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Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Replace unbounded coding-agent loops with measured, incremental changes: sense code state, choose one bounded task, open a reviewable PR, and pause until a human responds.

AI Engineer · Jul 25, 2026
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Source Summary

HumanLayer frames coding automation as **sense → control → actuate**: detect a measurable code condition, select a bounded change, and give an agent a skill plus handwritten reference patterns. Their workflow schedules **one incremental PR per day**.

Practical Implication

Build loops around deterministic scanners, small changes, CI, and human review. Keep **at most one open PR per loop**, then feed reviewer corrections back into the skill before the next run. Increase throughput only after the loop is reliable.

Agent-Ready Context
HumanLayer frames coding automation as **sense → control → actuate**: detect a measurable code condition, select a bounded change, and give an agent a skill plus handwritten reference patterns. Their workflow schedules **one incremental PR per day**.

Build loops around deterministic scanners, small changes, CI, and human review. Keep **at most one open PR per loop**, then feed reviewer corrections back into the skill before the next run. Increase throughput only after the loop is reliable.

The worked example is an internal RPC migration, not evidence that the pattern fits every engineering task. Even bounded loops can produce duplicate or conflicting work, and batching **three or five procedures** trades reviewability for speed.
Context Map
agentcoding#harness-engineering#coding-agents#agent-reliability
Uncertainty
The worked example is an internal RPC migration, not evidence that the pattern fits every engineering task. Even bounded loops can produce duplicate or conflicting work, and batching **three or five procedures** trades reviewability for speed.