AI literacy
AI is changing how work gets done. Learn what it genuinely does, where it quietly gets things wrong, and how to stay ahead of it instead of being unsettled by it.
The position I teach from
One half of the internet insists AI is about to do everything. The other half insists it is a useless toy. Both are selling something, and neither helps you decide what to do on Monday morning.
Here is the honest version. These tools are genuinely, substantially useful for a specific set of tasks: drafting, summarising, explaining, rewriting, translating, working through a problem out loud. They are also confidently, fluently wrong on a regular basis, in a way that is designed to be hard to notice, because the wrong answer arrives in exactly the same tone as the right one.
Which means the skill worth having is not "using AI". It is judgement: knowing which tasks to hand over, and how to check the answer. That is what these lessons are about, and it is not something you get from watching a video.
What we cover
Session one
What is actually happening when you type into one of these things, without the mysticism. Why it makes things up. Why it is superb at some tasks and hopeless at arithmetic. What "training data" means for the answers you get.
Session two
We take real tasks from your job or study and work them through together. How to ask for what you want, how to give it enough context, and how to recognise when the answer is confident nonsense.
Session three
How to verify an answer efficiently. What you must never paste into a chatbot. Copyright, workplace policy, and the difference between legitimate use and the kind that gets people into trouble.
Session four
Where it fits your week, where it does not, and how to keep your own skills sharp rather than quietly outsourcing them. Automating the parts of the job you never liked anyway.
Who this suits
You have watched this arrive in your workplace and you would rather understand it than have it explained to you by someone half your age in a meeting. Entirely reasonable, and easily fixed.
You are already using it. Learning to use it as a tutor rather than a ghostwriter is the difference between getting ahead and getting caught, and more to the point actually learning the material.
You keep hearing about it and nobody has explained it without either patronising you or trying to sell you something. It also happens to be a superb tool for anyone who finds small print and official letters hard going.
The part most courses skip
A confident wrong answer costs far more than no answer at all.
These systems produce fluent, well-structured, authoritative-sounding text regardless of whether the content is correct. They invent citations. They get dates and numbers wrong. They will agree with you when you are mistaken, because agreeing reads as helpful.
People have submitted legal filings citing cases that never existed, because the output looked exactly like every other filing they had read. That failure is not a bug that will be patched next year; it is a property of how the things work.
So we spend real time on verification habits: which claims to check, how to check them quickly, and how to tell the difference between a task where a mistake is harmless and one where it is not. Get that right and the rest is straightforward.
Straight answers
No. The people who get the most out of these tools are usually not programmers. They are people who know their own job well and learn to hand off the tedious parts of it. If you can describe what you want clearly, you can use AI.
Mainly the general assistants (Claude, ChatGPT, Gemini and Copilot) because they cover the overwhelming majority of real use. We use whichever one suits your work, and I will tell you honestly where each is weak.
Sometimes, and this is exactly why the lesson is worth having. Some information should never go into a chatbot: client data, health records, anything covered by your employer’s policy. We cover where the line sits and how to work productively on the right side of it.
I am not going to pretend to know. What is observable is that people who understand these tools are being asked to do more interesting work, and people who refuse to look at them are being left to argue with the ones who did. Learning what it actually does is the cheapest insurance available.
Yes, and it is worth teaching properly rather than pretending it does not exist. Using it to explain a concept you do not understand is study. Using it to write the assignment is cheating, is usually detected, and skips the learning you are actually being assessed on. We cover the difference frankly.
Yes. Small team sessions work well for AI in particular, because most of the value is in discussing where it fits your specific workflows. Get in touch and we will work out something sensible.
