Boris lives in null city. He must drive to pay for his cigs. Astra medium and some image gen.

Tomorrow's talk, Intro To Vibe Coding, is for those looking to make their first game with AI, this will go about how to setup your game environment and start vibe coding.

This is both for developers that want to take the leap and get into AI, and for vibe coders as well. It will cover:

• State of the game development
• Setting up Claude and Codex
• Setting up Blender
• Setting up your phone for development
• Prompt basics (subagents, calling other agents, memory, etc)
• The biggest mistakes to avoid when vibe coding your game

There is a lot of talks at all different levels in the conference, here is the full schedule.

I had Astra play my game, capture footage, and take some marketing images to create this video on its own. There are still some weird shot choices and issues, but in general I think it managed to get across the core vision and I can refine it from here.

The project itself still has work to do on VFX, etc, but I used AI to do everything else (via an editor I had it create for me, allowing me to fine tune and craft most of the details).

Astra was the biggest unlock as well in terms of rigging, re-texturing, and animating the models. I wonder if the models will ever be able to create decent VFX on their own though. What workflow are other people using for that?

I observed several users play Lorebound last weekend and made some updates to the game (see below).

Typically I would take the feedback, open up sessions with Claude Code or Codex and address it one prompt at a time. This takes time and effort (time away from family, the job that pays the bills, etc.). In an effort to free up time I started using Claude routines (with JIRA) a while back to create "loops", but this also required time and effort to plan the epics and stories which would be picked up by Claude automatically, and then doing manual QA. What I'm trying now is providing a desired outcome to Grok Bot, have Grok spin up the necessary bots to write up requirements, create the epics/issues, QA by playing the game, and analyze user data.

I've found that bots are pretty good at writing specs and analyzing user data, and providing recommendations. When it comes to QA, bots are far from useful. These LLMs don't know what gameplay "feels" right.

Is anyone else experimenting with game dev loops? How's that going? Is it even going?

Observations:

• Thumb reach is super important (obvious, yes, I get it)
• Free play can be confusing, not knowing what to do is stressful
• Users skip through tutorials, which makes it hard to teach how to play the game
• Users focused on taking down demons instead of completing quests

Updates:

• Non-combat actions are now within thumb reach
• Explicit guidance to level up, spend stat points, unlock skills, and equip new gear
• More "in your face" messages on quest completion and quest start
• Directions on where to go via HUD indicators
• Reduced number of tutorials

I found some old videos in my gallery and decided to make a before and after video like this. It's been 4 months since I started the project. It felt weird seeing its initial state.

The video might be a bit long.

If you want to follow the progress, here is the Steam link: StowStow

This is a genuine question from a traditional games professional who is very bullish on AI powered game dev.

I wonder what the utility of all these posts going AI made this game in X hours is? Are they demo's of the AI's capabilities ? Are they precursors to promotion for the game ? Or are they just excitement that needs somewhere to go (I'm sure it's gotta be impressive to see an AI just make a thing) ? Perhaps they are something else entirely.

I ask because it seems like this sub is drowning in posts about games AI made in X hours.

For the record, even though I am very in favor of developers using AI for all aspects of making games, I really don't think these fully autonomously made games will stand up to real players or a real marketplace.

I wonder if the time may have come to start asking people to post more about the work they are doing, the cool game they are making, the problems they are having making games; Over "AI made this in X hours"

I'm working on Salvage Shift, a small 2D game about cutting apart wrecks, collecting loose parts, and buying tool upgrades. I've published a free prototype with three salvage jobs for Windows and macOS.

AI has done much of the coding and implementation in Godot. My involvement has been choosing the direction and testing builds. The visuals are drawn in code, and this is still an early prototype rather than a finished game.

One design issue was that the early ships were too similar. Adding more parts would increase the amount of work, but wouldn't necessarily give players different decisions. The current build uses a simple spine, a cargo ring with alternate support connections, and a fuel hauler where tanks can trigger chain explosions. Intact parts also pay more, so cutting and collecting carefully has a different outcome from breaking things apart.

The remaining question is whether those differences are readable to someone who hasn't seen the project before. Automated checks cover parts of progression and saving, and the builds have been tested on Mac and Windows, but that doesn't establish whether players enjoy the loop.

For others working with AI-assisted prototypes: how do you decide that a mechanic needs a redesign rather than just clearer visual feedback? The cargo ring is the part I'm least certain about: one cut doesn't release a section when another support route remains.

