Teresa Torres' Step-by-Step Guide to AI Product Discovery

**Aakash Gupta** (0:00)
What does discovery look like in the age of AI? Does it change everything or does it change nothing?

**Teresa Torres** (0:05)
You know, I've been getting asked a lot, like when delivery is free, do we still need to do discovery? And I actually think when delivery is free, discovery becomes more important.

**Aakash Gupta** (0:14)
In today's episode, I sat down with Teresa Torres, the legendary author of Continuous Discovery Habits. This is a book that I myself have read multiple times, marked up multiple times. So many PMs are doing customer interviews, yet their products and their features fail. Why? She has worked with over 17,000 PMs across the world, in over 100 countries. So she brings the insight you need to improve your discovery, not just for regular features with AI, but for AI features.

**Teresa Torres** (0:45)
Here's the challenge I see with prompt engineering. We all have experience like chatting with ChatGPT or Claude, and we're in a conversation. If we get that first prompt wrong, we can immediately refine. But when you're building a product, the prompt can't be refined by you. Once it's live in your product, there's no refinement. It's a one shot.

**Aakash Gupta** (1:03)
So what are the signs that PMs are doing fake discovery?

**Teresa Torres** (1:08)
Nothing in their backlog changes. They don't kill any ideas. There's a lot of discovery theater out there.

**Aakash Gupta** (1:13)
Before you go, Teresa, I have to ask, how big is the business of Teresa Torres?

**Teresa Torres** (1:19)
Yeah, so I'm looking f*****g.

**Aakash Gupta** (1:22)
Teresa, welcome to the podcast.

**Teresa Torres** (1:24)
Thanks for having me. I'm excited to do this.

**Aakash Gupta** (1:26)
As I was saying off air, you are on my S tier of guests along with Marty Cagan. You are the two guests I wanted most when I dreamed of starting this podcast. And that's because I think you have probably advised more PMs on discovery than anyone else in the world. What would you say the number is at now?

**Teresa Torres** (1:44)
Yeah, it kind of depends on how we count. So when I was coaching teams directly, I would work with about 30 teams a year. I did that for over a decade, so probably over 300 teams. And what that means is like weekly calls for multiple months. So I was sort of in-depth. Through the Product Talk Academy, we have over 17,000 students, which is pretty mind-blowing, and they come from over 100 countries.

**Aakash Gupta** (2:08)
Wow, 100 countries. I didn't even know PM was practiced in 100 countries. So you have really seen the whole world of product discovery, and it's interesting because so many PMs are doing customer interviews, yet their products and their features fail. Why?

**Teresa Torres** (2:24)
Yeah, this is a complicated topic. I think there's a lot of reasons for this. I think the primary reason is that we're not that good at interviewing. So a lot of teams, they go into interviews with the intent of exploring their solution and getting feedback on their solution. That's not really the best way to get feedback on our solutions. Our goal in our customer interviews should be to learn about our customers. Even if we know that's the goal of the interviews and we don't talk about our solutions, we tend to ask really unreliable questions like, what do you like and dislike about different things? Tell me about your experience broadly. And so one of the things that I teach, I introduce this idea in the book, we teach it through all of our programs, is this idea of story based interviewing. So how do I talk to you and collect a reliable story about your past experience? So I learn about what you actually do and not what you think you do, not what you aspire to do, but in reality, what did you do recently? So that I can make sure that I'm building a product that fits in your lived world.

**Aakash Gupta** (3:16)
So it sounds like people are asking too many hypothetical questions. Here's a prototype, would you like to use this? What would be the better way for them to approach that conversation?

**Teresa Torres** (3:25)
Yeah, so let's look at this in tears. So the first is a lot of people present a solution and say, would you use this? That's terrible, unreliable feedback. We're not good at predicting our future behavior. Also, humans want to be nice, so we're going to say, yeah, of course I would use that. And even if we think we're being honest, we're optimistic about our future time and about what we might do in the future. So we might actually genuinely think we're going to use it, but it doesn't mean we are. There's actually better ways to test our solutions. So I really like assumption testing when we're evaluating solutions, which is a whole different activity from interviewing. We can get into that if you want. What I like to use interviews for is let me just learn about you. And so what I want to do, sort of the next level, like people learn, okay, I should ask an open-ended question. So they'll be like, tell me about your experience with my product. The challenge with that type of question, it is open-ended. I might learn a lot about you, but what I'm going to learn is what you think you do, not necessarily what you actually do. And so to fix that, I want to ask you, tell me about the last time you used the product or even better, tell me about the last time you solved the problem the product was designed to solve.