Hi, everyone. Welcome back to another episode of Glass Talk. Today, we are very excited to have Teresa Torres with us. Teresa is a renowned product discovery coach and also best known for her influential book, Continuous Discovery Habits, and she has guided countless product teams in adopting customer-centric approaches and developing sustainable discovery practices.

And with her expertise in opportunity mapping, hypothesis-driven decision-making, and cross-functional collaboration, Teresa has revolutionized the way companies build products that deliver both customer value and business value. And beyond coaching, Teresa shares her insights through her product talk blog, producttalk.org blog, where she provides actionable advice on product discovery and management. So today, we would like to explore her journey, her approach to continuous discovery, and

how teams can create products that truly resonate with their customers. Thank you for joining today, Teresa. Thanks for having me. Thank you. So first of all, it's really impressive that your book is sold over 100,000 copies worldwide. That's really impressive. And we really love the books. But could you tell us about the book and to the people who don't know the book yet? And also, what is Continuous Discovery Habits in your voice?

Yeah, my goal in writing the book was to create a really practical guide for product teams. So when I say product teams, I mean the cross-functional team, so product managers, designers, and engineers, and really give them a guide for how do they make good decisions about what to build. And there's a few kind of key tenets to that. So if we want to make good decisions, we need to build in feedback loops.

How do we know if we made a good decision? How do we measure it? How do we know if it was the right thing? And so in the product world, we're trying to build for our users, for our customers. We want to have a feedback loop with them. Is this working for them? Is it solving a need for them? Are they going to continue to engage and use it or buy it again? And so with continuous discovery, discovery is the work that we're doing when we're deciding what to build.

And continuous discovery is any digital product is always evolving. It's never done. So if it's never done, we're continuously making decisions about what to build. And so we need to be looking at continuous feedback loops. So how do we make sure that on a daily basis, we're getting feedback from our customers that what we're building is the right thing to build for them? And so the book is meant to be a practical guide to help teams do that.

And I look at it as three big components, and then each of those three components have smaller subcomponents. So the first one is really understanding how we're going to create value for the business so that we earn the right to serve the customer over time. And so that's defining clear outcomes that's going to make sure that your business will be around for the long term. The second is making sure that we're understanding customer value.

So how do we make sure we're creating value for the business in a way that creates value for the customer? And then the third piece is how do we discover the solutions that address that creates that customer value in a way that creates that business value? And that's super high level, but we can get into sort of the more specifics. But really, my intent with the book was to create a practical guide to help teams make better decisions about what to build.

Thank you. And ideally, like the map, like opportunity mapping, like, you know, starting with like a desired outcome, not output, but outcome, focus on outcome, then break it down to like opportunities, what opportunities we have. Then for each opportunity, we can create, you know, we can think of like solution and experiment for each solution or something. Could you elaborate on the opportunity mapping? Yeah.

So I created this visual called an opportunity solution tree. It's meant to represent those three components that I talked about. So the top of the tree is the outcome. Our outcome represents business value. And then from there, we're looking at what I call opportunities. Opportunities are unmet customer needs, pain points or desires. So how can we positively intervene in our customers' lives in a way that drives our business outcome? So we're aligning that business goal with customer

value. And then, of course, for any individual opportunity, we're looking at what are the solutions that can solve that opportunity in a way that drives business value. And so as you work your way down the tree, we're starting with that business need. Then there's the opportunity space or mapping the opportunity space to understand customer needs. That allows us to make a more sort of strategic decision about where we want to play.

We're looking at all the areas where we could create customer value that allows us to make a more strategic decision about where we where we want to create customer value. And then we can iterate our way through smaller opportunities so that we can continuously deliver value. So a well-structured opportunity space using an opportunity solution tree allows us to find, week over week, what can we do that creates value for our customer in a way that creates value for the business?

Yes, that's really an insightful mapping. And people can visually understand the concept. And that's really, I think, great. And thank you. But do you have some example? I think you've coached many product teams, and I think you explained this concept hundreds of thousands of times, I think. But do you have any great example that people easily understand the concept? Yeah.

So one of the examples that I used throughout my book was related to streaming entertainment. Think a company like Netflix. Part of the reason why I use that example is it's a product that everybody around the world is broadly familiar with. So you could imagine if you worked at a company like that, one of the outcomes, one of the business needs would be to increase viewing engagement, get people to watch your service more often. That's tied to this business goal of driving retention.

