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How to Start Writing Loops for Advanced AI Models like Fable 5 + GPT 5.6 (Clearly Explained)
⏱ 21 min video · 3 min read9 Jul 2026
TL;DR
Creator Chris explains the concept of 'loop engineering' for AI coding agents like Claude Code, Codex, and Cursor — shifting from one-off task prompts to objective-driven loops that run autonomously until a goal condition is met. He also shows how to package loops into reusable skill files, and connects them to external tools for even more powerful automation.
Key points
1
A loop is an objective given to an AI agent that it executes repeatedly through defined steps (plan, build, test, verify) until a specific exit condition is satisfied — removing the human from every intermediate step.
2
Loop engineering requires two things done well: a clearly defined goal condition (the exit criteria) and a well-scoped set of loop steps the agent should follow.
3
Most AI coding agents (Claude Code, Codex, Cursor) support a for/goal feature that explicitly tells the agent to keep working until the goal condition is met.
4
Loops can be saved as reusable skill files (e.g. skill.md) so you can trigger a complex multi-step loop with a single instruction like 'use the design review loop skill'.
5
Advanced 'elite loops' connect skill-based loops to external tools and data sources (e.g. Ahrefs for SEO, PostHog for analytics) to create fully automated, data-driven agent workflows.
Actionable insights
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Start by defining your goal condition first, then work backwards to specify the steps the agent should cycle through — this is the correct order for writing an effective loop.
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Use the for/goal syntax in Claude Code or Codex to formally signal a loop rather than relying on natural language alone, which may not consistently trigger autonomous looping behavior.
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Convert any frequently repeated loop into a .md skill file so you can invoke it with one command; the skill can also define post-loop actions the agent should take after the goal is reached.
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Use loops for knowledge work too (SEO, ad optimization, CRO, research) — not just software development. Any repeatable objective with a verifiable end state is a candidate.
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When unsure how to specify loop steps, ask the agent itself to help design the loop by describing the objective and asking it to outline the step-by-step process a human would follow manually.
Notable quotes
“Instead of putting in a task for the agent to complete, we give the agent an objective. And then we get an outcome back. We are thinking at a higher level of abstraction here.”
“Using this skill, you basically create the documents that you need and then you say build the app using the build MVP skill and it builds the whole app from start to finish. That is really the power of building with loops.”
“Part of this is knowing when to write a task and when to write a loop for your agent that you are working with.”
Worth watching?
⏭️
Worth watching the full video?
The core concepts are fully captured here — if you are a non-technical builder wanting to understand what loops are and how to start using them, this summary gives you everything the video does without the pacing and sponsor segment.
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