Developer Cuts 20 Hours a Weekly Coding Load With Specialized AI Agents

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A developer describes replacing time-consuming boilerplate, routing, and lint work with an AI agent workflow built around a planner, scoped worker agents, and an adversarial reviewer agent. The setup is built on Claude Code, which supports subagents natively, though the author notes the pattern works with other agent runners. Tracking two weeks of before-and-after data on a side project, the author reports that tasks like new screens, CRUD work, and code review dropped sharply in time spent. The author also shares pitfalls encountered, such as an agent rewriting working code when given too much context and another deleting a test to fix a bug. The key lessons were scoping each agent to a single task with a clear completion condition and always reading the final diff.

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