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Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Source
youtube.com
Author
AI Engineer
Date

Context

A coding loop can be paced by human review capacity. In HumanLayer's talk, the team describes a migration workflow that finds code still using an old pattern, selects a small change and opens a pull request for review.

Before another run, the workflow checks whether its previous pull request remains open. If so, it stops, preventing that loop from accumulating more unreviewed changes. Human corrections also update a version-controlled feedback file that later runs receive. This makes review both a brake on output volume and a source of guidance for the next attempt.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
Key quotes

“we're still building 40,000line PRs that just nobody wants to read, right?”

Kyle Mistele

“Control loops change a system incrementally instead of just trying to get straight to the end state immediately all at once and risk blowing everything up, right?”

Kyle Mistele

“I don't think you should ever send an agent to do deterministic code's job, but you certainly can.”

Kyle Mistele

“bad code is much more expensive in the age of agents than it it has ever been at any point in the past”

Kyle Mistele

“idiomatic handwritten examples for the agent to follow because they're just pattern replicators and otherwise you're getting what's in the docks or what the agent knows from the internet”

Kyle Mistele
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