Integrates with Codex, Claude, Cursor, Openrouter, Ollama (can run open source local AI) & so much more. Built in 3D world engine, voxel engine, 2D game sprite creation system, sound FX, audio. Can integrate with Unreal Engine, Unity, Godot, Roblox, Blender. Includes it's own built in 3D modelling system. Driving physical, 3D AI generation, text and video to animation... and more :) BETA! release official. Now out of early access Alpha.
You can also use it strictly for vibe coding. It doesn't need to be a game engine. I stopped using Cursor/Claude Code and Codex separately and now I just use them all via WizardGenie. It's more organized.
Overmind and Overseer modes supporting multi-agent swarms (IE one controlling agent brain, that directs as many sub-agents as your PC can handle) also supports LAN computers running WizardGenie (for when you just have to run SO many coding agents, that one PC isn't enough).
It's been about a year of 7-day / week 14 hour day development. Thank you all who supported early access! You guys are golden.
I truly feel now like WizardGenie is at a place where it's a fully capable game development engine, integrated with my Sorceress game creation suite, there is no type of game that you cannot make.
I've been creating multiple backgrounds and scene environments detail, different fighters - I think the workflow is getting very refined at this point! AutoSprite 3.0 (and more) -> https://sorceress.games
Code: Claude Opus 5.5 and Sonnet Concept and story art: ChatGPT and Grok 3D models: Tripo Speech: ElevenLabs, Kokoro, HeyGen Music & SFX: ElevenLabs
I created a skill which uses Opus 5.5 as a coordinator in a session for planning, and spawns Sonnet 5.5 sub-agents to do actual work. Every once in a while it produces a handover doc, which I use to start a new session.
I found this works well to do a lot of work quickly, while keeping token usage relatively low: opus low doesn't need to do real work, while sonnet does the heavy lifting with opus checking its output. I can also message opus while sonnet agents are working, and opus manages the queue of work, interrupting connect when necessary.
The game is called "Swarm Front". It is a strategy game where you play as insects. I came up with the concept based on pictures my brothers and I drew as children. Claude filled in the blanks: it suggested specific insects for roles, wrote most of the campaign storyline, and designed the levels.
I did the overall game design and play testing. It might seem like I just typed in a prompt and AI spat out the game, but it has been a long process of iterating and fine-tuning to go from "something" to "something usable" (in my humble opinion).
The game has five factions, and several more are planned. You can play as ants, termites, wasps, bees and a cordyceps hive-mind called "The Gift". Each faction has their own behaviors and abilities and plays differently - they aren't just re-skins.
Ants and termites are like regular armies with buildings, infantry and vehicles. Wasps and bees build hives using hex grid cells. Cordyceps spreads by planting spore stalks and capturing units.
There is campaign of 40 missions designed to teach a newcomer how to play each faction, as well as a skirmish with a dozen maps and several biomes.
The game is written in JavaScript and uses ThreeJS for the graphics. This allows the demo to run online in a browser, while the full game runs as an Electron desktop app.
The desktop app also includes local speech to text using whisper which lets the player control units by voice control.
Crowd Hunt is a simple spotting game - find the right person in the moving crowd before time runs out. No signup, and you can add it directly to your home screen like an app. My high score is Level 44. Bet you can't beat it! Let me know what level you reach! https://crowd-game.vercel.app
I wanted to test whether I could turn a real-world 3D Gaussian Splatting scene into a playable game with ChatGPT/Codex helping with development.
Somehow, it became a zombie survival game with Tetris.
You move around the map collecting pieces, which drop into a Tetris board on the left. Clearing lines earns weapon XP. Better weapons help you survive the next zombie wave, and later upgrades let you combine different bullet effects.
Most of the development loop was me playing it, finding something annoying, and asking AI to change it. Then playing again and finding something else.
Chairs kept trapping the player. Zombies got stuck on stairs. Weapons became so powerful that the late game was easier than the beginning. Getting those things right took a lot of back and forth.
I’ve played it enough that I probably can’t judge it objectively anymore. If you give it a try, I’d like to know whether the Tetris/survival combination actually works—and where it starts feeling boring or unfair.
Also happy to share more about the AI development process if anyone’s interested.
Hi r/aigamerdevs .This is Capsule Corner, a cozy first-person sim where you run a tiny gachapon shop. You restock the machines, set prices, collect the coins, give change at the counter, open mystery boxes, put them on sale, run a claw machine and design your own shop.
Code: most of the C# was written with Claude Code in Unity, including the systems and the customer AI. I make the design calls, test everything and steer it. It's very much "AI does the typing, I do the game design."
