Programmes
Every session ends with something built.
Two programmes, one method. Engineers finish with a working, evaluated AI system running against their own problems. Business teams finish with automations they use the next morning. Leaders get a clear view of where AI fits and what it will take.
Designed and taught by a Google Developer Expert and Agentic AI Foundation ambassador who builds with these tools every day.
The method
Learn it, apply it, build it
Every cycle runs the same way. A short piece of self-paced foundation before we meet. A live workshop where we apply it to your work, not a toy example. Then a lab where each person builds the thing themselves. The artifact from one cycle becomes the starting point of the next, and the final week is a capstone your team presents and defends internally.
01
Foundation
Self-paced material before each session, so live time is never spent on things a video can teach.
02
Workshop
A live session applying the skill to your systems, your data, and your constraints.
03
Lab
Each person builds a working artifact on their own, with support between sessions when they get stuck.
For engineering teams
The AI Engineering Programme
A 4–6 week programme that takes a cohort of working engineers from LLM fundamentals to a deployed, evaluated AI system. Provider-agnostic and taught on your stack: the patterns hold whether you build on Anthropic, OpenAI, or Google models.
The arc: how LLMs behave and how to prompt them as an engineering discipline; structured output and API integration; retrieval and RAG over your own documents; agents and tool calling with proper guardrails; evaluation harnesses that fail the build when quality drops; and the security and observability work that separates a demo from a system you can run. It ends with a capstone the team builds and defends.
It starts small: a pilot day with one team, on one real problem. If the day doesn't convince you, stop there.
For business teams
The Applied AI Programme
The same method for the teams around your engineers: marketing, operations, finance, HR. No prompting theory delivered from a lectern. Each person picks a task they actually do every week and, cycle by cycle, turns it into a working AI-assisted workflow.
By the end, the team has automations running in their real tools, the judgement to know what to trust, and the habit of building rather than waiting. Organisations often run this after the engineering programme, so both sides of the company speak the same language.
For leaders
Advisory
A senior pair of eyes for the decisions around the building: where AI applies in your business, build versus buy, vendor evaluation, and regulatory positioning. Available as one-off engagements or as an ongoing retainer after a programme, so the momentum doesn't leave when I do.
Not sure where your organisation stands? Score your readiness in five minutes.
Start
Tell me about your team and what they need to be able to do. I'll tell you what I'd run, how long it would take, and what it costs.