AI-factory: Stopping AI Code Rot

The biggest issue with LLM agents right now isn't the first draft—it's the "code rot" that happens when an agent refactors a feature but accidentally breaks three other things because it lost the original intent. AI-factory tries to fix this by moving from prompt-based generation to a spec-driven pipeline.

Basically, instead of just telling an agent "fix this bug," you define a strict specification. The pipeline ensures the AI adheres to that spec throughout the iteration process, which keeps the codebase from degrading into a mess of contradictory patches. It's essentially a guardrail for autonomous coding agents.

If you want to get this running for a deep dive into your own projects, here is the basic flow:

1. Clone the repo and install dependencies.
2. Define your system specifications in the designated spec files.
3. Run the pipeline to generate or modify code based on those specs.

git clone https://github.com/highflame-ai/ai-factory.git
cd ai-factory
npm install

For anyone building a custom AI workflow, this is a solid alternative to the "prompt-and-pray" method. It treats AI generation more like traditional engineering—where the spec is the single source of truth—rather than just a chat conversation. Definitely worth a look if you're tired of your agent introducing regressions every time it tries to be "helpful."

The full source is here:
https://github.com/highflame-ai/ai-factory