Goals and Loops: Telling Your Coding Agent When It's Done

In June 2026, two people with unusually good vantage points posted what amounts to the same sentence. Peter Steinberger: “You shouldn’t be prompting coding agents anymore. You should be designing loops that prompt your agents.” Boris Cherny, who created Claude Code: “My job is to write loops.” Both lines are quoted in Addy Osmani’s essay that gave the shift its name, loop engineering, and it would be easy to file them under aphorism if there were not a small, concrete feature sitting underneath: you hand the agent a definition of done, and it keeps working, turn after turn, until that definition actually holds. This is a short guide to that feature, what it does, why it works, and how to fold it into an ordinary day of work.

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Working With Coding Agents: Principles for Reliable AI-Built Software

In late 2025, Andrej Karpathy described going from roughly 80% manual coding to 80% agent coding in a matter of weeks, calling it the biggest change to his workflow in two decades of programming. Coding agents like Claude Code and Codex can now explore a codebase, plan a change, write it, run it, and test it with minimal supervision. Yet the people getting reliably good output are not the ones with the cleverest prompts. They are the ones who noticed that the bottleneck has moved: writing code is now cheap, and deciding whether to trust it is the expensive part. This post distils what top practitioners converge on into seven working principles, aimed at anyone using these tools to build real things.

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