This isn’t meant to be a new IDE or a “better prompting” layer. It came out of frustration with how quickly AI-assisted projects drift once they grow beyond a few files.

The core idea is that architecture usually lives in people’s heads or in docs, so every generation forces the model to re-infer structure from raw code. That inflates context and increases the chance of subtle breakage.

Archeon treats architecture as a small, explicit, machine-readable artifact that exists outside the model and is validated before code is generated. The goal is to reduce degrees of freedom early, not to make the model smarter.

Everything runs locally and can be ignored or removed at any time. If it doesn’t help a project stay coherent over time, it’s not worth using.

I’m mostly curious whether others have hit the same scaling problems with AI-assisted codebases, and how they’ve tried to address them.