You’ve published for years. Most of it isn’t in your AI workflows.
If you’re an established expert, you’ve likely accumulated years of thinking across blog posts, YouTube videos, and conference talks. Most of it sits unused in your current AI workflows. With the right approach, you can capture that public thinking and turn it into a structured, usable reference in about 10 minutes.
This article walks through a practical method for mapping any expert’s content archive using a free AI skill developed by Kieran Flanagan. The process scans public content, scores key ideas by actionability and clarity, and organises them into a mood board you can actually work with.
What the expert lessons skill does
The skill is a text file containing instructions for AI to follow. It searches the web for an expert’s most important content, downloads video transcripts where available, and scores ideas across dimensions like actionability, clarity, and novelty.
You can download the skill for free from Kieran Flanagan’s blog. It’s designed to work with Claude code, but also runs on OpenAI Codex or Google’s Antigravity if you’re using Gemini.
How to run it
The process is straightforward. Open the downloaded skill file in your preferred AI coding tool. Create a folder and drop the skill file into it. Then instruct the AI to run the expert-lessons.md skill on the expert you want to map.
If the expert is well-known, the AI will find them. For less prominent experts or common names, add context such as company affiliation. The AI will then search for their most important content, pull transcripts from videos, and scan blog posts and talks.
The output is a mood board: a web file you can open in your browser. It includes quotes, application suggestions, links back to source material, and scoring across usability metrics. For an expert like Daniel Priestley of Dent Global, the skill might generate a dozen high-priority lessons, each linked to its original source.
Two clear use cases
You can use this skill in two ways. First, map your own content archive. If you’ve published consistently, this gives you a structured reference of your recurring frameworks and ideas, ready to integrate into your AI workflows.
Second, study another expert’s thinking. If you want to understand how a particular expert approaches their domain, this skill captures their public frameworks quickly and systematically.
The mood board isn’t the final deliverable. It’s a starting point. In a future article, we’ll explore Kieran’s follow-up skill, which takes these lessons and generates new AI skills based on the expert’s frameworks.
What works and what doesn’t
This approach works best when there’s substantial public content to pull from. Established experts who publish regularly will generate rich, detailed mood boards. If you’re early in your publishing journey or keep most of your content private, the output will be limited.
The skill only works on public content. Private client documents, proprietary methodologies, and internal archives won’t be touched. If that’s where your most valuable thinking lives, you’ll need a different approach.
Always validate the output. The AI scores ideas based on patterns it identifies, but your judgement matters. Check that the flagged content aligns with what you actually consider your best work or most actionable frameworks.
A practical step toward usable knowledge
For expert-led businesses, structuring knowledge is a persistent challenge. This skill offers a practical way to take years of scattered thinking and turn it into something you can reference, refine, and build on. It’s not a replacement for deeper knowledge management work, but it’s a useful starting point that takes minutes rather than months.