So in a subscription business, we want people to retain. Maybe our theory of retention is the more you watch, the more likely you are to retain. So the top of our tree, we might have an outcome like increase average viewing minutes per week. And then we want to go out and we want to interview our customers, understand how our product fits in their world. Presumably, they're buying our product to be entertained.

When do they want to be entertained? Where are they watching? Who are they watching with? There's a lot we might want to learn. And as we sort of collect those stories, we're going to learn things like common pain points, like maybe I can't find something to watch, or I want to have a good viewing experience. Maybe I have a slow internet connection and it constantly has to buffer. So as I hear customer stories, I'm going to hear these opportunities, needs, pain points, and desires.

If we addressed them, it could help us drive our outcome. So if I interview you and I want to figure out how do I get you to watch Netflix more, if you tell me a story about how you wanted to watch Netflix, but you couldn't find something to watch and you were browsing through all the options, and one of the challenges you ran into was, I can't tell if I'm going to like this show, right? So the high level need is I need to find something to watch.

The need below that is I can't tell if I'm going to like this show. And we could even break that down even further into maybe you like to evaluate shows based on, is it a character drama or is it plot driven or who's in the cast? These are all sort of sub components to I can't tell if I'm going to like this show. And I can visually map this. So an opportunity solution tree is just a decision tree.

It's we're taking a hard thing and breaking it down into its sub components. And then for each of those sub components, we're breaking it down even further. And what that allows us to do is we might spend the rest of our lives trying to help people find something good to watch. But if we work our way down the tree to something teeny tiny, like who's in this show, that's something we could solve in a short period of time and deliver a solution and then move on to the next thing that's

neighboring it. And as we do more and more of that, we start to solve the higher order problem of I can't tell if I'm going to like this show. I see. In my understanding, through the user interviews and so on, we should collect the user stories and understand the context and how people use them in what context and situation people use and need that solution.

And so how can we improve it? But isn't it similar to jobs to be done framework? Or do you have other like, yeah, like a similar concept, do you think? Yeah, there's a lot of overlap. So in a jobs to be done interview, we tend to focus on the purchase decision, right? So there's this concept of when you buy a product, you're hiring it to do a job. And what we're listening for is what is that job? So what I teach is I call it story-based customer interviews

where I'm collecting specific stories about what actually happened. So my Netflix example, I'm asking, tell me about the last time you watched Netflix, or if I'm on the mobile team, tell me about the last time you watched Netflix on the go. Or if you're on the search team, tell me about the last time you had to search for something on Netflix. All of those are story-based questions.

Now, none of those are a jobs to be done interview, right? A jobs to be done interview would be something like, tell me about why you decided to sign up for Netflix. Because jobs to be done is really. I'm going to finish this and then I'm going to qualify it. It works when we're talking about the highest level job. And here's the thing, I'm familiar with Tony Ulrich's, how he's written about jobs to be done and especially Bob Moesta's work on how he's really popularized jobs to be done.

Both of them, I believe, get more specific than just the purchase, but the way most companies use jobs to be done, they're applying it at that high level around the purchase. And so they end up with a job like, I want to be entertained. I don't want to be bored after dinner at home. That's the job I'm hiring Netflix for. Whereas with my opportunity mapping, we're getting much more granular. That job exists.

I do want to be entertained, but I have a very specific need if I can't find something to watch. And the reason why I can't find something to watch is because I can't tell if I'm going to like this show. And the reason why I can't tell if I'm going to like this show is because I like plot-driven or I like character-driven dramas and not plot-driven dramas. And I don't know which one this is. Right? So my goal with opportunities and getting more and more specific is to tackle hard,

intractable problems iteratively over time. Whereas the way most people use jobs to be done, it's really at that higher purchase decision level. But I think a lot of the people that have invented jobs to be done or have popularized jobs to be done, the way they teach it and the way they talk about it is really similar. It's just how it ends up getting applied in business. It's a little bit of a different level.

I see. I'll give an example. Usually a company, a company, not a product team, a company will commission a jobs to be done study for the whole product. And they're trying to understand the jobs for the whole product. Whereas opportunity solution trees, we're building at the team level. Every single team is building an opportunity solution tree. So a little bit, it's just a difference in scope. Now, if Tony Ulrich was here or Bob Muesta was here, I could imagine they would argue

jobs to be done could be done at those other scopes. But I rarely see companies apply jobs to be done at the narrower scopes. I see. I see. Yeah. Thanks for clarifying the difference and the granularity. And yeah, thanks. And at the same time, when we evaluate the opportunities and there's so many metrics or ways to, how to say, prioritize the opportunities. Some people use ICE metrics, like impact and easiness or whatever.

