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A conceptual discussion on the importance of stacking loops in AI agent design, drawing parallels to Sutton's Bitter Lesson and advocating for scalable systems over manual fixes.
Describes a loop command in Cursor to automatically fix flaky tests by running the test suite multiple times, collecting intermittent failures, and fixing or quarantining them until five consecutive green runs.
Peter Steinberger suggests moving from prompting coding agents to designing loops that prompt agents, while @dzhng advises using state machines instead of loops.
The article explains the concept of 'loops' in AI coding, where developers write programs that prompt coding agents instead of manually prompting, as popularized by Peter Steinberger and Boris Cherny, and discusses how this shift represents a new abstraction layer in AI-assisted development.
Boris, the creator of Claude Code, shares a crucial shift: moving from writing prompts to writing loops, letting the model iteratively progress tasks in a repeatable loop instead of providing a one-time answer.