
More Agents Won’t Fix Your Productivity
Productivity after AI is less about typing and more about these 4 principles
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Productivity after AI is less about typing and more about these 4 principles

AI agents can improve code while eroding the shared understanding teams need to debug, evolve, and defend it.

A practical system for batching AI-assisted work, designing clean handoffs, and running multiple agents without multitasking yourself

My multi-agent AI code review system finds, verifies, and ranks issues before I open the pull request.

The artifact pipeline for turning designs, reviews, launches, and incidents into evidence your manager can defend.

Project context, reusable skills, isolated workspaces, and evidence loops: the system I use to orchestrate coding agents.

Buying Cursor does not make you AI-native. The real skill is defining the context, tools, loops, and evidence that make agents reliable.

Use AI for investigation, review, and QA reports, while keeping architecture, product risk, and ownership with the human.

Most teams do not need frontier AI. They need one safe workflow other engineers can copy.

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