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Shownotes
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:
• Follow Teresa Torres: ProductTalk.org
• Follow Petra Wille: Petra-Wille.com
Mentioned in this episode:
• Behind the Scenes: Building the Product Talk Interview Coach (producttalk.org/2025/08/customer-interview-coach) by Teresa
• How I Designed & Implemented Evals for Product Talk’s Interview Coach (producttalk.org/2025/09/interview-coach-evals) by Teresa
• Leading Through the AI Wave—With Clarity, Not Confusion (petra-wille.com/blog/leading-through-the-ai-wa…) by Petra Wille
• AI Prototyping - All Things Product with Teresa & Petra (youtube.com/watch?v=6yfjNso_YYM) episode
• ChatGPT (chatgpt.com)
• Aman Khan (linkedin.com/in/amanberkeley) — distinction between AI-powered vs. AI product managers
• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO) (lennysnewsletter.com/p/the-rise-of-cursor-mich…) - Lenny’s Newsletter (lennysnewsletter.com)
• Devin AI (devin.ai) and Windsurf (windsurf.com) (acquired by Cognizant (cognizant.com/us/en))
• Yelp (yelp.com)
• Uber (uber.com/tw/en)
• Large language model (LLM) (en.wikipedia.org/wiki/Large_language_model)
• Claude (claude.ai)
• Gemini (gemini.google.com/app)
• BlackBerry (blackberry.com/us/en)
• Replit (replit.com)
• Zapier (zapier.com/l/home)
• Amazon Web Server (AWS) Step Functions (aws.amazon.com/step-functions)
• AI Agents in Practice: How Henrik Kniberg Sees the Future of Collaborative Work (productatheart.com/blog/ai-agents-in-practice-…) - Henrik Kniberg (linkedin.com/in/hkniberg)’s “interns” metaphor from Product at Heart 2025 (productatheart.com)
• Anthropic (anthropic.com)
• Extensible Markup Language (XML) (en.wikipedia.org/wiki/XML)
• OpenAI (openai.com)
• en.wikipedia.org/wiki/Markdown
• Eval (short for evaluate) (en.wikipedia.org/wiki/Eval)
• Personal information or personally identifiable information (PII) (en.wikipedia.org/wiki/Personal_data)
• Machine learning (ML) (en.wikipedia.org/wiki/Machine_learning)