Then some people use OKR. There's so many metrics. And do you have some, your favorite metrics or evaluation, like evaluate process? So most of those frameworks are applied at the solution level. And I think that's wrong. Right? So most of the time when we're talking about ICE or there's rice and there's so many variations on that, right? Where most people are applying that is they have a list of features or a list of ideas.

And they're trying to understand the impact of those features and how confident they are in that or the effort required. Right? And I think the challenge with that is that we're missing the more strategic question, which is what's the most important customer need or problem for us to solve? And I rarely see teams apply those frameworks at the opportunity level. And so I think what happens, like all of us, like our brains want to jump to solutions.

And so we fall into this trap of prioritizing solutions. But I think the more strategic decisions happen in the opportunity space. So which opportunities should we go after? And I think this is where, if you want to differentiate from your competitors, having a better understanding of the opportunity space and choosing the opportunities that nobody else is solving that matter to your customer is where your differentiation comes

from. So the first thing I would say is I really want to encourage people to prioritize opportunities and not solutions. And then once you've chosen a target opportunity, you can compare and contrast solutions. And the way that you're comparing and contrasting solutions is based on how well they address the target opportunity. So in that context, we don't need one of those scoring frameworks. We're using prototyping and assumption testing to evaluate, is this solution actually addressing

this need? And we can kind of compare and contrast. But then this does leave the question of how do I evaluate opportunities? How do I decide which opportunity to focus on first? There's a lot of frameworks for how to assess opportunities. And I think what's most important is that you use the framework that matches your stakeholders' expectations, right? Because when we choose a target opportunity, that's usually where we have to defend that

decision internally. And different companies at different moments in time, different criteria will matter more. So I think about it as there's four broad categories of criteria. So one is just opportunity sizing, how many customers are impacted, how often. Two is market factors. If we were to, is this opportunity a differentiator? Is it table stakes? How does it affect our position in the market? Three is company factors.

Different opportunities might support our company's strategic initiatives differently. And then fourth is customer factors. How important is it to our customers? Here's the thing. If I work at Spotify, when they're making a big push for audiobooks and podcasts, it doesn't matter if I've uncovered an opportunity about music that my customers care a lot about. If my whole company is saying, no, all hands on deck, we're investing in audiobooks and

podcasts, right? So sometimes in an organization, company factors are going to trump everything else because they're making a big strategic bet. Other times, like if I work at a company where, maybe if I work at Google and I'm working on Gemini and we feel like we're behind open AI, maybe it doesn't matter how many customers are impacted because customers don't even know what to do with generative AI yet.

But what matters is there's opportunities that they feel like are table stakes where they're behind. And so they have to catch up, right? So it's not that there's one best framework, it's that you have to look at where we are as a company. What's the criteria that's going to matter most for our strategic decisions, for our position in the market, for how they impact customers. And then we're tailoring that criteria based on what our company needs in that moment in

time. I see. Yeah, thank you. And then, but is that the same for the visionary company? Visionary means like, you know, let's say there are some consumer companies that like the founders are very visionary. So meaning customers or users don't even, never thought about the product. Like let's say Snapchat, BDRNN, those companies are really like the founders have forward thinking, so visionary. So does your framework or concept work for this visionary company to like, yeah, startups?

Yeah. So like, I think we're going through this right now with generative AI. The average person in the street doesn't even know what generative AI is. They certainly don't know what to do with it, right? But that doesn't mean that if I work on a generative AI product that I can't do discovery because I'm not interviewing my customers about solutions. I'm interviewing my customers about their lives and their needs.

And so I'm listening for what opportunities would generative AI be a good solution? Where do I want to play in this opportunity space? So one of the biggest mistakes product teams make is they use their interviews to explore solutions and it's just not very effective. First of all, when we're exploring solutions, we need to understand more quantitatively is our solution going to work and doing that one interview at a time is just not very effective.

The purpose of an interview is to understand different contexts. So one person, what are your needs in a given context? So we can stick with entertainment, right? I could ask a bunch of people, how do you spend your evenings after work? And I can listen for, are people bored? Do they have a gap? Are they looking for something to do after work? Are they always watching TV? Are they reading books? Are they listening to podcasts?

Are they socializing with friends? How are they making those decisions? Do they feel like their needs are getting met? Again, are there gaps? And regardless of what product I'm going to build or what technology I'm going to use or how visionary my future state of the world is, if I don't understand that context, my solution isn't going to work. So there was no human ever that we interviewed and they said, I need generative AI.

