Lecture 2: Core Prompting
Lecture 1 explained what’s happening inside the model; Lecture 2 is about what you do with it. We cover how to prompt effectively — treating AI like a capable but new hire, using techniques like detailed scope-of-work prompts, the “interview me” pattern, and prompt postmortems you can reuse. We dig into trust and observability (catching confident mistakes, grounding answers in your own data, knowing when to demand evidence over assertions), the mechanics of managing long conversations (context rot, “lost in the middle,” knowing when to start fresh), and resource-mindful habits that are good for your wallet and the planet alike. We close on a thread that will recur all quarter: how to stay the one steering the AI, rather than letting your own skills and independent judgment quietly atrophy.