Loop Engineering - by Addy Osmani - Elevate

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Loop Engineering<br>From prompting agents to designing the systems that prompt them.

Addy Osmani<br>Jun 08, 2026

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Loop engineering is replacing yourself as the person who prompts the agent. You design the system that does it instead. A loop here can be thought of a recursive goal where you define a purpose and the AI iterates until complete. It’s roughly five building blocks and Claude Code and Codex both have all five now.<br>I believe this may be the future of how we work with coding agents. However, its still early, I’m skeptical and you absolutely have to be careful about token costs (usage patterns can vary wildly if you are token rich or poor), so I want to unpack what it is and what it means.

Peter Steinberger recently said: “You shouldn’t be prompting coding agents anymore. You should be designing loops that prompt your agents.” Similarly, Boris Cherny, head of Claude Code at Anthropic, said “I don’t prompt Claude anymore. I have loops running that prompt Claude and figuring out what to do. My job is to write loops”.

Okay, so what does any of that mean?<br>For like two years the way you got something out of a coding agent was you wrote a good prompt and shared enough context. You type a thing, you read what came back, you type the next thing. The agent is a tool and you are holding it the entire time, one turn after the other. That part is kind of over, or at least some think it’s going to be.<br>Now you build a small system that finds the work, hands it out, checks it, writes down what is done and then decides the next thing, and you let that system poke the agents instead of you. I wrote before about the cousin of this, agent harness engineering, which is making the environment one single agent runs inside and the factory model - the system that builds the software. Loop engineering sits one floor above the harness. The harness but it runs on a timer, it spawns little helpers, and it feeds itself.<br>The thing that surprised me is this is not really a tool thing anymore. A year ago if you wanted a loop you wrote a pile of bash and you maintained that pile forever and it was yours and only yours. Now the pieces just ship inside the products. Steinberger’s list maps almost exactly onto the Codex app, and then almost the same onto Claude Code. And once you notice the shape is the same you stop arguing about which tool, you just design a loop that still works no matter which one you happen to be sitting in.<br>The five pieces, and then notes

A loop needs five things and then one place to remember stuff. Let me list it first and then map it.<br>Automations that go off on a schedule and do discovery and triage by themselves.

Worktrees so two agents working in parallel dont step on each other.

Skills to write down the project knowledge the agent would otherwise just guess.

Plugins and connectors to plug the agent into the tools you already use.

Sub-agents so one of them has the idea and a different one checks it.

Then the sixth thing, the memory. A markdown file, or a Linear board, anything that lives outside the single conversation and holds what’s done and what is next. Sounds too dumb to matter. But it’s the same trick every long running agent depends on and I went into it in long-running agents, the model forgets everything between runs so the memory has to be on disk and not in the context. The agent forgets, the repo doesnt.<br>Both products have all five now.

The names are a bit different here and there but the capability is the same thing. Let me go one by one because honestly the details are where a loop either holds together or quietly leaks everywhere.<br>Automations, this is the heartbeat

Automations are what make a loop an actual loop and not just one run you did once. In the Codex app you make one in the Automations tab and you pick the project, the prompt it will run, how often, and if it runs on your local checkout or on a background worktree. The runs that find something go to a Triage inbox, and the runs that find nothing just archive themselves which is nice. OpenAI uses them internally for boring stuff like daily issue triage, summarizing CI failures, writing commit briefings, hunting bugs somebody added last week. And an automation can call a skill, so you keep the recurring thing maintainable, you fire $skill-name instead of pasting a giant wall of instructions into a schedule that nobody will ever update.<br>Claude Code gets to the same place but through scheduling and hooks. You can run a prompt or a command on a interval with /loop, you can schedule a cron task, you can fire shell commands at certain points in the agent lifecycle with hooks, or you push the whole thing to GitHub Actions if you want it to keep running after you close the laptop. Same idea exactly, you define an autonomous task, you give it a cadence, and the findings come to you so you are not the one going around checking.<br>There is a second in-session...