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Engineering Manager Handbook
Building with AI
AI-Assisted Engineering

AI-Assisted Engineering

🚧 Expanding

AI coding assistants are already in your team’s editors and terminals whether you’ve blessed them or not. The interesting management question isn’t “should we use them” — it’s how to get durable leverage out of them without trading away the rigor that keeps a codebase alive. Used well, they collapse the boring parts of the job and free people for the thinking that matters; used carelessly, they generate plausible code nobody understands at a pace your review process can’t absorb. This page is a stub; the aim is to help you steer toward the first outcome. The tooling is only half the story — getting a whole team to adopt these tools well is its own change-management problem.

Getting started

If you want hands-on experience before forming opinions — and you should — pick one tool and actually ship something small with it. A few reasonable entry points:

  • Claude Code — an agentic, terminal-based tool that works across your whole repo. Our step-by-step guide covers install, pointing it at an existing project with /init, and the handful of commands worth knowing on day one.
  • GitHub Copilot — the most widely adopted in-editor assistant; likely already in your team’s IDEs, so worth knowing well.
  • Whatever your team already reaches for — meet people where they are before standardizing on anything.

The tool matters less than the reps. Spend a week doing real work through one of these and the trade-offs below stop being abstract.

What this will eventually cover:

  • Where assistants genuinely help (boilerplate, tests, unfamiliar APIs, exploration) vs. where they mislead
  • Autocomplete vs. chat vs. agentic tools — and when each fits the work
  • What “AI wrote it” does to code review, ownership, and the definition of done
  • Measuring whether it’s actually helping, not just feeling fast
💡
The trap I watch for is velocity that looks great and ages terribly. Generated code is easy to accept and hard to truly own. My rule for the team: you are accountable for code you commit exactly as if you’d typed every character — if you can’t explain it in review, it doesn’t ship. That single norm does more than any tooling policy.

📚 Go Deeper

Books

  • Simon Willison's blogThe most clear-eyed running commentary on coding with LLMs — what genuinely works, written by someone who ships with these tools daily.

Tools

  • Claude Code documentationAn agentic coding tool that works in the terminal across your whole repo, not just a single file. The current high-water mark for AI-assisted dev.
  • GitHub Copilot documentationThe most widely adopted in-editor assistant. Worth knowing well since much of your team is probably already using it.
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AI Literacy for EMsClaude Code 101