Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

AI First Engineering Use this skill when designing process, reviews, and architecture for teams shipping with AI assisted code generation. Process Shifts 1. Planning quality matters more than typing speed. 2. Eval coverage matters more than anecdotal confidence. 3. Review focus shifts from syntax to system behavior. Architecture Requirements Prefer architectures that are agent friendly: explicit boundaries stable contracts typed interfaces deterministic tests Avoid implicit behavior spread across hidden conventions. Code Review in AI First Teams Review for: behavior regressions security assumptions data integrity failure handling rollout safety Minimize time spent on style issues already covered by automation. Hiring and Evaluation Signals Strong AI first engineers: decompose ambiguous work cleanly define measurable acceptance criteria produce high signal prompts and evals enforce risk controls under delivery pressure Testing Standard Raise testing bar for generated code: required regression coverage for touched domains explicit edge case assertions integration checks for interface boundaries

ai-first-engineering