I’ve been constructing a small Python demo sport for ~1.5 weeks and wished to share a slice of it right here. I’m posting this to aigamedev + vibecoding as a result of the workflow is the purpose.

Scope word: I’m solely displaying elements of the demo (just a few cores, some mechanics, and bits of gameplay). Full demo is deliberate for Steam within the coming weeks; I’ll replace the Steam hyperlink when it’s stay. Observe if you need that drop.

TL;DR

• Chill incremental idle/clicker about pushing “cores” into instability till they breach
• All property are generated by the sport code at runtime (graphics, sounds, fonts)
• AI was used for coding assist solely, no generative AI property/content material
• In-built about 1.5 weeks
• Instruments: Gemini 3.1/3 Professional for coding, ChatGPT 5.2 Pondering for technique/prompting

What the sport is It’s an incremental idle/clicker with a “breach the core” objective. You construct output, handle instability, and set off breaches throughout totally different cores. The design objective is easy: all the pieces ought to look and sound engaging even while you’re doing fundamental incremental actions.

AI utilization (coding solely) I used Gemini for implementation bursts and ChatGPT for structure/technique/immediate engineering. The worth for an skilled Python dev was sooner iteration and fewer glue-code fatigue, so extra time went to really feel, tuning, and construction. No gen-AI artwork/audio/textual content is shipped; visuals/audio/fonts come from code.

Engine structure (the way it’s put collectively)

1. Loop + threading The sport runs on a devoted thread that owns the GL context and the principle loop. This retains issues responsive round OS/window habits.
2. Window + enter GLFW window wrapper plus framebuffer-aware mouse coordinates for high-DPI. Enter tracks press/launch, deltas, and drag threshold so UI/world interactions keep constant.
3. World Timer targets FPS (or uncapped) and smoothed the dt for the updates.
4. State-driven design A single GameState holds the financial system, upgrades, run knowledge, settings, and the parameters that drive reactive visuals. The simulation updates the state; rendering reads it.
5. Simulation updates by Numba-accelerated features for efficiency.
6. UI is specified by a 1920×1080 base decision and scaled to the window permitting for customized resolutions and aspect-ratios.
7. Renderer + publish Batch 2D renderer with a numpy vertex buffer and a Numba JIT quad-writer for throughput. There’s an HDR-ish buffer + bloom-style publish chain and gameplay-reactive parameters.
8. Shaders Shader-side draw varieties deal with shapes/textual content/particle rendering, clipping, and the “core” look. Plenty of the “polish” is in that pipeline.
9. Fonts/audio are code-generated Fonts are generated into an atlas at runtime, and audio is generated by code too. No exterior asset recordsdata for these.

If you wish to see particular subsystems (save format, UI routing, and so forth.), inform me what to concentrate on and I’ll publish a brief follow-up with screenshots/gifs.

Steam (TBD): hyperlink shall be up to date (comply with if you need it).