@SilenceCaPrompt: Loop engineering is not a single thing. It consists of four distinct structures, and each serves a different type of ta…
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The article outlines four distinct loop structures for AI agents: turn-based, goal-based, time-based, and proactive, each delegating different aspects of task direction to the system.
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Cached at: 07/16/26, 02:02 AM
Loop engineering is not a single thing. It consists of four distinct structures, and each serves a different type of task.
Designing the loop means building the system that directs the agent instead of you directing it yourself, step by step.
This system always responds to two questions: what triggers the execution, and what decides that the work is finished.
In a manual session, it’s you who answers both, every time. Each type of loop shifts one more part over to the system.
→ turn-based: it’s your prompt that launches it. The agent gathers the context, acts, and checks its work in a single turn. Then you reread the output and write the next prompt. Use it when the needs are still taking shape and each result changes what you were going to ask for next.
→ goal-based: it’s a /goal command that launches it, with success criteria and a budget. “Get the Lighthouse score of the home page to 90, stop after 5 attempts.” When the agent tries to stop, an evaluator model checks if the goal is achieved and sends it back to work if the answer is no. Use it when the outcome is measurable but the path doesn’t deserve your attention.
→ time-based: it’s a clock that launches it. An interval triggers a fixed prompt of the type “check the PR, fix the CI” and waits for the next tick. /loop runs on your machine, /schedule deploys it to the cloud and it survives with the laptop closed. Use it for recurring work where the task is known in advance and only the schedule repeats.
→ proactive: it’s an event or a calendar that launches it, with no human in front. A routine monitors a channel and when something requires action, it spins up a workflow with a triage agent, a fix agent, and a reviewer that judges the result adversarially before closing the task. Use it for permanent responsibilities where you can’t predict what will happen, only that something will.
Each type delegates one more task than the previous. Turn-based leaves both in your hands, goal-based automates the checking, time-based automates the triggering, and proactive automates both while deciding the shape of the workflow at execution time.
The question isn’t which loop is the most advanced. It’s whether your task is exploratory, measurable, recurring, or permanent.
The more you delegate, the less you monitor.
The full breakdown on loop engineering is cited below
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