AI training for practical team workflows
Hands-on AI training for teams using Claude, ChatGPT, Cursor, and Claude Code on real work.
AI training is hands-on sessions that teach your team to use Claude, ChatGPT, Cursor, and Claude Code on their own work, with their own documents and code. It covers task framing, reviewing output, what not to put into a tool, and when to leave AI out of a workflow. It is for teams that have the licences and are not getting much out of them.
The problem
Most AI training is a demo of impressive-looking outputs on someone else data. People leave interested and go back to their inbox, because nothing connected to what they actually do on a Tuesday.
- Staff use AI for the easy things and never for the work that would save real time.
- One person is very good with it and the practice never spreads past them.
- Output gets pasted straight into client-facing work without anyone checking it.
- Nobody is sure what is safe to paste in, so cautious people avoid it entirely.
- The company pays for licences that mostly go unused.
What we build
Workshops on your real work
Sessions built around the documents, spreadsheets, tickets, and code your team handles, with sensitive details controlled rather than replaced by toy examples.
Task framing that works
How to give a model enough context to be useful, why most disappointing output is an input problem, and how to tell the difference.
Review habits
Practical verification for each kind of output, and recognising the specific ways models are confidently wrong. This is the part that protects quality.
A prompt library that survives
Reusable patterns for your recurring tasks, stored where the team already works, written after the process is understood rather than before.
Engineering sessions
Claude Code and Cursor used against your actual repository, covering where AI coding assistance helps and where it produces plausible code that fails review.
Clear boundaries
What goes into which tool, what never does, and who to ask. Specific enough to follow on a busy day.
What you get at handoff
- The prompt library, in your own workspace, ready to extend.
- Session recordings and written notes for people who join later.
- A one-page usage guide covering the boundaries.
- A shortlist of workflows worth automating properly, spotted during training.
- Follow-up session to catch what did not stick.
Stack
Assistants
Claude, ChatGPT, Copilot
Engineering tools
Claude Code, Cursor
Formats
Half-day workshops, Role-specific sessions, Follow-up clinics
Materials
Prompt libraries, Review checklists, Usage guide
Related services
FAQ
Is this useful for non-technical staff?
That is usually where it pays off most. Operations, sales, and admin teams handle exactly the language-heavy work these tools are good at, and they rarely get training aimed at them. The sessions are organised by the work, not by technical level.
Do you use our real documents?
Yes, with sensitive details controlled. Training on invented examples is the main reason AI training does not stick. We agree in advance what can be used and how.
What if leadership is worried about quality?
That concern is reasonable and the review habits are the answer. A team that knows how to check output produces better work than one that either pastes it straight through or avoids the tools out of caution.
How long does it take?
A half day covers one team on one category of work. Larger rollouts usually run several role-specific sessions plus a follow-up a few weeks later, which is when the useful questions surface.
Will this actually change how people work?
Only if the workflow changes with it. Training alone fades. That is why the sessions produce a prompt library in your own workspace and a list of workflows worth automating properly, rather than just a slide deck.
Ready to scope AI Training?
Send the workflow, tool stack, or reporting problem. We will tell you what should be automated, what should stay manual, and what is worth building first.