Learn a practical seven-step method for getting what you know out of your head and into AI, so you can use your expertise with more clarity, consistency, and capacity without losing the judgment that makes the work yours.
THE CLAXTONFounders, operators, sales leaders, creatives, and team leaders who know AI could be more useful than it currently is.
This includes people who are brand new to AI as well as people already using ChatGPT, Claude, or similar tools but who still feel like they are starting over, repeating context, or figuring it out as they go.
You can use ChatGPT every day and still find yourself starting over.
What Makes You Impossible to Replace gives you a practical method for sorting through that.
Instead of chasing every new tool, you will learn how to get more of what you already know into a form AI can actually support.
Your expertise is still the most valuable part of the system. AI can help you extract it, preserve it, apply it more consistently, and give it more capacity.
Seven steps for turning what you know into a more intentional, AI-supported way of working.
Get the thinking, knowledge, context, questions, and messy information out of your head and into something AI can work with.
Understand what you are actually trying to solve before asking AI to solve it.
Give AI the relevant history, knowledge, information, and boundaries it needs without dumping everything into one place.
Give AI evidence of how you think, write, request, explain, and communicate so it can support your work more accurately.
Turn useful corrections and repeated learning into context or instructions that can actually be reused.
Understand how prompts, Skills, Projects, connectors, and outputs can work together and how much capability the job actually needs.
Separate the work AI can support from the judgment, relationships, taste, leadership, accountability, and decisions that still need you.
The goal is not more AI. The goal is more capacity for the work that matters.
This course gives you a method you can keep using long after the two live sessions are over.
Give AI more of your actual thinking instead of relying on short, generic prompts.
Move from a vague frustration or idea to a clearer problem AI can actually help you work through.
Understand when AI needs more context and where that context should live.
Build and use an AI Project around a real body of work without treating one giant chat as a knowledge system.
Teach AI more about how you communicate, evaluate its output, correct what is wrong, and turn useful corrections into reusable instructions.
Understand the difference between prompts, Skills, Projects, connectors, and artifacts and how they can work together.
Recognize the difference between an AI assistant, a trained partner, a connected partner, and a proactive partner without assuming more automation is always better.
Decide what AI can prepare, what another person should own, what might eventually be automated, and what still requires your judgment.
Two live 60-minute sessions, one week apart
Start with the work already living in your head. Learn how to give AI more complete thinking, clarify what you are actually trying to solve, and understand how relevant context changes the quality and continuity of the work.
Learn how to give AI evidence of how you work, turn corrections into reusable learning, understand how the pieces of an AI-supported workflow connect, and decide what should still require your judgment.
Co-Founder + AI Architect, The Claxton Collective
Jandi Swanson is Co-Founder + AI Architect at The Claxton Collective, where she works at the intersection of business strategy, systems, creativity, and AI.
Her approach to AI is practical and deeply human. She is less interested in teaching the newest tool or the perfect prompt and more interested in helping people extract the knowledge, judgment, context, and ways of working that already live in their heads.
Inside Claxton, Jandi uses AI across client work, operations, courses, content, decision-making, and day-to-day execution. The methods in this course come from building these systems in real work, testing them, correcting them, and figuring out what is actually worth making repeatable.
Her goal is not to make people AI experts.
It is to help them use AI to create more capacity while protecting the judgment, relationships, taste, and expertise that make their work valuable.
GHTA member? Contact The Claxton Collective for your 50% member rate.
This course is for people who know AI could be more useful than it currently is.
You may be completely new to AI, or you may already use ChatGPT or Claude regularly but still feel like you are starting over, repeating context, or piecing together your own process.
No technical background is required.
No.
This course stands on its own and begins with the foundational concepts you need to use the Claxton Seven-Step Build.
The course is platform agnostic.
Jandi will demonstrate primarily in ChatGPT and may also reference Claude, but the methodology is designed to transfer across AI platforms.
No.
You can Build Along or Watch First.
If you prefer to focus on understanding the method during the live session, you can recreate the work afterward using the recording and resources.
Yes.
Course participants will have access to the session recordings for 90 days after Session 2.
You will leave with a practical method for getting more of your expertise into a form AI can support.
You will understand how to work through the Claxton Seven-Step Build, how the major AI building blocks fit together, and how to decide what AI should support versus what should still require you.
Yes.
GHTA members receive 50% off the standard course price.
Contact The Claxton Collective for the member rate.
Learn the Claxton Seven-Step Build and start creating more capacity without giving away the judgment that makes the work yours.
ENROLL NOWJump back in where you need to go.
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