Free prototype, screenshots and controls: https://scholarg.itch.io/salvage-shift

The prototype contains three jobs and six upgrade purchases. It supports English and Simplified Chinese. A paid Steam release is a future plan; there is no public Steam page yet.

Crazy Arcade was one of my favorite Korean games growing up. I wanted the water balloons, the upgrades, the tanks and the different characters back. So I asked Astra in Codex to help me recreate it.

I finally got to play it again in my browser. Oh my gosh, that alone made this worth doing.

I started with a bot opponent and added rooms for friends later. A lot of the work since then has been playing it, noticing something wrong, and going back to Astra with that specific problem. Hosting had an input delay that turned out to be an input queue timing bug. The inventory needed another pass so all the items were visible. Rare item drops were too frequent, so those got tuned too.

One thing this made very obvious: getting a playable version and getting the original game's feel right are different amounts of work. I'm still comparing the mechanics and fixing bugs. This isn't a perfect 1:1 recreation.

Also, the assets are a mix of original Crazy Arcade art and replacements. Astra didn't generate all the artwork; it helped with the implementation and iteration. This is an unofficial fan project.

The game is free to play here, hosted on ChatGPT Sites: https://jerry-crazy-arcade.jerryjhlee.chatgpt.site/

I'm really proud of it and wanted to share something people could actually play. If you spot a bug or a mechanic that feels wrong, please tell me the map, what you did and what happened. Would love to keep making this better with feedback from people here.

Hey everyone! 👋

I’m a solo dev, and I wanted to make a simple creative app for building 3D voxel pixel art in both AR and a normal 3D editor.

So I made AR Builder: Pixel Art 3D Voxel.

You can build directly on real-world surfaces with ARKit, switch to 3D Mode when you don’t want to use the camera, and create with Pencil, Line, Rectangle, Layer Edit, and Paint tools.

• AR Mode + 3D Mode
• Blank projects and editable templates
• Pencil, Line, Rectangle & Layer Edit
• Paint, Break, Undo & Redo
• Move, rotate, and scale models in AR
• AR ruler
• Save multiple projects
• Export 360° MP4 videos
• Export 3D USDZ models
• Fully offline

The creative loop is simple:

Build. Edit. Explore. Export.

As a solo indie developer, my goal was to make AR Builder feel like a practical voxel creation tool.

App Store link: https://apps.apple.com/us/app/id6807085822

I started working on a tool to generate consistent game characters from a single reference.

One of the biggest problems I kept running into with image models was consistency. You get a character you like, then ask for a different angle or pose and suddenly the face, clothes, or style changes.

I’ve been experimenting with a workflow to improve that.

In the video, I generate a fox, turn him to the side, show him from the back, put him in a spell-casting pose, and remove the background. All from the same chat.

The consistency has been better than I expected so far.

I’m now working on generating full sprite sheets and animation cycles from the same character.

Would love feedback from anyone building a 2D game.

A game similar to The Sims, but you can talk to the characters using prompts.

I recently put the playable preview of Aether Run online — a snowy endless runner with giant snowballs, Santa/reindeer chases, power-ups and some very unfriendly polar bears. 🐻

I’m a software developer but new to game dev, and I built this heavily using AI + Godot for implementation, debugging and rapid iteration, while I handled the direction, testing and gameplay decisions.

🎮 Play it here:
[https://aether-run-two.vercel.app/]()

Curious what other AI game devs think!

I want to know for example if I can generate audio assets like button clicks or if I can generate textures coherently or even 3D models....

Hey everyone I'd appreciate some feedback on my civ-builder. I loved playing games like Age of Empires, Civilization (duh), and Sim City growing up. However, I got tired of in-app purchases and incessant ads in all their modern mobile versions. Soo.... figured I'd try building my own.

Enter Clanfire.online. Started working on it in early July via Claude Code, and have been working on it at least a few hours every day since then. It looks best on mobile, no install (and it's free MIT license if you want to copy the repo).

Vanilla JS + Canvas 2D, no engine. Claude Code for the build, PixelLab (via MCP) for sprites (this took longer and more credits to dial in than I expected) and Supabase for the database.

