In This Episode:

• Why their early stance on AI-powered interview synthesis has shifted


• What Teresa learned from running 15 interviews through ChatGPT and Claude


• How AI raises the floor for beginners but accelerates experts even more


• The importance of separating analysis from synthesis


• Why most teams struggle with customer interview synthesis in practice


• What happens when interviews pile up — and whether AI can realistically help


• The risks of relying on AI when your interviewing skills aren’t solid yet


• A vision for “expert + AI” synthesis that’s both fast and high-quality


• The ongoing debate about AI-led customer interviews


• A detour into PC-building that perfectly illustrates the limits of AI support

Key Takeaways:

• AI isn’t magic. It can help, but only if your interviews are strong and you provide the right context.


• Beginner + AI is usually better than nothing. But the real performance gains come from expert + AI.


• You still need to synthesize every interview individually. Dumping transcripts into an LLM isn’t a shortcut.


• Customer understanding is a competitive moat. Outsourcing it entirely will cost you in the long run.


• Empathy comes from human interaction. AI can’t replace the experience of talking directly to your customers.

Resources & Links:

• Follow Teresa Torres: https://ProductTalk.org


• Follow Petra Wille: https://Petra-Wille.com

Mentioned in this episode:

• ChatGPT


• Claude


• The Interview Snapshot: How to Synthesize and Share What You Learned from a Single Customer Interview


• The Interview Coach by Teresa


• Customer Interview Analysis: Where AI Helps and Hurts by Teresa