AI Training for Teams

AI tools are available to everyone today, but a licence alone does not make a team work better. Some people use them heavily, some not at all, and few know which data they are allowed to enter. We run hands-on training after which the team knows what AI is good for in their work, how to use it and where the limits are.

01Who the training is for

We train technical and non-technical teams. We always tailor the programme to the group, because a sales team, a customer service team and developers all work with AI differently. We run three formats:

• Workshops for teams. Working on the tasks the team does every day. Participants leave with concrete ways of working, not a list of curiosities.
• Training for non-technical departments. Working with text, analysing information, preparing documents, emails and summaries, and judging when an AI result can be trusted and when it needs checking.
• AI for developers. Coding assistants in daily work, code review and writing tests with AI, and building your own solutions on top of language models.

02How we prepare the programme

Before the training we talk to a person on the company side about what the team does, which tools it uses and how much experience it has with AI. We also ask for examples of typical tasks. Based on that, we put together the programme and the exercises. Participants work on situations similar to their own, not on generic examples from the internet.

Most often we work with ChatGPT, Claude and GitHub Copilot. The choice of tools depends on what the company uses or plans to use. If the company has already chosen a tool, the training focuses on it.

03What participants learn

The foundation is the ability to frame tasks well: how to describe the context, the goal and the expected format of the result, how to work with a model in several steps, and how to refine a result instead of starting over. We also show enough of how models work to understand their limits: where errors come from, why a model can answer confidently and incorrectly, and how to catch it.

The second pillar is security. We discuss which data can be entered into AI tools, what privacy settings the different tools offer and how to set simple rules for using AI in the company. If the company already has a policy on this, we build on it.

For developers we go further: coding assistants in the editor, generating and reviewing tests, working with documentation and refactoring. We also talk about where an assistant speeds work up, where it can slow it down, and how to review code you did not write yourself. We write more about this in our post on whether AI will replace programmers.

04After the training

In workshops for technical teams we introduce prompt engineering and RAG, the basics of building your own solutions on top of company knowledge. If after the training you want someone to keep choosing and setting up AI tools and testing new models and features, we do that as part of our AI Tools for Business service.

Want to train your team in AI tools? Tell us what your team does and which tools it uses, and we will propose a programme.