AI has solved the building problem but maintenance problem is an issue. Spinning up a new feature with an AI coding assistant takes minutes now. That part works. The problem comes the next day when the AI breaks two existing things while adding a third.

I'm a pure vibe coder — no traditional coding experience. I spent 6 months building a personal project entirely with AI agents. The building was fast. The maintenance was painful - until I found a simple pattern. Each feature lives in its own folder with a manifest file, a central Kernel auto-discovers them at boot. The AI works in one folder per task and physically cannot affect code outside it.

The result when you add a new feature, existing ones stay untouched. Hallucinations stop spreading across the codebase. Token usage drops because the AI only reads what it specifically needs. My own codebase is still messy in places - this pattern doesn't fix everything but it helps in minimizing the maintenance spiral.

Experienced software engineers will probably find holes in this. I know I’m flying blind on traditional best practices and might have missed something but my goal wasn't perfect engineering - my goal was survival against AI-generated spaghetti code.

This is one of the ways in which we can make coding with LLMs better.

Git link: https://github.com/Maqsood32595/fractal-kernel/tree/with-admin-dashboard.