ai-sdlc

The AI SDLC is a framework and manifesto for teams building software with AI assistance. Its starting premise is that AI tools have made it much easier to generate code quickly, but that speed creates its own problems: teams end up with more features than they fully understand, more code than they can reason about, and momentum without a clear direction. The framework is a response to that situation.

The core idea is to structure development around explicit control points. At each control point, the developer pauses, reviews what the AI produced, verifies they understand it, and decides whether to move forward. AI handles the implementation work between those checkpoints. The developer retains ownership of every decision, and those decisions are recorded in the repository as shared context the team can refer back to.

The README is intentionally brief and points to separate documents for the full detail: a Manifesto describing the reasoning behind the approach, a Principles file laying out the key rules, and an In Practice file covering the specific phases, verification steps, and how responsibility is divided between the developer and the AI.

This is not a code library or a tool you install. It is a set of documented practices and a philosophy for engineering teams who want to use AI without losing understanding of what they are shipping. The language of the repo suggests it is aimed at developers and engineering managers who feel that AI-assisted workflows are moving faster than their teams can track.

The repository itself is sparse on technical detail in the README, and most of the substance lives in the linked markdown files rather than in deployable software.