What Building PPI.Studio Taught Me About Governing AI Coding Agents

说明与用途

构建 PPI.Studio 显示 AI 代码生成器速度快，但常常压缩或误解细节。通过实施严格的治理体系，让人类拥有生产代码，AI 仅提供完整替换路径的建议，可确保可靠性和透明度。

问题

AI coding agents can produce code quickly but often compress or misrepresent technical details, leading to incorrect architectural decisions.

结果

The governance framework prevented semantic compression errors, ensured complete replacement paths, and maintained human accountability, turning AI agents into reliable engineering accelerators.

工作流

• 1. Define a clear human‑owned production code base under src/main/.
• 2. Use src/test/ as the agent‑maintained proving ground.
• 3. Treat interfaces and contracts as change‑control boundaries with API impact analysis.
• 4. Enforce constructors to perform dependency assignment only.
• 5. Require every important claim to have an evidence class (Implemented, Tested, etc.).
• 6. When an agent suggests a change, provide the full replacement path and affected classes.
• 7. Conduct regular audits to verify build success and identify incomplete modules.
• 8. Maintain a closed‑loop workflow: evidence normalization → conflict detection → scoped analysis → recommendation → scientist review → assay feedback → updated evidence.

证据

The failure was not a fabricated SDK boundary. It was semantic compression.

来源

The responsible answer must identify the exact class, method, registration mechanism, and execution path that makes it happen.

来源