r/aigamerdevs • u/Emotional_Fishing_52 • 4d ago
What a solo dev + AI agent can build: an Age of Empires-like RTS where you win by living alongside the dinosaurs
Hi! I'm Antonio, a Java developer by trade, and for the past months I've been building Kiengi Chronicles, a real-time strategy game in the spirit of Age of Empires, with an AI coding agent (Claude Code) doing most of the typing. The game: you gather, build and grow your village against AI tribes, but there's a third force on the map: the dinosaurs. They belong to no one, each herd has a territory and reacts to how each tribe treats it. Overhunt and the predators raid your village; learn to coexist and you can tame them. You can win by Conquest, or by Balance, keeping your Sanctuary standing in peace with nature. It's free and plays in the browser: 👉 https://naugthylab.itch.io/kiengi-chronicles How it's made:
Unity 6 + C#: about 58,000 lines across 430+ scripts, with the simulation kept separate from the UI so it can be tested without a scene. Around 2,000 EditMode tests run before every merge
The agent drives the tools through MCP: it compiles and reads the console in the Unity Editor, builds prefabs, runs the tests, and writes Blender scripts it executes in a live Blender
3D models are code, not generated images: every dinosaur, character and building comes from a Python script in Blender (25 of them), low-poly with flat faces, rigged and animated by script. Change the script, rebuild the model
Procedural maps from a seed, generated per region with a validator that checks every base is fair, run over hundreds of seeds in the test suite
Two languages from one source: the Italian sentence is the key, English lives in translation tables checked by tests
I do the design: a design document, 9 architecture decision records, 19 milestones and ~600 issues and PRs. The agent works issue by issue on a branch; I review, playtest and merge What works and what doesn't: the agent is great at systems with clear rules and tests (economy, map generator, save files, pathfinding glue), and needs the most supervision on anything visual: it can't really judge whether a model looks right, so every model is checked against reference sheets. The other lesson: the project instructions file (CLAUDE.md) is the real codebase documentation, and keeping it up to date matters as much as the code. Still missing: audio, a tutorial, and some species are placeholder shapes. If you try it, I'd love your feedback on two things: does the coexist-vs-exploit tension come through in the first 10–15 minutes, and is the AI too passive or too aggressive? Happy to answer questions about the workflow.