🐝 BeeCool Devlog #1 — Millions of Bees, One Rainstorm at a Time

Hey everyone 👋 I’m James (aka BeCool3000).

I’m building BeeCool, a GPU-driven bee colony simulator where thousands (and eventually millions) of bees buzz around a dynamic hex-grid world.

Even though I have released 1.0. Right now I’m working on a demo, which will be capped at 500 bees — enough to show off the swarm feeling while leaving plenty of room for your imagination about what the full game can do.

In the full 1.0, you’ll be able to simulate millions of bees. There’s even a rain and water system I spent months developing, so maps can have storms that flood tunnels and change how your hive grows.

BeeCool is also my way of showing what’s possible with compute shaders and AI-assisted development (Codex). I’ll be sharing more about how I built it in future posts, especially for RTS and sim devs who want to push past normal unit limits.

Ahh but compute shaders are rough!

Some of the main roadblocks for using compute shaders in games (especially sims/RTS) are:

1. Data Management

• GPUs are great at parallel math, but keeping CPU ↔ GPU data in sync is tricky.

• Any CPU readback kills performance, so you have to design systems that never need to pull data back mid-frame.

• Designing everything to be GPU-first means rethinking your architecture.

2. Debugging & Tooling

• Debugging GPU compute is harder than CPU code—error messages are vague, and tools like RenderDoc/Nsight are specialized.

• You don’t get step-through debuggers like in C#.

3. Complexity of Algorithms

• Not all game logic fits parallel GPU execution.

• Things like AI, branching logic, or small conditional tasks run better on CPU. Compute shines with math-heavy, uniform workloads (pathfinding fields, particle sims, water, etc.).

4. Cross-Platform Issues

• Shader languages differ: HLSL (DirectX), GLSL (OpenGL/Vulkan), Metal (Apple).

• Consoles/phones might not support certain features, so you end up writing multiple versions or falling back to CPU.

5. Memory Limits

• GPU memory is limited compared to CPU RAM.

• Large world states, like RTS unit logic, can hit VRAM ceilings fast.

6. Synchronization

• You can’t just “wait” on the GPU without stalling the pipeline.

• Properly sequencing kernels and ensuring no race conditions across threads is hard.

7. Adoption Barrier

• Most devs stick with CPU because:

  • It’s easier to prototype/debug.

  • Teams are trained in C#/C++ not shader compute.

  • Middleware (Unity/Unreal) only partly supports it—lots of boilerplate is still on the dev.

Stay tuned for the demo 🐝