Show HN: A SQLite graph that captures why AI-generated code exists
A new SQLite graph repository aims to preserve the engineering context behind AI-generated code. It serves as a local reference architecture for documenting requirements, decisions, and other project-related information. This tool is designed to support AI coding agents while ensuring that human oversight remains central to the engineering process.
- ▪The repository captures the reasoning behind AI-generated code by maintaining a local SQLite graph.
- ▪It is intended for use with AI coding agents like Codex and GitHub Copilot, focusing on preserving engineering context.
- ▪The tool does not replace human judgment or formal ALM systems, but rather complements them.
Opening excerpt (first ~120 words) tap to expand
Reviewable AI-Assisted Engineering ai-vprocess-ops: a small SQLite graph that captures why AI-generated code exists AI wrote the code. Where's the why? AI coding agents can build fast, but the engineering reason behind the work often disappears across sessions. This repository is a small, executable reference architecture for preserving that reason as a local SQLite graph: requirements, decisions, trace candidates, tests, evidence, open issues, policy triggers, standards references, and ALM handoff rationale. Existing project notes or memory DBs can feed this method as optional upstream sources. The repository itself stays focused on the V-process / pre-ALM method layer.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.