We're barely getting a grasp on what generative AI is and what it can do, right? But we have lots of needs that arrive in our life that it turns out generative AI is starting to fill those needs. So it's not about how visionary are the founders. It's about how good of a match is there between that vision and the human context of what people need. I see that totally makes sense. But at the same time, sometimes I hear from the product team that,

oh, we are following these metrics or following this way, but founders someday told us, oh, we should do X, Y, Z, totally different things. Sometimes this miscommunication happens. Do you have some tips or advice to fix this? I mean, I know the concept of productorial and the concept, but yeah. I think there's a misconception. I think people think an empowered team means they get to do whatever they want, and that's not what it means at all.

An empowered team means they're empowered to make the daily decisions they need to serve the business, but they're still serving a business. They're still being tasked with an outcome. They still have a strategic context in which they have to work. So let's walk through an example. Again, I think Spotify is a great example of this, because they recently made a big strategic bet.

Historically, they'd just been in music, and they decided to expand to audiobooks and podcasts, and particularly podcasts, right? Let's say that you're working on a product team at Spotify during this transition to making an investment in podcasts, and let's say that the leader of Spotify, David Ek, I think, Daniel Ek, one of those names, he says to all the product teams, I want you all to shift gears and work on supporting this new strategic initiative.

As a product team, I shouldn't be like, no, you told me my outcome is to increase retention in music listeners. Your outcome has changed. The strategic context of your company has changed, and it doesn't matter what music listeners are telling you they want. The company is making a strategic bet in a new area, and so we're all moving to that new area, and this is something that I think is a big conversation happening right now, where there's a big debate about how empowered should teams be.

So we saw this with Airbnb, where they're arguing they're going to follow more of an Apple model, and Apple notoriously, the perception is they make top-down decisions. Steve Jobs decided everything. Okay, well, Steve Jobs decided everything. There's no way they'd be as successful after his death as they have been, right? It's not that he decided everything. He set a really high standard of quality. He set a visionary direction.

Every product team at Apple still has to make dozens and dozens of decisions, and they should be empowered to find those right answers, right? But the strategic context and the direction the company is going to go in should be set by the leaders, and so that changes what a team might work on, but it doesn't change how empowered they are to go about their daily lives, because no leader in any organization can make every decision in that organization, and so I think this is a huge misconception.

I think founders are always going to, not just founders, founders, CEOs, executive teams are always going to say we're going this way, and sometimes that way is going to change, because the market is always changing, and technology is always changing, and customer needs are always changing, and that's our leadership's job is to steer the ship and say we're going in this direction, and then it's all of our product team's jobs to say, okay, given our new strategic context,

how does our work have to change? I mean, I think people think about it as like this false dichotomy is we're empowered or we're not. I think about it as at what scope are we empowered? When there's lots of cash and there's lots of room to explore, we get empowered at a broad scope, and then when cash tightens up and companies make more of a tighter strategic context, then our teams are empowered in a narrower band, but I still think they're empowered teams, because

every team is going to make lots of decisions. I see. Yes, totally. Totally makes sense. Yes. And you tapped on the technology, and now, as you mentioned, Gemini and Chachibiri and AIs, it's trendy, and people started adopting the tools and AI for their daily work, daily life, and have you seen the AI or LLM affected how product team works or the customer needs or customer behavior in this space? Yeah, I think we're already seeing it have a huge impact.

I know there's a product called a chat PRD that's helping product teams write better PRDs. I know some people are using it to write their customer stories. The problem with user stories is that, like writing user stories, it's really tedious to write all the detail required to cover all the edge cases and all the acceptance criteria, and I've seen a lot of examples where an LLM is helping with that. It doesn't mean the LLM is deciding what to build.

It means the LLM is filling in all the details and helping us find edge cases we might miss and helping to write some of the more boring parts of our job. I also think for a long time, we've seen, even before chat GPT came out, we're seeing machine learning used in synthesizing, finding themes, finding patterns across large data sets. I personally use chat GPT to analyze what's working on social media and what's not, and to pull out what topics are resonating with

people and to pull out what's driving engagement and where do people want to learn more. I think there's a lot of areas where it can help. What I don't like is when people are outsourcing the work of understanding humans to changing it to understand fake humans. I don't like these companies that are setting up interview synthetic users instead of interview real humans. I think we've seen over and over again that technology needs more humanity, not less,

so I don't love those services. I also don't love, I know there's a company building a one-click opportunity solution tree. Click this button and we'll create an opportunity solution tree for your market. That kind of misses the point. The goal is not to have an opportunity solution tree. An opportunity solution tree helps us synthesize what we're learning and helps us align as a team.

