AI adoption, one rung at a time
Get productive with AI. Then get the evidence to trust it.
Hands-on teaching for individuals, teams and leaders, from a solution architect who builds and runs production AI. Remote anywhere, onsite in the UK. No hype, no tool to sell you.
The ladder
Four rungs. You earn each one.
Autonomy is earned, not granted. Most people and most companies are either stuck on the first rung, or have jumped to the fourth without earning it. Both cost you: the first in time, the second in trust.
Who it is for
Same ladder, different starting rung.
An individual usually needs to get from rung one to two and stay there. An engineering team with agents in production needs to get to four honestly. The work is different; the method is the same.
How it works
Find your rung. Earn the next one. Prove it stuck.
01
Find your rung
A short conversation, or for organisations a week of looking at the real work. Not a survey. We find where you actually are, task by task, and what is holding you there.
02
Earn the next one
Hands-on, on your own work, with your own tools. Prompts become assets, failures become checks, checks become evidence. You leave with things you keep, not slides.
03
Prove it stuck
A follow-up two weeks later for teams, a measured before-and-after for engineering, a written plan per team for leaders. If it did not stick, we find out why.
Why listen to me
I teach what I have run in production, and I publish the numbers.
Six people, from zero to productive
A tech lead, two data engineers, a CTO, a senior programmer and one more. All started from nothing. All use AI every working day now. They are the reason this site exists: three of them told me to build it.
Production AI, not slideware
I build and run AI systems at Cedar & Bloom: an AI news platform and a careers service, with agents, retrieval, evaluation suites and a measured cost model. When I teach a method it is because I have run it and watched it fail first.
Open-source reference repos
Evals and observability as a CI gate. A resumable, cost-aware LLM pipeline. An MCP server that ships with its own eval suite. A repository habits analyser. All MIT-licensed, all yours to keep after a session.
Fourteen published field notes
Nine engineering pieces on what survives production, and five on what AI does to the people around it. Every number in them is measured or labelled as modelled. Honesty over hype is the whole editorial policy.
Twenty-plus years of delivery
Tech lead and solution architect for insurers, banks, automotive, SaaS and media, through my own consultancy. I have been the person in the room who had to make the plan work, not the one who presented it and left.
Tell me which rung you are on.
A short message is enough. Say who you are, what you are trying to do, and whether you want remote or onsite. I reply within two working days.