ai-first-engineering

# 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 ## When to Use Engineering operating model for teams where AI agents generate a large share of implementation output. Covers: Process Shifts, Architecture Requirements, Code Review in AI-First Teams, Hiring and Evaluation Signals, Testing Standard.