ai-first-engineering

AI-First Engineering is an operating model for teams where AI agents generate a significant portion of implementation output. It shifts focus from typing speed to planning quality, emphasizes evaluation coverage over anecdotal confidence, and reframes code review around system behavior rather than syntax.

• Define process shifts prioritizing planning quality and evaluation coverage over traditional metrics
• Establish architecture requirements favoring explicit boundaries, stable contracts, and typed interfaces
• Refocus code review on behavior regressions, security, data integrity, and failure handling rather than style
• Identify hiring signals for engineers who decompose work cleanly and produce high-signal prompts and evals
• Raise testing standards with required regression coverage, edge-case assertions, and integration checks

1. 1.Review the process shifts section to understand how planning and evaluation priorities change with AI-assisted development
2. 2.Assess your current architecture against the agent-friendly requirements (explicit boundaries, stable contracts, typed interfaces)
3. 3.Adapt your code review checklist to focus on behavior, security, data integrity, and failure handling rather than syntax
4. 4.Update hiring rubrics to evaluate decomposition skills, acceptance criteria definition, and prompt/eval quality
5. 5.Implement the raised testing standard with regression coverage requirements and integration checks