​Your team's AI tools. Built before training begins.
Most AI training produces awareness. This produces capability. I spend weeks inside your organization building custom AI agents from your actual documents — then teach your team exactly how those agents were built, how to improve them, and how to build new ones from scratch. By the end of the engagement, your team are your organization's internal AI experts. The tools stay. The knowledge stays. The dependency on me doesn't.
About Chris Pearson
Chris Pearson is an AI adoption consultant based in Houston, Texas. He holds an MBA, a PMP certification, and has spent 20 years managing enterprise technology across industries — including a co-authored AI whitepaper with UC Berkeley.
ChatCPt, LLC exists because most AI training doesn't produce adoption. It produces awareness.
Chris built the discovery-first methodology to close that gap — starting with your organization's real documents, real workflows, and real use cases before any training begins.
The measure of a successful engagement isn't whether your team liked the training. It's whether they're still building six months later without picking up the phone.
A Different Kind of AI Engagement
Discovery
I embed in your organization before any training begins. I attend your existing team meetings, collect your actual documents, and map the workflows where AI will save the most time. Then I pre-build your first AI agents — trained on your materials, structured around your voice, ready to use on Day 1 of training. These are your proof of concept. They exist to show your team what's possible with their own content, in their own language, before anyone has to imagine it.
TRAINING
Day 1 covers the fundamentals: how AI works, prompt engineering using the RTF framework, and ethics and governance. Day 2 is where the transfer happens. Your team opens the pre-built agents, sees exactly how they were built, and learns that there's no code — just clear direction in plain English. Then they build. They modify existing agents. They create new ones. They leave not as AI users but as AI builders — with the frameworks and hands-on experience to keep building long after the session ends.
Adoption Support
Three monthly working sessions over 90 days. Month 1 handles early friction. Month 2 introduces advanced techniques: Critique Mode, data analysis, voice extraction for new use cases. Month 3 is a deliberate handoff. Champions take the lead. New agents get built for workflows we didn't touch in training. By the end, your internal experts are fielding peer questions, improving existing agents, and building new capability without me. That's not a side effect of the engagement. That's the goal.