Your team, taught to use AI on the work they actually do.
Not a prompt workshop. We train your people inside their own systems, on their own jobs — and leave them able to create their own tools for the work nobody else understands well enough to scope.
in the room
Taught in person, on your own work.
Sessions run with the people who will actually use it, in the systems they already work in. Small groups, real jobs on the table, and time to try it while someone who has done it before is still in the room.
The habit first. The tools after.
Four things, in this order. Each one is useless without the one before it — which is why teams that jump straight to tool-making end up with a pile of half-working scripts nobody trusts.
Where AI belongs in the day — and where it doesn't
AI helps most when it changes a few specific jobs, not when it is used for everything. We start by finding those jobs in each person's actual week, so the training has somewhere to go.
Context is the whole game
How to give AI what it needs: the documents, the worked examples, the house rules and the tone. The gap between a mediocre answer and a usable one is almost always the input, not the model.
Checking the work
How to spot the confident wrong answer. What has to be checked before it leaves the building. Which jobs should never be handed over at all. This is the part that makes it safe to let people loose.
Making their own tools
Once the habit lands, people start making small tools for their own jobs — the ones never big enough to scope. We show them how, and where the line sits between a personal tool and something that belongs on the roadmap.
Small groups, real work, someone left holding it.
Per cohort, per department, on your own work. The shape flexes with how many people you have and how far along they already are.
Baseline
A short, honest read on where each team really is. Nobody starts in the same place, and pretending otherwise is why generic training fails.
Sessions by department
Small groups, run on live work in their own systems. Sales does sales work; finance does finance work. No shared sandbox exercises.
AI champions
One or two people per department who carry it after we leave, with a standing line back to us for the questions that come up later.
A library they own
The prompts, patterns and tools your team collects along the way, kept somewhere they control — so it survives people leaving.
Team trainingPrompt & tool libraryIn-house AI champions
Three ways this fails — worth knowing first.
Most people reading this have sat through AI training that changed nothing. Here is when that happens, so you can tell whether now is the right time.
Training without live work doesn't stick
If there is nothing waiting on Monday, it evaporates inside a fortnight. Adoption runs alongside real solutions, not as a standalone away-day.
Scattered data stalls it
If nothing is written down and the data lives in six places, your team will hit the same wall we would. That is what Identify is for — do it first.
Nobody becomes an engineer in six weeks
The goal is capable people who make genuinely useful small tools. It is not an in-house development team, and we won't sell it as one.
Start at Identify
If the data is scattered and nothing is written down, adoption stalls. Identify tells you what is worth fixing first — and whether your people are the bottleneck at all.
Start with the free quiz.
See how you stack up, and what to do about it. Two minutes.