AI literacy training
AI skills, taught on your own work.
Most AI training shows a polished demo and leaves the room unchanged. Ours runs on tasks your team already does, with tools that fit your budget, so what they learn on Tuesday they can use on Wednesday. By the end, everyone knows what the tools are good for, what they get wrong, and what must never be pasted into one.
Fit
Signs the time is right
None of these needs a crisis to justify training. They are the ordinary signs that the tools arrived before the ground rules did.
- A few people at the company quietly use ChatGPT, and nobody has agreed on what is safe to put into it.
- AI-written text has started reaching customers without anyone reading it first.
- You bought licenses months ago and most of them sit unused.
- Someone pasted a customer’s information into a chatbot, and you heard about it afterwards.
- You want the team using these tools, but every article you read contradicts the last one.
- A system is being built for your business, and one of your people will be running it.
The sessions
What the training covers
Each item below is either a session of its own or a thread that runs through all of them. Together they are the difference between a team that has seen AI and a team that can be trusted with it.
Your tasks, not demos
Before the first session we collect a handful of things your team actually does: a quote to write, a contract to summarize, an inbox to sort. The sessions are built around those, and people work on their own examples in their own accounts. A canned demo always succeeds, which is exactly why it teaches nothing. Watching a tool struggle with your messiest real document is worth more than watching it ace a rehearsed one.
Choosing tools
There are more AI products than anyone can evaluate; a shortlist of two or three is the aim. We shortlist against what you already run and what you are willing to spend each month, then try the shortlist on your own tasks before anyone commits to a subscription. Sometimes the honest pick is the cheap general-purpose chat tool over the expensive specialist one. What matters is that the decision comes from your work, not from a vendor’s marketing page.
Prompting, and its limits
Good prompting is mostly ordinary clarity: name the task, give an example, describe what the output should look like. We teach a small set of habits that covers most everyday use. Then we spend just as long on the limits, because there are questions no phrasing can rescue, and there is a point where rewriting the prompt takes longer than doing the task yourself. Knowing where that point sits is the skill.
Checking the output
These tools produce confident text whether they are right or wrong, so the ability that matters most is knowing when to verify. We practice it directly: the team reviews AI output on their own subject matter, hunts for the errors, and learns which kinds of task fail quietly. The rule we leave behind is plain. The harder it would be for you to check an answer yourself, the less weight it should carry.
Data boundaries
Every session covers what never goes into a chat window: customer information, employee records, passwords and keys, anything a contract or a regulation covers. We put it in writing as a short list matched to the specific tools you chose, because the safe answer differs between a consumer chatbot and a business account with training switched off. People break vague rules. They keep short, specific ones.
Running what we build
When we build a system for a client, someone on their staff operates it afterwards: reviewing what it drafts, approving anything a customer will see, noticing when its answers start to drift. Training that person is part of every build, and it is available on its own. They practice inside the running system itself, and they learn what it may do alone, what it must hand to a human, and what to do when it behaves strangely.
The shape
From scoping to follow-up
Scope
A short call to settle who is being trained, what they do all day, and which tools are already in use, sanctioned or not. The price is set here, before anything is scheduled. If training is not the right spend for you yet, this call is where we say so.
Prepare
We collect real material from the team, the documents and emails the sessions will run on, and draft the session plan and the safe-use list. You review both before the first session and can pull anything you would rather not have in the room.
Sessions
Small groups, everyone at a keyboard, working their own examples in the tools you picked. Each session ends with the group producing something they would otherwise have made by hand, so the point of it is visible the same day.
Follow-up
The reference material is handed over and we stay reachable while the habits settle. A few weeks in, questions surface that nobody thought to ask in the room; answering those is part of the engagement, not an extra.
What you keep
What stays behind
Training that lives only in memory fades by the next busy week. Everything here is written down, belongs to you, and is meant to outlast the sessions.
- A one-page safe-use list, specific to your tools, stating what never goes into a chat window.
- A prompt reference built from your own tasks during the sessions, not copied from a template.
- The tool shortlist, with monthly costs and the reasoning behind each pick.
- A team that has done the work once with the tools, not just watched them demonstrated.
Next step
Talk it through first.
Your team is probably using these tools already, with or without ground rules. An intro call covers what the sessions would look like for your business and what they would cost.
Book a call