ai-first-engineering
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.
- Kind
- Skill
- Works with
- Claude Code, Codex
- Source
- affaan-m/ECC @ d3b8a3e90890
- Path
- skills/ai-first-engineering/SKILL.md
- License
- MIT
- Jobs
- Implementation, Review
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# 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