# Responsible Loop Engineering

DevFeed: [Responsible Loop Engineering](<https://devfeed.tech/articles/responsible-loop-engineering-25319.md>)

Original publisher: [Read original article](<https://kau.sh/blog/responsible-loop-engineering/>)

Author: Kaushik Gopal

Published: 2026-06-22T20:39:22Z

Content type: opinion

Language: en

Sources: [Kaushik Gopal's Site](<https://devfeed.tech/sources/kaushik-gopal-s-site.md>)

Topics: [Loop Engineering](<https://devfeed.tech/topics/loop-engineering.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Software Engineering](<https://devfeed.tech/topics/software-engineering.md>), [future of software](<https://devfeed.tech/topics/future-of-software.md>), [Agent Skills](<https://devfeed.tech/topics/agent-skills.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [future-of-software](<https://devfeed.tech/tags/future-of-software.md>), [loops](<https://devfeed.tech/tags/loops.md>), [software-engineering](<https://devfeed.tech/tags/software-engineering.md>)

## AI overview

The author argues for responsible loop engineering: designing and operating agent systems that can run continuously while controlling costs. The article distinguishes capped one-shot loops from autonomous loops that select tasks, use subagents, research, test, and return results for review. It argues that autonomous loops require bespoke engineering, integrations, execution strategies, and queueing.

## Source excerpt

Loop engineering convinced me. Not because it's clever -- because done right, it doesn't bankrupt you. This post captures where I've landed: a responsible way to run loops at scale without burning a hole in your pocket. Naysayer -> Believer ## I've been a vocal naysayer. Not because the approach doesn't work -- it works. The costs never justified it. No surprise -- the people singing its praises usually aren't the ones paying the API bills. But when Peter & Boris tell you something, you look closer. Same thing happened with agent skills -- Simon W saw something early, and that became the biggest hammer in our AI toolbox. Types of loops ## The public discourse mixes loops with loop "engineering," so let's disambiguate. One-shot loops ### Today, an agent can execute a task, have an independent judge review the result1, apply the feedback, and repeat. You put a cap on the number of loops. Or you let it run until it's "satisfied" -- a bad idea. These are easy to set up. Many people are already demonstrating them. I call these one-shot loops. They're easy enough that I'll focus on the other kind. Autonomous loops ### But when Peter Steinberger and Boris Cherny talk about loops, I think they mean autonomous loops. You set up agents to run continuously. They decide when to act, pick up the right tasks, spin off subagents, research, test theories, and send results back for review. Or ship, if confidence is high enough. An entire system running on its own -- you shovel tasks at the speed of thought or voice. These loops are self-sustaining and take real engineering to get right. I'll go out on a limb: Future of Software Engineering is loop engineering Most of the software engineers of tomorrow are going to be spending their time setting up and engineering loops. Because it's hard and it's going to require skill -- there's no one loop we can template for all solutions. From my experimenting so far, this feels bespoke in the way good software is bespoke. You can't just use an agent sk