Your team is learning AI alone.

I give them the roadmap for learning coding agents they've been looking for.

Why now

The way knowledge work gets done is changing.

Your competition is learning AI. They’re shipping in days what used to take months, and the gap widens every week. These tools are already reshaping how work gets done. The move is to get ahead of that curve before you spend the next two years playing catch-up.

The tools are finally trustworthy enough to build real work on. Your existing people can produce production output at a speed that didn’t exist eighteen months ago. The bottleneck now is getting your team past the chat window and into the way these tools actually want to be used: context, prompting, and agent architecture. That’s where most teams stall, and that’s where I come in.

What I do

What I install

Three pillars, delivered in order. Each one multiplies the next.

  1. Get the right tools in the right hands, and the team aligned behind them.

    Most teams have licenses but no standardized method for onboarding and understanding these tools. My first-principles approach to learning coding agents will allow the whole team to have a shared setup and understanding, meaning everyone learns together.

  2. Build the skill set that outlasts the current tool.

    Working with AI is a discipline, and the people who treat it that way pull away from everyone else. This is where the MACHINE curriculum does the work. Seven pillars taught from first principles, so your team learns the mechanics of working with agents instead of just picking up the latest fads. They walk away with quality output in real production-level environments with these tools, not just demos.

  3. Build the automations that run the work for you.

    Once your team knows the tool, the next layer is building agents that automate and streamline work for you. I help architect that layer, including the workflow, guardrails, and tooling. The end state is a small team producing the output that used to require a much larger one, with your people focused on the judgment calls instead of the keystrokes.

The curriculum

The framework that I teach: MACHINE.

AI has real depth as a skill, yet people don't treat it that way due to the approachable interface, and they pay the technical debt down the line. MACHINE is the seven-pillar, first-principles framework I teach AI through. It is designed to be provider agnostic for when the tools change.

  1. Mapping

    How to plan and scope work with agents.

  2. Agents

    How to create AI agents and orchestrate them to do work.

  3. Context Engineering

    How to optimize what is in the model’s active memory.

  4. Harness Engineering

    How to understand Claude Code and build robust automations.

  5. Intuition

    Knowing how AI works and the failure patterns, so you can prevent them before they happen.

  6. Natural Language

    How to prompt engineer effectively.

  7. Engineering

    How traditional engineering mixes in with AI.

How I engage

High-touch cohort engagements.

Engagements typically run six to twelve weeks, cohort-style and high-touch. Tailored material, live application sessions, and Q&A, structured as a hands-on program so the team applies it to their own workflows and sees it working quickly, instead of figuring it out alone.

Proof

Where this has already worked

Direct testimonial

“Our team was absorbed in a merger. Everyone left and I was the only one still there, training their replacements. AI was the only way I could carry the team’s workload while the new hires came up to speed. When I started working with Roman, my output went roughly 5x. I ran my first internal AI workshop using his frameworks, and 50 people showed up. Now I’m building a fully automated PR-review pipeline so I can stop spending my day monitoring my team’s output.”

Peter Pruchnerovic DevOps engineer, regulated European enterprise

Engagement outcomes

Who

About

I’m Roman Colman. I worked at Los Alamos National Laboratory in AI research. I have three published papers, including an IEEE publication and a NeurIPS spotlight, which is a top 3% paper at the world’s premier AI conference. I’ve put over three thousand hours into Claude Code, and I turned that obsession into The Agentic Lab: a community and movement with thousands of members.

I spend much of my time scaling my business using Claude Code for development of internal tools and automations, marketing, outreach, and research. The other large portion of my time is spent helping The Trajectory Engineers, a cohort of real business owners and software developers building real businesses and software with coding agents.

Build a team that understands the tool of the future.

If you’re a CEO, CIO, or fractional CIO looking at a team with the licenses but not the leverage, let’s talk. One call, peer to peer. We figure out whether this is the right fit before anyone signs anything.