When I could not solve a maths exercise, my aunt sat beside me and pointed me back to the step I needed to reconsider. She gave me the patience to find the answer myself.

I think of her when I use AI to learn. You can ask again, admit that you missed a step and try a different explanation without worrying that your question sounds stupid. At work, that opens a possibility for people who need guidance when an experienced colleague is busy.

But the same tool can complete the exercise before you have understood anything. This session explores how to use that availability to build understanding: asking for hints, working through an example, testing an explanation and doing part of the work yourself.

As AI takes on tasks people once learned their trade through, the first step into a profession needs attention. My aunt gives us a place to start: learning happens in the thinking you are helped to do.

For professional learning, AI literacy and events concerned with people entering or changing a profession. A personal teaching experience makes the difference between obtaining an answer and developing understanding tangible. The audience explores how to ask for guidance and keep practising when AI can already finish the task. Accessible to non-technical participants, with a useful connection to mentoring, onboarding and lifelong learning.