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Back to Blog<br>“Loop engineering” is having a big moment right now.<br>Boris Cherny mentioned that he doesn’t prompt Claude anymore, he writes loops. Peter Steinberger posted a monthly reminder to stop prompting agents, and design loops that prompt them instead. On the other side, people are pointing out that a loop around an LLM call is still just a while loop, and that we had cron jobs and webhooks long before we had agents.<br>I think that this critique misses an important shift that’s happening: the work inside the loop has changed. Agents can now investigate, modify code, run tests, and review results with pretty high quality. The middle of the software development lifecycle (SDLC), where humans used to spend so much time working on repetitive tasks, can now be designed with agents and humans working side-by-side, as part of an autonomous system.<br>Most of the conversation today is still around individual loops: one developer using agents to move a task forward. But I believe the more important pattern is emerging at the team level.<br>The best engineering teams are starting to run agentic SDLC loops in production: always-on systems that take work from trigger to verified outcome across the software development lifecycle, with humans involved where judgment actually matters.<br>So, what is loop engineering?<br>At the team level, loop engineering is the practice of designing a system where a team of agents work toward an outcome, bringing humans in where judgment matters most. The hard engineering work lies in choosing the right system design, the right models for each task, and knowing when to involve humans so the loop delivers a higher-quality outcome.

A team-level loop connects triggers, agents, human checkpoints, and shipped outcomes into one repeatable system.

What makes loop engineering different from automation?<br>1. Agents carry the bulk of the doing<br>Pre-AI software automation could route, notify, and glue systems together, but it couldn’t investigate a stack trace, write a fix, and then rerun the test suite. The middle of the workflow, the part that used to require a person, can now be fully agentic. That’s a completely different category of work being absorbed, and it requires you to rethink what can become a loop.<br>2. Humans are in the loop by design, not as a failure mode<br>In previous DevOps-style automation, a human showing up usually meant something was broken. In agentic loops, a human checkpoint is where the highest-leverage judgment happens. It separates a high-quality outcome, from a loop that keeps spinning and burning tokens.<br>The hard part is identifying the right point to bring the human in. If it’s early, you’ve rebuilt a notification bot. If it’s late, you increase the risk of creating a whole lot of slop. The goal is not always to remove the human entirely, but to use the right level of autonomy for the risk involved.<br>3. Each run can make the loop better<br>A cron job runs the same way every night. An agentic loop can leverage memory and traces from previous runs to improve over time.<br>Each run produces a trace: what worked, what failed, and where the human stepped in and corrected course. That trace can then be fed back to improve the quality of the overall system: prompts, tests, acceptance criteria, tools, or escalation rules.<br>The key shift: from individual to team-level agentic SDLC loops<br>The most forward-thinking teams are moving beyond individual loops and building loops for the team: standing workflows where repetitive work across the software development lifecycle is handled by agents on an ongoing basis, and humans participate at the moments that actually need them.<br>We’ve started calling these agentic SDLC loops, and the shape is remarkably consistent.<br>The outer shape of an agentic SDLC loop<br>Trigger: A PR opens, an alert goes off, or a ticket lands.<br>Execution: Agents execute the middle: investigate, reproduce, draft a fix, and run the tests.<br>Verification: Agents and automated systems run the checks available to them, while humans step in where judgment, approval, or additional context is...