Audit the work
We start with the work, not the tools. Together we break a live process into steps, find the repeated effort and mark where human judgement must stay. That gives the session a real backlog instead of a list of generic prompts.
AI training for commercial teams
Practical ChatGPT and Claude training for business teams. We audit the work, run a tailored session, leave reusable tools and set a 30-day landing plan so the learning moves into actual use.
Generic AI training starts with features and ends with inspiration. This starts by finding where the hours go. The live session then uses examples people recognise, and the landing plan gives each team a first action, an owner and a date.
We start with the work, not the tools. Together we break a live process into steps, find the repeated effort and mark where human judgement must stay. That gives the session a real backlog instead of a list of generic prompts.
One live session, rebuilt around the people in the room and the work they own. The team practises with its own examples in ChatGPT, Claude or the approved company tool, then judges the output against a clear quality bar.
The session leaves tools people can use: a Click Audit worksheet, the four Cs crib sheet for reviewing AI-assisted work, a one-line quality test and a short glossary in the company's language.
The team agrees five actions for week one, turns its Click Audit into a build backlog and sets a 30-day definition of good. Training ends with owners and work in motion, not a recording nobody watches.
People are using a shared method on real work. A named owner has moved at least one item from the audit into practice. The team can show how it reviews quality, where human judgement stays and what it will build next.
The test is not whether people enjoyed the session. It is whether the work changed.
For a longer build and champion model, see how Deepgrain embeds capability.
Common questions
Tell us which team is in the room, which tools are approved and where the work keeps getting stuck.