AI Coding Governance for Real Software Teams

Short summary

Code generation is fast, but software engineering is hard. Real systems have hidden contracts—authorization rules, business logic, deployment assumptions, integration edges, stale documentation—that AI cannot reliably infer from prompts alone; success requires tight boundaries, clear context (ADRs, tests, architecture constraints), smaller decomposed tasks, fast verification, and realistic review workloads. Productivity metrics that skip review burden mask the true cost of AI-generated code in production.

• •Code generation isn't equivalent to production-ready software engineering
• •AI needs explicit context (ADRs, tests, architecture) and tight task decomposition to work safely
• •Review burden is underestimated; tired reviewers don't guarantee confident merges

Generated with AI, which can make mistakes.