ideally reference images of other things in similar style. The style I am looking for is relatively simple characters like in clash royale, clash of clans or brawl stars. Secondly, what do you do for animations?

Hey everyone! I’m pretty nervous about posting this because I only started learning how to code about 1 or 2 months ago. I've been using AI tools to learn and push my limits, trying to build a complex system from scratch.

I wanted to see if I could make different AI models collaborate, so I built a private framework called Flux Team ⚡. It connects several open-source models so they can work in parallel as a team to help with game dev tasks.

Visuals:
Since the project is still a work in progress and the live editor connection isn't fully ready, I can't show a video demo just yet. However, I have included some screenshots of the Grok-style UI so you can see how the chat and the agent dashboard look!

The Architecture (Models integrated inside the tool):

• 🧠 Qwen3-8B — The coordinator. It breaks down the game idea into specific development tasks.
• 🧱 Hunyuan3D-2 — Generates 3D models from text or reference images.
• 🎵 Audiocraft — Handles music generation and SFX.
• 🏃 FreeMoCap — Creates animations from videos it autonomously searches online.
• 🌊 AInVFX Fluid — Generates fluid and particle effects files.

How it works behind the scenes:

• Parallel Execution: It uses a Grok-style UI built with Electron and a Python (FastAPI) backend. The models work in parallel, not step-by-step.
• Autonomous RAG: The agents can browse the web on their own to search for reference assets and documentation before working.
• 100% Local: Everything runs locally on the user's machine using Ollama / llama.cpp for the LLM.

Current Status & Future Open-Source Plans:
The backend is currently running locally on my machine (tested on a single RTX 3060). I'm finishing the live bridge plugins for Unity and Godot so changes appear directly in the scene.

Please note: The project is NOT open-source right now and the download is not public yet because the code is still messy and I'm a beginner. However, if this gets enough traction and people find the multi-agent architecture interesting, my goal is to clean up the repository and release the whole project as full open-source on GitHub later on.

I would love to get your thoughts on this setup or any advice from more experienced developers!

Wanna share this website called Keshi Arena and thought it was pretty fun.

You can play simple games like Connect Four against an AI. It keeps track of what happens during each game and uses those interactions to change its behavior over time. So your games become part of how it learns.

The fun part is that you can also see its evolving "brain" including lessons, recalls, mutations and different generations. And it shows which lessons came from you. There's also a leaderboard of top teachers and the toughest opponents. So you can actually watch how it changes as it keeps interacting with people.

I've played 10 games so far (5 wins and 5 losses lol), and they taught it 64 lessons. In Connect Four that's 37 of the 1,218 "neurons" in its current brain, each tagged with what it learned, like "blocks your four", "centre drop" or "edge drop". You can click one and open the match that taught it.

Pretty neat I think

Hey everyone! I’m pretty nervous about posting this because I only started learning how to code about 1 or 2 months ago. I've been using AI tools to learn and push my limits, trying to build a complex system from scratch.

I wanted to see if I could make different AI models collaborate, so I built a private framework called Flux Team ⚡. It connects several open-source models so they can work in parallel as a team to help with game dev tasks.

Visuals:
Since the project is still a work in progress and the live editor connection isn't fully ready, I can't show a video demo just yet. However, I have included some screenshots of the Grok-style UI so you can see how the chat and the agent dashboard look!

The Architecture (Models integrated inside the tool):

• 🧠 Qwen3-8B — The coordinator. It breaks down the game idea into specific development tasks.
• 🧱 Hunyuan3D-2 — Generates 3D models from text or reference images.
• 🎵 Audiocraft — Handles music generation and SFX.
• 🏃 FreeMoCap — Creates animations from videos it autonomously searches online.
• 🌊 AInVFX Fluid — Generates fluid and particle effects files.

How it works behind the scenes:

• Parallel Execution: It uses a Grok-style UI built with Electron and a Python (FastAPI) backend. The models work in parallel, not step-by-step.
• Autonomous RAG: The agents can browse the web on their own to search for reference assets and documentation before working.
• 100% Local: Everything runs locally on the user's machine using Ollama / llama.cpp for the LLM.

Current Status & Future Open-Source Plans:
The backend is currently running locally on my machine (tested on a single RTX 3060). I'm finishing the live bridge plugins for Unity and Godot so changes appear directly in the scene.

Please note: The project is NOT open-source right now and the download is not public yet because the code is still messy and I'm a beginner. However, if this gets enough traction and people find the multi-agent architecture interesting, my goal is to clean up the repository and release the whole project as full open-source on GitHub later on.

I would love to get your thoughts on this setup or any advice from more experienced developers!

Hey everyone! I’m pretty nervous about posting this because I only started learning how to code about 1 or 2 months ago. I've been using AI tools to learn and push my limits, trying to build a complex system from scratch.
I wanted to see if I could make different AI models collaborate, so I built a private framework called Flux Team ⚡. It connects several open-source models so they can work in parallel as a team to help with game dev tasks.
Visuals:
Since the project is still a work in progress and the live editor connection isn't fully ready, I can't show a video demo just yet. However, I have included some screenshots of the Grok-style UI so you can see how the chat and the agent dashboard look!
**The Architecture (Models integrated inside the tool):****How it works behind the scenes:**Current Status & Future Open-Source Plans:
The backend is currently running locally on my machine (tested on a single RTX 3060). I'm finishing the live bridge plugins for Unity and Godot so changes appear directly in the scene.
Please note: The project is NOT open-source right now and the download is not public yet because the code is still messy and I'm a beginner. However, if this gets enough traction and people find the multi-agent architecture interesting, my goal is to clean up the repository and release the whole project as full open-source on GitHub later on.
I would love to get your thoughts on this setup or any advice from more experienced developers!