Navigating the Complexities of AI Development

What You’ll Learn:

• Why “free to build” doesn’t mean “no cost”
• How AI prototyping tools help with assumption testing
• Common pitfalls (and how to avoid them)
• Why engineering skills still matter in a no-code world
• The types of prototypes that are perfect for AI tools
• How these tools change team collaboration and speed

Key Takeaways:

• AI tools can help build usable prototypes in hours—not weeks.
• These tools are great for fast, interactive assumption tests.
• You still need engineering know-how to troubleshoot or guide LLMs effectively.
• Product teams benefit most when they build and test together.
• Even failed prototypes offer valuable learning.

Episode Quote: “Even if the cost to build goes to zero, if you keep building the wrong thing, you're still wasting your life.” – Teresa Torres

Resources & Links:

• Follow Teresa Torres: https://ProductTalk.org
• Follow Petra Wille: https://Petra-Wille.com

Mentioned in this episode:

• Large language model (LLM)
• ChatGPT
• Claude (Anthropic API)
• Teresa’s Continuous Interviewing Course (where she introduced a custom chat interface app, allowing students to interact with a ChatGPT-style tool powered by her own prompts and proprietary data)
• Petra’s The PMwheel – a Compass for the Product Manager Development Journey
• Vibe coding
• Teresa’s Assumption Testing Course
• Jeff Patton’s drawing of the three people having different pictures in their head about one thing
• Replit
• V0.dev
• Bolt
• Lovable
• WindSurf