If you just create it with the click of a button, you're not doing any thinking at all and you're definitely not going to be aligned as a team. I think there's some misapplications of it, but I think we're just starting to scratch the surface. To me, it feels like 1994. We're a year into the web. There's a lot of hobbyists. We're all trying to figure out what in the world this is for, but I do think there's a ton of potential for it to dramatically change the way that we work.

Understanding humanity, what humans want is more important, so people try to outsource, but this is not. That's human stuff. I'm pretty confident that if we're building products for people, we probably still need to be talking to people. I don't see that changing. Exactly, but just curious, what kind of AI tool do you use for your daily work? I use both ChatGPT Plus, the paid version, and then also Cloud. How do you difference it? Different use cases? Yeah. I use ChatGPT. I have it on my phone, and I use it a lot for what I used to use Google for.

I'll give a really silly use case. I have a puppy, and I'm always wondering, is it safe for my dog to eat this thing? I literally will just open ChatGPT on my phone and be like, can dogs eat french fries with truffle salt? It's just a dumb query. Before, I would have asked Google, but then on Google, I got to click through a bunch of links and see a bunch of ads and read 2,000 words before I get to the answer. I just want an answer.

ChatGPT has definitely replaced that for me. That's not a work use case, but it's probably my most common use case of I think about it as my curiosity engine. I'm curious about something, and it's a way to just get a fast scratch that itch. Work-wise, I use ChatGPT to do data analysis. I'll upload a spreadsheet and then use it to have a conversation about what's in that spreadsheet. I use it when we post a new article on Product Talk.

I want to create a long-form summary of that article to share on social media. I'm actually using Clod for that. I find that Clod does a little bit better job of matching my writing style. I think because of the New York Times lawsuit with ChatGPT, ChatGPT will not return text verbatim. Even if you ask it, I would try to get ChatGPT to be like, summarize this article using the language from the article. Use my words, but create a high-level summary of the article. It can't do that because it can't.

I think they put in guardrails to not return anything verbatim from the training set, whereas Clod, I can give it an article, ask it to write a summary, and the summary is my words. It's not Clod's words. It's just taken from the article. There's a little bit of differences between the two in what they'll do and not do. ChatGPT can browse the web and Clod can't, so I'll use ChatGPT for things like a lot of SEO stuff.

I'll give it an article and a keyword and ask it, how can I improve this article to rank better for this keyword? I've given both a product landing page and then asked, how can I improve this landing page? I'll give it an ideal customer profile. Here's my target customer. Here's the landing page. My ideal customer profile has a summary of what I've learned about my customers, about how they evaluate.

In my case, I sell courses, so I have a summary of what people look for when they're buying courses, what their needs are, and then I give it that and I give it landing page and then I say, how can I improve this landing page? So I use it a lot. I use both a lot as like, I use ChatGPT a lot as like a sounding board, like another person on my team. And then I use Clod a lot now. I just recently started using Clod whenever I want something that's written to be, to sound like me.

Like I feel like in my writing, I have a very distinct voice. And if I'm going to use ChatGPT or an LLM to help me like repurpose it into other formats, then I want it to still sound like me. I definitely don't want it to sound like ChatGPT. I see. Yeah. Thank you. Are either of you using these tools in your work? Yeah. Yeah. I use Gemini, Clod, and ChatGPT, but mainly ChatGPT plus, yeah, Pro I mean. Yeah, same. And I use ChatGPT and Clod often case situations.

And because since I'm not a native English speaker and I learn English as a second language. And when I send email or when I send like a message or post something, I want to, I want a ChatGPT to revise my English and I use that. I have an admin where English is also her second language and she uses ChatGPT to just check all the emails that she sends. And especially she does customer support for me. And we have a knowledge base with all of our like support with like a whole bunch of support

templates. And we now use, we used to use ChatGPT for this where we could give ChatGPT an incoming email and it would find the right template to use. So that just saves time of like, what's the right template. But then OpenAI made a change where it won't return the exact template anymore. That's part of that verbatim problem. So we just switched to Clod and Clod will return the exact template. So it's, we still have a human sending all the emails and reviewing and we take, we customize

the template based on the email that we get, but it's just makes it, we have a lot of different types of products and people email us about a lot of different things. So it helps with like quickly getting to the right area of the knowledge base. See, that totally makes sense. Yes. I assume because you have like a coach, I don't know, like I saw that 11,000 people who coach, but I think the number should be bigger right now.

