You’re already giving your content workflows feedback. Every time you edit a draft, fix the same awkward transition, or reword a vague heading, you’re providing corrections that an iteration loop can capture, so the next run starts closer to what you’d approve.
I run these loops across articles, LinkedIn posts, video scripts, and landing page copy. When an edit pattern shows up three times across separate pieces, the system proposes an update to its instructions. I approve it, or I don’t. Either way, I no longer manually update agent docs every time output drifts in the same direction.
Here are seven loops, from brief development through post-publish performance. I use Claude Code, but these structures work in any agent framework. You don’t need all of them. If you’re building your first, start with the quality gate (loop 3). Otherwise, start wherever your workflow keeps breaking.
1. The upstream filter loop
Most iteration happens after generation. This loop runs before writing begins.
It’s worth the extra step because a weak angle is the most expensive failure in the pipeline. By the time it reaches a finished draft, you’ve spent a full pipeline run plus your own review time discovering what a strategist agent could have told you upfront.Â
I run mine on angles I’m considering pitching to outside publications, where a killed angle costs nothing, and a bad pitch costs an editor’s trust.
The strategist agent evaluates the brief or angle against defined criteria before anything is written and issues one of three verdicts:
- Pass: Proceed to writing or pitching, depending on the workflow.
- Revise: Something specific needs to change first. The angle is too close to a piece you’ve already published, the thesis is too broad to support, the topic fits, but the audience is wrong, or the argument needs a proof point you haven’t gathered yet.
- Kill: The angle can’t be fixed with revision. There’s no original point of view, or the source to support it doesn’t exist. The agent documents why, and the rationale is logged.
The kill log is where this loop pays off. After enough runs, it shows which angle patterns consistently fail without anyone reviewing individual verdicts.
Before you build this, define:
- Evaluation criteria: Original point of view, thesis strength, and audience fit requirements.
- What triggers each verdict.
- Where verdicts and kill rationales get logged.
Dig deeper: How to build a Claude Code-powered second brain for agency work
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2. The retrieval refinement loop
In a standard pipeline, a research agent retrieves sources, the writer uses them, and problems surface at the end…
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