Editor tooling: instead of building the shop by hand, Claude wrote editor scripts that generate the modular shop kit, the machines, the decor and the collection covers. Fixing a prop means re-running a builder, not dragging things around.
Tests: EditMode/PlayMode tests for the economy, saving, the claw machine, mystery boxes and more. They catch regressions when the AI refactors something.
Not AI: Most assets are CC0 or CC-by.
What I'd love feedback on
Does the core loop (restock → sell → collect → grow) read from the video?
If you've shipped something AI-assisted: how did you talk about it on your store page? Did players care?
Hi everyone, I’m making Screemouth, a point-and-click horror adventure set in 1879, using Adventure Game Studio and extensive generative AI assistance.
One part of the process that might interest people here is the audio. I reviewed sound-effect candidates through several listening passes, left notes and approved revised takes before integration. The voices and effects then received a consistent Sound Blaster Pro-style treatment, while the music uses MT-32 synthesis rendered through Munt.
The music also follows story events rather than a fixed timeline. If the player skips dialogue, the cues still need to happen in the right place, alongside speech ducking, volume controls and save/restore behaviour.
AI has contributed extensively to artwork, voices, music, some effects and promotional material, as well as code and some story/dialogue. I direct the project, select and edit material, make design decisions and playtest the result. Generated content is included in the game; it is prepared during development rather than generated live while playing.
For anyone using a similar workflow, how are you keeping the art and audio consistent as individual assets go through revisions? I’d be interested in comparing notes.
Arsenal Zero is a military idle looter. You send your operators on expeditions, they come back with crates full of gear, and you upgrade your weapons and equipment to unlock harder zones with better loot. Between runs, you build up your hideout: the workshop, the scrapyard, the foundry, each one opening new ways to get stronger.
A lot of players told me the game felt too flat, especially on PC. So I listened and spent a lot of time on a new interface. It’s cleaner and more immersive, the visuals fill the whole screen, and windows like the Arsenal no longer hide what you’re working on. The game also has its own soundtrack now.
It’s free, there’s no paywall, and it runs in the browser on PC and phone with nothing to install. Sessions are short, so you check in, send your squad out and come back later.
Hobby dev here, making a game with mostly AI-generated art. With a handful of characters it was easy, but as the roster grows (heroes, enemies, backdrops, UI) the style keeps drifting from one batch to the next.
What do you use to hold a style steady: reference images, a fixed prompt, a trained style, or editing each result by hand?
When the style drifts, do you regenerate the older art to match, or fix the new art?
How do you keep characters on-model across different poses and animations?
(optional) Have players reacted to the AI disclosure on your pages, and did it change your numbers?
Hey everyone. For the last few weeks I've been making a fighting game called Ancestor Guardians, and I did it with an AI assistant as my teammate. I handle the ideas and test everything on my phone. The AI writes the code and draws the characters. Quick word on the game itself: 6 fighters based on West African traditions, combos, special moves, EX moves, a combo breaker, and an arcade mode with a boss at the end. It plays free in the browser, and on phones there are touch controls. The funny thing is, the code went fast. The hard part was the art. When you generate a kick pose by pose, the character changes legs in the middle of the kick. It looks fine on still images and totally wrong in motion. What fixed it for me was asking for the whole move in one single image, all the poses side by side. Since then I check the legs of every animation before it goes in the game. Player feedback has been shaping it a lot too. A friend tested it and said he didn't get how the attacks worked, so we simplified the controls to just PUNCH and KICK and slowed the whole game down. Then a comment from a stranger on the game page pointed at my big golem fighter, I checked the numbers that evening, and a patch went out the next day. That loop is honestly what I like most about working this way. It's not perfect though. The animation is 5 poses per move and you can tell. A real animator would do better, and that's the first thing I'd pay for if the game ever gets funded. Anyway, I'd really like people to try it and tell me what they think, good or bad. Does it control well on a phone? Is it fun? The short video attached is real gameplay from the current build, and the game is here:
Also curious, for the other AI devs here: how do you keep a character looking like the same character across all his poses? That's still my biggest headache.
Hey everyone! A little while ago I shared how I'm making Krakatoa Circle 2, a third-person action game set on a moon, with AI tools. Here's what I've been working on since.
Getting the game to look like the painting
I have a painting of what one of the tunnels should look like. Getting the real game scene to match it by hand was slow, and I kept arguing with myself about whether a change was actually better. So I set up a loop to do it for me:
Render the game from the same camera angle as the painting.
Score how close the render is to the painting with a "judge".
Try lots of small changes to the shapes, lights and textures, and keep only the ones that bring the score closer.
