Thinking About Thinking with AI: Why Self-Knowledge is Your Real Interface

Delivered by Anders Reagan

Audience Exposure Level: Open to all

This session isn’t about learning to prompt better — it’s about learning to think better, because AI mirrors whatever thinking you bring to it. If you don’t understand your own reasoning habits, assumptions, blind spots, or knowledge gaps, AI will amplify them. But if you do? It becomes a force multiplier.

At its core, this session explores how metacognition — the ability to notice and reflect on how you think — is the foundational skill for mastering AI workflows. But reflection alone isn’t enough. You also need knowledge: of your domain, of the tools, and of the kinds of errors AI systems make. Without that, you can’t improve. With it, you can design a personal learning system that adapts as fast as the tech does.

This is a session for people who want to work smarter and more honestly — to turn their own cognition into the most powerful tool in the AI stack.

Objectives/Learning Outcomes

By the end of this session, participants will be able to:

1. Explain what metacognition is and why it matters more than prompting skill in long-term AI use.
2. Map their own cognitive patterns, including typical assumptions, shortcuts, and knowledge boundaries.
3. Recognise when AI outputs reflect limitations in their own inputs or mental models.
4. Distinguish between surface-level reflection and strategic, knowledge-driven feedback loops.
5. Use AI as a diagnostic tool to surface gaps in understanding, not just generate content.
6. Develop a personal metacognitive workflow for ongoing improvement in AI-augmented work — one that scales with complexity, not just with volume.