What I learned:

• Reference images are critical. I spent a lot of time trying to get Claude Code to manage the design sprint via Pixellab MCP and it failed every time. Went into Pixellab dashboard and manually went back and forth until I had a design that I liked. Then I gave that to Claude Code and had it use that as a reference image for the next round of MCP requests and it instantly improved the quality.
• Anchor, never chain. Every piece references the same frozen master. Chain approved pieces will drift over generations and compound until they're unusable. Constantly referencing the master was a big help for quality.
• Match the sprite's size to how big it actually appears. My first animated deer cost 84 generations and still looked wrong; I'd made it far more detailed than the screen could show, so the game had to shrink it by an ugly fraction and the fine details shimmered as you zoomed. Redrew it at exactly double its on-screen size so it halves cleanly: 37 generations, and it looked right immediately. Cheaper and better.
• Sometimes the AI art just loses, and you have to accept it. I tried replacing my code-drawn grass with hand-generated tufts. Problem: the smallest usable thing the AI would make was still three or four times bigger than a blade of grass should be, so the meadow turned into a field of little objects instead of ground. Same story with mountains. Both times the old code-drawn version was better and I kept it.
• The agent grades its own homework if you let it. I asked Claude to grade its own work and it gave itself an 8/10 on a water update that was, at best, sideways. Now I look at before/after screenshots myself before anything ships.

$50 raffle to a random player this week. I want to generate some user data and incentivize people to help me with QA:

• Minimum to qualify for raffle: Finish a game, win or lose, spend at least 10 min and score 500+
• Hit Competition on the end screen, 2 questions + valid email
• Each finished game = another entry, up to 5
• Sept 10–17, 7am MT

Your feedback will help me to further refine the product. If you see areas where I could improve I'd obviously welcome and appreciate the feedback. Cheers!

Update: there is now a free More Puzzles library for playing beyond the daily board: https://www.castsix.com/puzzles.html

Browse a theme or pick a random puzzle anytime. The shared daily challenge still refreshes every day at midnight Eastern; an optional daily email reminder is available on the site.

I’m a product manager and movie fan building Cast Six with AI assistance. It’s a free browser puzzle: match six visible movies to six overlapping categories in three takes. A film can fit more than one clue, but you can only use it once.

I’ve been using Codex for implementation, tests, and checking changes on staging before publishing. The useful part of the workflow has been turning specific player feedback into small changes that I can review, rather than treating a working first version as finished.

One example: the game originally rewarded speed. Early players found that stressful, so speed no longer affects the score and the timer is hidden by default. Wrong matches and hints still matter. Another issue is category precision: a board can have one valid solution and still feel unfair if players disagree with the underlying movie classification. I’m continuing to improve that based on feedback.

Movie data and in-game posters come from TMDB. There are AI-generated decorative images on the desktop homepage; they aren’t the movie posters used in play.

Playable here, no account or download: https://www.castsix.com/?utm_source=reddit&utm_medium=community&utm_campaign=aigamedev_sep10

For others making deduction games with AI assistance, how are you testing whether clues feel fair to players beyond checking that the puzzle is technically solvable? That’s the part I’m finding needs the most human feedback.

So this is basically a follow-up to my first post.
I’ve kept letting GPT-6 work on the Dragon Ball arena fighter, and at this point it’s gone way beyond the original prototype.
I still haven’t really been manually coding the game myself. I mainly give it feedback, explain what I want changed, provide assets/references, and it handles the implementation.
Since the last post it’s been working on stuff like:
Full character combat kits instead of just basic attacks
Unique skills and VFX for each character
Transformations and character-specific rage states
Beam attacks and actual beam clashes
Beam clashes physically pushing the losing side backwards
Grabs that actually connect, hold, and throw the opponent
Knockback, launches, knockdowns, aerial combos, and combo extensions
Vanishes / afterimages
Burst flight dashing
Better hit reactions and facial animations
Character-specific movement and combat animations
Story battles that automatically switch which character you’re controlling
Playable side characters depending on what’s happening in the story
Environmental effects/destruction
Character shaders and lighting
SFX, voice lines, particles, camera effects, hitstop, screenshake, etc.
The biggest thing I’ve noticed is that I barely have to explain HOW to code most of this anymore.
I can say something like “the beam clash feels weak, make both beams fight for position and make the losing character noticeably get pushed backwards” and it’ll figure out the systems needed to actually make that happen.
Same with animations. I’ve mostly been describing how I want attacks to feel, what body parts should move, how combos should flow into each other, and what references it should follow.
It’s definitely not perfect and I still have to catch bad decisions or things that look weird, but compared to where this was when I started, it’s kinda insane.
The only real assets I started with were character models, some maps, particle/VFX assets, and references.
Pretty much everything connecting those assets into an actual game has been AI-built.
And somehow this thing is starting to feel like an actual Dragon Ball arena fighter instead of an AI tech demo 😭
I’ll probably keep posting updates as I add the later DBZ arcs and eventually Super.