Here’s something I see all the time:
A leader wants to automate prospect research. Or customer outreach. Or content creation. They’ve done the process hundreds of times. They know it works. But when they try to apply AI?
They get stuck.
Not because the AI isn’t capable. But because they’ve never had to explain their process with the kind of precision an AI needs. The workflow lives in their head as intuition—not as clear, repeatable steps.
On Friday, I hosted a Lightning Lesson where we tackled this together. Over 340 leaders and professionals joined me to walk through how to take something you know intimately and break it down so AI can actually execute it.
No theory. Just a real workflow, deconstructed step by step.
The Challenge: Getting What’s in Your Head Into Structure
Think about something you do regularly in your business. Maybe it’s qualifying leads. Analyzing feedback. Preparing reports.
Now imagine explaining every single step to someone who’s smart but has never done it before. Not just the what—the how, the why, the decision points, the nuances.
Suddenly it’s not so simple, right?
That’s the gap. You have expertise that’s second nature. AI needs explicit instructions. Deconstruction is how you bridge that gap.
And honestly? The process of breaking it down often reveals things you didn’t even realize you were doing—which makes your process better, with or without AI.
What We Built Together
In this session, I walked through a workflow I use for LinkedIn prospect research. Nothing fancy—just a practical business process:
Start with a buyer persona (the kind of prospect you want to find)
Search LinkedIn for people who match that profile
Evaluate each prospect against specific criteria
Generate personalized engagement recommendations
Output everything in a structured format
The interesting part isn’t the workflow itself. It’s how we approach building it.
Key Concepts You Can Apply Immediately
1. The “What/Why vs. How” Principle
You shouldn’t be writing detailed AI instructions from scratch. That’s the old way.
Instead, you define the business outcome and sketch high-level steps. Then let AI generate the detailed execution instructions.
You bring domain expertise. AI brings execution precision. Stay in your lane.
2. Meta-Prompting: Let AI Write AI Instructions
Here’s the actual technique:
“You are an expert workflow designer and prompt engineer. Please write a prompt for this scenario. The outcome is [your goal]. Here are the high-level steps: [your steps]. Now write the detailed instructions.”
Let the model craft the “how” while you focus on the strategic “what and why.”
I demonstrate this live in the session—you’ll see how much better the AI-generated instructions are than what most people write manually.
3. Skills vs. MCPs: Understanding the Difference
This came up multiple times in Q&A because it’s genuinely confusing.
Skills teach Claude how to do something. Procedural knowledge. “Here’s how to write a LinkedIn post in my style.”
MCPs (Model Context Protocol) give Claude access to something. Tool connectivity. “Here’s how to read from and write to my Notion database.”
They work together. Skills provide the methodology. MCPs provide the capability.
4. Build a Workflow Registry
Don’t just build workflows ad hoc. Create a system.
I show my Notion setup where every workflow is documented with:
Name and business process assignment
Description and expected outcome
Trigger conditions
The actual steps
Links to AI assets (prompts, personas, templates)
Status tracking
This becomes your institutional knowledge. Your competitive moat.
5. The Clarity Test
Here’s how you know if a workflow is ready to automate:
Can you explain it clearly enough that a smart person who’s never done it could execute it successfully?
If not, you’re not ready for AI yet. The work is in the deconstruction, not the automation.
6. Create Reusable AI Assets
In the demo, I use a buyer persona stored as a markdown file. It’s an AI asset I can plug into multiple workflows—prospect research, email outreach, and content creation.
Think in building blocks. What pieces of knowledge or context can you document once and reuse everywhere?
Questions That Came Up
The Q&A was where things got practical. People asked questions like:
“Should I design my Notion database first, or let Claude do it?” (Start simple with what makes sense to you, then let Claude optimize based on your actual workflow)
“When do I need a Skill versus just a good prompt?” (Skills when you’re doing the same thing across multiple workflows and want consistent execution)
“How detailed should my workflow steps be?” (Detailed enough that the AI knows what to do, but not so prescriptive that you lose flexibility)
These weren’t hypothetical. These were people actively working through this in their businesses, hitting real obstacles, finding real solutions.
Why This Matters Right Now
We’re past the “playing around with ChatGPT” phase. The tools are ready. The question isn’t whether AI can help your business—it’s whether you can articulate your processes clearly enough to take advantage of it.
The leaders who figure this out aren’t necessarily the most technical. They’re the ones who can think operationally, break down their expertise, and build systems that scale.
That’s what this Lightning Lesson is about. Not the technical wizardry (though we cover that too). The mindset shift from “What can AI do?” to “What do I need done, and how do I break it down?”
Want to Go Deeper?
This Lightning Lesson gives you the approach. If you want to actually build these systems with hands-on guidance and expert feedback, I’m running two cohort courses:
Claude and Claude Code for Builders – Starts Tomorrow (January 26)
This course is primarily for “builders” - business people who want to go deep on Claude’s capabilities, Claude Code for agentic workflows, and building a prototype application (e.g., website)
25% founder discount for this inaugural cohort.
Hands-on Agentic AI for Leaders – Next cohort starts February 2
This is for business leaders and non-technical builders who want to move from experimentation to actually deploying AI in their operations. We build real workflows, deploy them, and develop the literacy to lead AI transformation.
Rated 4.8/5. Over 250 students trained.
The best AI implementation starts with clear thinking about your business, not with fancy prompts.
Watch the session. Pick one workflow. Break it down.
That’s where real progress starts.
— James