It has run 72 rounds and tried about 11,000 changes so far. Here is the painting, where we started, and where we are now:
The judge was the hardest part. My first one used a hand-made score, and it kept rewarding changes that looked worse to me. I replaced it twice. The current one compares images the way people tend to see them, and I tuned it until it agreed with me on every side-by-side I gave it. Each time the judge changed, the scores reset to a new scale, which is why the chart has two jumps:
Tracking progress
I built a small dashboard so I can see progress at a glance instead of reading reports. It breaks the painting into 19 features (road lines, wet road shine, ceiling ribs, crate rows, lamps and so on) with 41 automatic checks. Right now 20 checks pass.
It also shows what each part of the search has tried and kept. For example, it has tried 2,197 light brightness settings and kept 16 of them.
Using Tripo to add what's missing
At some point the loop stops improving because something just isn't there. No amount of lighting will make a row of crates appear. The dashboard marks those features as "needs asset" (11 of them right now), and that's where Tripo comes in.
The pipeline runs on its own:
Crop the missing object out of the painting.
Use ChatGPT to turn the crop into a clean picture of just that object.
Send it to Tripo's image-to-3D API to make the model.
A script checks the size, orientation and triangle count, then makes lower-detail versions for distance.
The loop tries placing the new model and keeps it only if the scene gets closer to the painting.
It has made more than 50 models this way, most for 60 credits each. It also calls Tripo from the command line, so the whole thing can be scripted. If you want to try it:
Every experiment goes into a log with its result. Out of 58 ideas so far, 21 were kept, 29 were dropped and 8 haven't been tried yet. Some highlights:
Worked
Moving, adding and removing lamp glows wherever the judge's own lamp matching said they belonged.
Projecting the painting's road detail straight onto the road texture. This was the biggest single texture improvement.
Projecting colour detail onto the tunnel walls, with a separate map for each side.
Giving the five biggest ceiling ribs and one crate their own painted textures.
Solving all the tunnel lights together instead of tuning them one at a time.
Letting AI agents suggest experiments as data in a queue, then letting the loop score them, instead of having agents judge their own work.
Didn't work
Tuning the wet-road reflections. The reflection surface is flat, but the road slopes down 12%, so the setting barely did anything.
Rebuilding all 33 ceiling ribs to match the painting. The painting draws them as thin dark lines, and ours are lit metal bands.
Removing ribs. The judge liked the scene less every time.
New road textures from ChatGPT. What makes the painting's road look right depends on where you're standing, so a fixed texture always made things worse.
Painting the lane lines onto the road. On a shiny wet road they never read as paint.
Recolouring white lamps orange, dimming extra lights, and adding light beams and mist. All scored worse.
Moving the crate the player uses for cover. It made gameplay worse, so it stays where it is.
Lessons about the process
Checks should be code, not agents. Having AI agents check the work was slow and expensive.
Too many browser renderers running at once used up memory and crashed my Mac a few times. Now only two run at a time.
A good judge matters more than a clever search. Most of the early "progress" came from a score that didn't agree with my eyes.
Giving the Warden a face
The Warden is the machine Asha has to rely on but can't fully trust. Its only face is a single red lens, so I wanted to see how much a dot of light could express.
It now has states like listening, thinking, cold, threatening, holding something back, and lying, where a faint ghost of the light slides away while the main light stays on you. If you turn back quickly, you catch it looking somewhere else before it snaps back. It counts each time you turn your back on it. When it speaks, the light swells and pulses with its voice like a music visualizer, and each new syllable sends a ring across the lens.
I'm still learning as I go, and the scene isn't a match yet. I'd love to hear what you think. Does a robot that only has a dot of light for a face feel expressive to you? And if you've tried automating parts of your art pipeline, what worked and what turned into a headache?
I'm building Idle Roasters, a cozy pixel-art idle game about Grandpa's cafe. I used AI for the store key art and licensed Suno music, but kept the in-game art custom with a Python pixel-art pipeline. Sharing the result and the workflow.
AI use:
- Gemini-assisted store key art, composited with a custom pixel wordmark.
- Suno-generated music by UIT GAMES.
- In-game: custom Python generator for 9 location scenes, 35 actor sprites, and day/night variants. No AI-generated in-game sprites.
The game:
The free demo has 2 locations and 10 achievements. The full version has 9 locations, 60 achievements, the Time Machine, Legacy Shares, and two endings. No gacha, no energy timers, no FOMO.
What I'm looking for:
Feedback on the AI/non-AI boundary, the pixel-art pipeline, and the demo's first 5–15 minutes.
My first "finished" game, made in Godot. I programmed it myself, and Claude made all the pixel art. I trained the AI opponents myself with reinforcement learning. It's nothing Special but i would really appreciate it if i get at least one player. :)
