ABOUT THIS EPISODE
What You’ll Learn in This Episode
- Why most AI outputs fail without proper context
- How to think of AI like onboarding a new intern (and why that matters)
- Practical first steps for product leaders: decision logs, success metrics, and structured documentation
- How to balance giving AI enough context without overloading it
- The parallels between giving context to teams and to AI systems
Key Takeaways
- AI needs more context than you think. Treat it like a new teammate who doesn’t know your company history, industry, or strategy.
- Start small now. Even if your org isn’t adopting AI yet, you can prepare by documenting decisions, goals, and guardrails in machine-readable ways.
- Not all context is helpful. More isn’t always better—focus on giving AI the minimum effective context to perform well.
- Leaders already do this. The same way you create strategic context for your teams, you’ll need to do it for AI agents.
Resources & Links:
- Follow Teresa Torres: https://ProductTalk.org
- Follow Petra Wille: https://Petra-Wille.com
Mentioned in the episode:
- Agentic AI
- Teresa’s new podcast, Just Now Possible in Youtube, Apple Podcast, and Spotify
- Petra’s Coaching Packages
- ChatGPT
- Henrik Kniberg’s talk at Product at Heart on treating AI agents like interns
- Teresa’s webinars on how she built the Product Talk Interview Coach: Behind the Scenes: Building the Product Talk Interview Coach and How I Designed & Implemented Evals for Product Talk’s Interview Coach
- Josh Seiden’s blog series about AI
- Teresa’s new blog posts: 15 Ways to Use AI at Home (and Fill Your AI Product Toolbox) and 21 Ways to Use AI at Work (And Build Your AI Product Toolbox)
- Petra's new blog post: Why Context, Not Just Data, Will Define AI-Ready Product Teams
English
United States
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