What you’ll learn in this episode:
- The difference between an AI-powered product manager and an AI product manager
- Why prompt engineering for a product is different from prompting ChatGPT for personal use
- The role of prompt decomposition and orchestration in building robust AI features
- How to think about system design, risk mitigation, and cross-functional collaboration
- Why observability and logging traces are critical for LLM products
- The challenge of evaluating non-deterministic AI features (and why “thumbs up/thumbs down” isn’t enough)
- How to decide when AI is the right solution for a customer problem
- The hidden cost of ongoing maintenance for AI features
Resources & Links:
Mentioned in this episode:
