@Maxsteinbrenner: Prompt engineering has been replaced by loop engineering. What is it? (Explained in 60 seconds) For the past 2 years we…

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Summary

Explains the shift from prompt engineering to loop engineering, where AI agents are given goals and iterate through recursive loops (research, draft, evaluate, test, improve) until meeting standards, with open, closed, and orchestrated looping approaches.

Prompt engineering has been replaced by loop engineering. What is it? (Explained in 60 seconds) For the past 2 years we have been prompting agents with individual tasks. That is starting to change. So far, if you wanted an agent to build a dashboard for a client, you would give it a task, review the output, improve the prompt, and repeat the process until the work was done. Looping changes that. Instead of giving an agent individual tasks, you give it a goal and let it work through a recursive loop until that goal is met. For example: → Research → Draft → Evaluate → Test → Improve → Repeat The agent keeps cycling through the loop until it reaches the standard you defined. Within loop engineering there are two main approaches: 1. Open Looping You give the agent a goal and allow it significant freedom in how it achieves it. This is powerful, but also expensive and harder to control. 2. Closed Looping The human defines the architecture, constraints and evaluation criteria. The agent is then responsible for executing, improving and iterating within those boundaries until the goal is reached. The next evolution is orchestrated looping. Instead of a single agent running a loop, one agent breaks the goal into smaller tasks and assigns them to specialist agents. Each specialist runs its own loop and reports back. In other words: You move from one agent improving itself to an entire team of agents iterating together until the goal is achieved.
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Cached at: 06/10/26, 12:24 AM

Prompt engineering has been replaced by loop engineering. What is it? (Explained in 60 seconds)

For the past 2 years we have been prompting agents with individual tasks. That is starting to change.

So far, if you wanted an agent to build a dashboard for a client, you would give it a task, review the output, improve the prompt, and repeat the process until the work was done.

Looping changes that.

Instead of giving an agent individual tasks, you give it a goal and let it work through a recursive loop until that goal is met.

For example:

→ Research → Draft → Evaluate → Test → Improve → Repeat The agent keeps cycling through the loop until it reaches the standard you defined. Within loop engineering there are two main approaches:

  1. Open Looping You give the agent a goal and allow it significant freedom in how it achieves it. This is powerful, but also expensive and harder to control.

  2. Closed Looping

The human defines the architecture, constraints and evaluation criteria.

The agent is then responsible for executing, improving and iterating within those boundaries until the goal is reached.

The next evolution is orchestrated looping.

Instead of a single agent running a loop, one agent breaks the goal into smaller tasks and assigns them to specialist agents.

Each specialist runs its own loop and reports back.

In other words:

You move from one agent improving itself to an entire team of agents iterating together until the goal is achieved.

Peter Steinberger 🦞 (@steipete): Here’s your monthly reminder that you shouldn’t be prompting coding agents anymore.

You should be designing loops that prompt your agents.

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