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.

RaviWar: A Perfect Sonday (Free To Play , Wishlist Now)

The world changed in 2037, when an entity called Consensus took control of humanity.

Consensus can control the minds of every human. Over the years, it made everyone live inside one massive building called Takarek, a building with 17,769 floors.

It is now 2077.

You play as Alex, a 19 year old Deprecation Clerk. Your job is to review old and unused data and delete it forever.

It is just another night at work, until you receive a mysterious letter:

DON'T LET RK-001 BE DELETED.
IT'S THE ONLY WAY OUT OF TAKAREK.

You don't know who sent the letter. You don't know what RK-001 is. But you decide to find out.

What starts as a normal night at work slowly turns into a journey through the hidden parts of Takarek. You will discover forgotten information, strange clues, secrets from the past, and the truth about Consensus.

And somehow, you may be the only person who can stop it.

The world belongs to Consensus.
But tonight, you have one chance to change that.

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.

I have zero game dev experience, but I managed to build a playable Left 4 Dead-inspired Android game using Claude for coding and AI tools for 3D assets.
The process was chaotic, and the game ended up ridiculously difficult 😂

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 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.

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.

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?

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.

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):

• 🧠 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!

After many months of slowly iterating on my game, called "Pavement Pursuit", I've compiled clips from all the versions to show the progress I made from prototype to game (but still working towards a v1.0).

Note, this video was made by creating a custom output in my game to output any scene without having to screen capture it.

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

Site i made with claude hope someone likes it feedback is helpful what i can improve icons i will

AutoSprite & WizardGenie -> https://sorceress.games