We have had just over 16,000 people enroll in our courses. And that's in our paid courses. If I were to look, we now have like free courses. I don't, to be honest, I don't even track how many people will take our free courses. But we've had over 16,000 people enroll in one of our paid programs. And that's since 2017. And then our courses are a little different from how my coaching used to work.

I used to work with teams where I would meet with them every week for 12 weeks in a row. So it was like a very high touch coaching program. I probably have worked with about 200 teams in that context. But I don't do that anymore because what through that coaching program, we were able to develop a course that gets like 80% of the benefits and it scales better. Right. We can have way more people go through a course. So if you're a lot, the problem we were trying to solve was we would now work with really large companies and they come in and they say,

we have a thousand people across our product design and engineering team. I can't coach all those teams. Right. But we can have them take our courses. And so over the years I've shifted from this like high touch coaching program to a more scalable course program, but it's all based on the same curriculum. And there's no way I could have gotten to the course curriculum without doing the coaching. I see.

I saw your LinkedIn and you've been coaching like since 2011 and it's been, I think, 13 years, 14 years now, but you created, started the course, you said 2017. And also you published a book in 2021. And I was wondering, why did you publish in 2021? Not in 2015 or 2017. Yeah. Sorry, dumb question. It's actually a really good question. I started working on the book in 2016. That was when I first wanted, I basically developed the opportunity solution tree in early 2016. And I wanted to write a book about it.

The challenge with writing a book is it's the epitome of a waterfall process. You write a book, you release it, you hope it is good. And I didn't really want to do that. I wanted to make sure that the book that I wrote was going to be good. And so instead of writing a book in 2016, I started to take, I was coaching at the time. So I was working with 10 teams at a time. I had cohorts of teams and I started to codify what I was going to write in the book in a course platform.

And I had my coaching teams go through the course content and then come to coaching. So I could see what worked, what confused them, what were they able to change their behavior. So I shifted my coaching from just being like real time, I'm here to help you to you go through content on your own. And then I'm real time here to help you. And then eventually I got to the point where that curriculum started to get good enough that most of the time in coaching, they didn't have hard questions.

Like the content was good enough to get them where they needed. And that's when I decided I was ready to write the book. So you were continuously developing the book. But you also wrote a lot of great blogs, right? And I'm curious, how does writing book process look like? But you write blog, you teach people and you gather feedback maybe, but yeah, I'm curious, how did you do everything at the same time? Yeah, so first of all, I now have a lot of help with my blog.

So I have a blog editor, Melissa Susino. She writes two of our series. So she writes our product and practice series, where we write stories about real teams who are putting the discovery habits into practice. And then she writes our tools of the trade series, which is where we interview teams about what tools they're using to put the discovery habits into practice. I'm the editor on those posts, but obviously being the editor is a lot easier than being the writer.

And then over the years, we've found ways to make it easy to write blog posts. So for example, we have another series called Ask Teresa. And most of those questions and answers actually come out of our community. So I run a Slack community for discovery practitioners. And I'm just participating in that community, helping people out. And then inevitably a conversation will happen, where it's just a really good dialogue, and we'll turn that into

a blog post. So I think over the years, I've built up systems to make blogging regularly, not a lot of work. I've also done things like I do a ton of podcasts, I do a ton of interviews, I do a ton of webinars. And anytime there's a Q&A, we keep all the questions. So I have a database of over 1000 questions related to discovery. And so I don't ever have to think about what to blog about.

It's been years since I've had to sit down and be like, what am I going to write about today? More likely, I have 40 blog posts I could be writing, and it's just, is there enough hours in the day? Even though I've been blogging for, I mean, I started Product Talk in November of 2011. So 13 years now, or coming up on 13 years, I'm writing a book was a whole different story. Like I, I'm a big reader, and I really wanted to write a really well structured, well written book, because I like that as a reader.

And writing like a 2000 word blog post, it's like on one tight topic, and like you explore it in depth. But in a book, you have to cover more ground. It's like a balance of how in depth do you go versus how much of a whole picture do you share? And so I probably spent four months just working on the table of contents, just trying to get the structure right, and understand the depth. And then when I wrote the first chapter, I actually wrote chapter five first.

So chapter five is the interviewing chapter. And I wrote that first, and it ended up being 50 pages. And I was like, oh, I, I have 14, 15 chapters outlined. They can't each be 50 pages. So there was a lot of trial and error of like, how do I reduce this? And then the other thing that I did is I put together a group of early readers. So I had 60 people that were reading each chapter as I wrote it.

