ai-first-engineering
Engineering operating model for teams where AI agents generate a large share of implementation output.
npx skills add mturac/everything-openai-codex --skill ai-first-engineering --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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
- Process Shifts
- Architecture Requirements
- Code Review in AI-First Teams
- Hiring and Evaluation Signals
- Testing Standard
What does the ai-first-engineering skill do?
Engineering operating model for teams where AI agents generate a large share of implementation output.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill ai-first-engineering --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.