agentic-engineering

Eval-first execution in agentic engineering runs baseline evaluations and regression checks before and after implementation, ensuring verifiable units and delta analysis to maintain quality governance across AI-driven tasks.

Route engineering tasks by decomposing work into independent units and sending classification or boilerplate to Haiku, implementation or refactoring to Sonnet, and architecture or root-cause analysis to Opus based on task complexity.

Decompose complex software engineering work by breaking it into independent agent-sized units with explicit completion criteria, risk focus, and cost tracking to manage execution and retries across sessions.

Yes, you can enforce regression checks and cost tracking across autonomous AI coding sessions by applying quality governance controls that monitor invariants, manage retries, and maintain rigorous review.

The best way to manage costs when automating software engineering tasks with AI is to use cost-aware model routing, sending simpler tasks to Haiku and reserving expensive models like Opus for complex root-cause analysis.