And then they could give feedback in a Google Doc, but they also joined a monthly call where we talked about, were they able to put that habit into practice after reading the chapter? And like, what obstacles did they come up? And those calls were super helpful. In fact, every chapter, every habit chapter in the book has a list of anti-patterns. And a lot of those came from my coaching practice, but I didn't include them originally in the book. My early readers encouraged me, like on the call, they would share their challenges and I would help them.

And they were like, you're, you have stuff in your head that needs to be in the book. And that's what led to those anti-patterns. So there was a lot of testing and a lot of just trial and error. Thank you. But I'm curious, where is your knowledge database? So maybe you are reading a lot of blogs and books, and where do you keep those ideas and learnings? A few different places. I'm a big fan of ReadWise. So I use ReadWise's Reader.

I still use RSS feeds. I feel a little bit like a dinosaur, but I will until they no longer exist. I do a lot of highlighting. So ReadWise's original product keeps all your highlights in one place, and one thing I love about what they do is they send you an email every day with a set of highlights across everything you've read. So it syncs with Kindle. I'm a big Kindle reader. I read all of my books on Kindle. So that's for stuff that I'm consuming.

That's all in ReadWise's Reader, ReadWise's product. For things like my question database and my own discovery work that I'm keeping track of, most of that I use Airtable. Airtable and Apple Notes. So Airtable is – I used to be an Evernote user, and then Evernote really just got bad quickly, and I didn't want to – I was afraid of adopting another product that might go away, and I was pretty sure Apple Notes is going to be here forever.

So I switched from Evernote to Apple Notes, and then I use Airtable for structured data. So my question database is in Airtable. I see. And when you write something, so where do you write? So Apple Notes, Evernote, but how about blogging? So it's like WordPress or something? Oh, you mean what do I use for my own blog? Yeah. I currently have a WordPress site. I don't know if you've been following along what's happening in the WordPress community.

So I'm seriously considering moving away from WordPress, but I've been on WordPress since the very beginning. But you have a sub-stack too, right? I do. This is – I just like to experiment, right? So when sub-stacks started to get really popular, and especially when they released their recommendations engine, I wanted to see if I could take advantage of that recommendations engine, but I really believe in owning my own data and having my own domain and not putting my content – like I never wrote – I wrote for Medium, but like I republished

product talk articles on Medium. Like I just want to own my own content. And so I was a little bit worried about, is this just another Medium and it's eventually going to go away? But I saw so many people have success with sub-stack recommendations that I wanted to find a way to take advantage of that. And then at the same time, Elon Musk had just bought Twitter, and my biggest social media audience at that time was on Twitter,

and I was a little bit worried about like, was I too dependent on Twitter? And so what I did was I took – I have a pretty robust social media strategy. We share a lot of content, and people love it. In fact, I get criticized on LinkedIn. People are like, Teresa posts 40 times more than the average person on LinkedIn. But we've ran experiments where we reduce how much we post, and it's negative. It's always negative.

Like people love how much we post. And so what I did was I took all the content that I share on social media, each day, and I packaged it into a daily email. And that's my sub-stack. So sub-stack is Product Talk Daily, and it's basically the content I share on social media in a daily email. And I did that so that I could tell my Twitter followers like, hey, I don't know what's going to happen to this site, but if you want to guarantee that you get my content,

sign up for Product Talk Daily. Do you automate sending? I saw your social media. I checked your social media. You're so active posting a lot. Do you automate stuff, or do you have someone doing it? Yeah, so I schedule social media. It's all scheduled via buffer. I'm not posting seven times a day. And I'll just outline our strategy. We share a worthy read every day. So that's an article that I've read over the years that's in my personal database of what I think is high

quality content. We share that every single day. So somebody else's article that I think is worthwhile, we share Monday through Sunday. I share an article from the Product Talk archive most days of the week. It depends. On Wednesdays, we publish new content. So we're publishing our new article on Wednesdays. But most of the other days, it's an article from the archive. So that's two posts a day.

Monday through Friday, we share a short-form video, so one to two minutes, just me as a talking head introducing one concept. And so that's three posts a day. And then we sometimes post about our upcoming webinars, or about our upcoming courses, or we have these little posts that share key concepts from the book. So those are occasionally a fourth post. And it just depends on our schedule and what's going on in our business that we want to get in front of people.

