Loop Engineering: Analysis & Application Case Studies
Loop Engineering shifts your role from prompting AI to designing autonomous agent loops. Explore how it builds on Context and Harness Engineering with real world cases.
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The head of Claude Code, Boris Cherny, once said in a talk:
“I don’t prompt Claude anymore. I have loops running that prompt Claude and figuring out what to do. My job is to write loops.”
In other words, he no longer prompts Claude himself. Instead, he writes “loops” that prompt Claude, and his job is simply to design those loops.
Peter Steinberger, founder of OpenClaw, put it even more directly: “You shouldn’t be prompting your Agent anymore. You should be designing Loops to prompt your Agent.”
This is a hot new concept that has been circulating widely in AI development circles over the past two weeks: Loop Engineering.
What is its relationship to the concepts we’re already familiar with — Context Engineering and Harness Engineering? What are the differences?
Is this just old wine in a new bottle, or is the tech world simply inventing new terms again?
