01 · Why we exist

The tools got good faster than anyone learned to use them.

Powerful AI landed on the average desk before anyone worked out what to do with it. You can see the result everywhere. A few people get a great deal out of these tools. Most tried them once, weren't impressed, and went back to doing things the old way.

That gap has nothing to do with how clever you are or how senior you are. It comes down to a handful of habits that are easy to learn and almost never taught.

A man sitting back from his laptop with his arms folded in a quiet office
Hands marking a printed page with a pen, a laptop open behind

02 · What AI literacy means

Knowing what to ask for, and knowing what to trust.

AI literacy is knowing what these tools can actually do, how to ask them for work you can use, and how to tell a good answer from a convincing one. None of it involves writing code. It is much closer to briefing a new colleague than to programming.

Getting an answer is the easy part. Judging it is the skill. These tools sound just as sure of themselves when they are wrong, so what matters is knowing where a number came from, noticing what is missing, and being willing to push back.

03 · How we teach

Five rules we don't break.

  1. We show it, we don't talk about it

    Every idea gets demonstrated live before anyone discusses it. If we can't show it in two minutes, we drop it.

  2. Real documents, not neat examples

    You work on the kind of files you deal with every week, mess included: column names that don't match, dates in three formats, totals sitting in the middle of the data.

  3. Nothing gets taken on trust

    Every exercise ends with someone tracing a number back to where it came from. When the model gets something wrong and sounds certain about it, we stop and look at it together.

  4. Agree the shape before the content

    Ask for the outline of a document before you ask for the document. It saves more time than anything else we teach, and it's the habit people keep.

  5. You leave with something that runs again

    Every course ends by turning what you built into written steps and a scheduled task, so it still works next month without you.

A small group around a table with laptops open, one person pointing at a colleague's screen

See what that looks like in practice.

Our core programme is where all of this actually happens, hour by hour.

See upcoming trainings