Cut through the jargon. This session gives you a clear picture of how AI tools work, what they’re good for, and where to begin.
There are three things people in our sector tend to say about AI: that it will replace jobs, that it’s overhyped, and that it’s too risky for regulated work. All three are partly right. All three are mostly unhelpful.
In this session, Aptem Chief Product Officer James Love gives you something more useful than a headline: a plain English guide to what’s going on under the hood, and a practical starting point you can use to get started.
The session covers:
- Three terms that underpin almost every AI conversation: generative AI, large language models (LLMs), and prompts, explained without jargon.
- How to write a prompt that actually works: a five-part structure (context, task, materials, shape, check) that you can apply to any tool
- A comparison of the three tools providers are most likely to encounter: ChatGPT, Claude, and Microsoft 365 Copilot, including where each one shines and where each one struggles.
- Four risk areas to understand and manage: data leakage, over trust, permission creep, and agentic action.
- A set of practical tasks you can try immediately, using real apprenticeship delivery scenarios.
Both approaches are covered. You’ll leave with a sharper understanding and a clearer sense of where to focus next. Watch the recording below.
Session 2 resources
