I was given a blank canvas to run an AI workshop — no constraints on content, format, or audience. I chose to teach Claude to people aged 15 to 60 with zero technical background. What happened changed how I use AI myself.

ABSTRACT
There's a difference between knowing what an LLM is and being able to explain it to someone who's never used Google Docs.

I was offered a space to talk about technology with no guardrails — content, format, even the number of attendees was up to me. I decided to run a Claude workshop for a mixed audience: zero technical background, ages 15 to 60+. That meant dismantling everything I took for granted. How do you explain next token prediction without saying "next token prediction"? How do you make a prompt make sense to someone who's never written one — and wouldn't know it if they had? How do you keep a room of 20 people engaged long enough to show them this isn't magic or a threat — it's a tool?

This talk is about what worked, what didn't, and the three things that the process forced me to change in how I work with AI.

It's not about explaining AI to your grandma. It's about what happens when you have to understand something in order to teach it truly.

**What you'll take away:**
- The analogies that actually land (and why abstract metaphors don't)
- How "no jargon" constraints make you a better prompter
- A communication model that works for non-technical stakeholders and technical teams alike