And the reason why I post so much is that my social media strategy started as a Twitter strategy. And Twitter was all about, if you posted throughout the day, you reached more people, right? Because I'm asleep when Europeans are awake, for the most part. And if I could schedule posts, then I could engage a European audience. And then when Elon Musk bought Twitter, I just took my exact same strategy and started doing it on LinkedIn. Well, most people don't post multiple times a day on LinkedIn.

They post like one time a day. I think LinkedIn even recommends you not post more than one time a day. But I will tell you, I am continuously experimenting. And if I only post one time a day, I get less engagement and less traffic than if I post multiple times a day. So I'm still doing it. And when we don't post a worthy read or a product talk article, we hear from people. People message me and are like, hey, where's your content? So that's also a pretty good indicator

that people like it. Yeah, that's pretty awesome. And do you, will you share more quotes? Because you know, I watch your video and talk and I really like the quotes like by, you shared a Wilson, William Gibson, a science fiction author. The future is already here. It's just unevenly distributed. I love these quotes. And will you share more quotes in your daily product blog or any blog post? In the two articles that we share each day, so the worthy read

and then the article from product talk, we always try to highlight a quote. What I found is that if you lead with a quote, people are curious. And we used to just use the quote as the social media post. But then, especially on LinkedIn, people are just really argumentative and people would read the quote and not the article. And then they would misinterpret the quote and they would argue with me about the misinterpreted quote.

So now we do a quote and then a full article summary to expose more of the article content. Just trying to like, I don't really want to argue with people on social media. And I definitely don't want to argue with people that like didn't bother to read the article and are misinterpreting it. So we now share a little bit more just to try to cut down on people that argue. I see. Thanks. Thanks for sharing the context behind it.

And sorry, this is maybe a dumb question, but I think you've coached thousands of, tens of thousands of people, but have you thought about starting your company again at some point? I mean, this is your company, right? But like a startup or joining a big company as a, like a CPO or executives and maybe you've already helped me, but. Yeah, I don't think I'll ever have a job again. I spent most of my full-time employee experience at early stage startups. I think the energy at startups is really fun. I really love zero to one product management.

I think that there's a lot of opportunity for discovery tools. I'm glad to see a lot of teams are now creating discovery tools. I think I'm past the stage in my life where I want to work that hard is part of it. Like I just, I know what is involved to put a new product in the world and for it to work. I mean, I do launch products. I think all of my courses are products. I'm still launching products, but I think software, it's just a different beast. And I think I'm past that stage.

I do occasionally, like I have some companies that I work really closely with and I do, like one company I knew was looking for a chief product officer role. And like, there's a part of me that like, I really miss working with engineers. I really miss coaching, like managing a team. There's a part of me that would love to do that. And then I think about 50 plus hours a week of work and being in an office.

And I just, I personally believe I can have more impact doing what I'm doing now. And it's, for where I am at this stage in life, it's a better fit for me. Totally. It makes sense. Thank you. And since time is running out, you know, so our audiences are like aspiring product managers, founders, and also writers and authors, and do you have some advice to those people in any aspect, from any aspect? Yeah, I think I learned this. I was lucky.

I learned this at a young age, but I learned it the hard way. I recently came across a blog post. I'll see if I can dig up a link for the show notes, but it was all about be really careful about choosing which hierarchies you want to climb, right? And the author wrote about everything, every decision you make in life sort of puts you on a different hierarchy. And a lot of us are so focused on getting to the next step. We don't always ask, is this the hierarchy we even want to be on? And I think this is true

for founders, because especially if you're in the Silicon Valley or the San Francisco Bay Area, broadly, it feels like it's the only path in life. Everybody should be a founder. This is what success looks like. And I think the challenge with that is that it is one of the hardest jobs on the planet. Your chance of success is minuscule, and most people aren't willing to talk about that. There's some really unsavory characters that are the result of a system where a small number

of people are rewarded excessively, and a lot of people don't see those rewards, but give their whole lives to something. And so I think that ecosystem can cause a lot of challenges. And I think a lot of people, especially people living in the San Francisco Bay Area, jump into that pool and play there because they think it's what they should do, and they don't ever stop and examine it. And that article about choosing your hierarchies really resonated with me, because as a 32-year-old,

I became the CEO of another person's startup. So I was not a founder. I didn't have founder equity, but I did become the CEO during the 08 economic downturn. And it was miserable. It was super hard. I faced a ton of... It was just crappy. And it forced me to ask myself, what in the world are you doing? And it led to the career I have now, which is a way better fit for me. It's also why I'm really confident that I'm doing what I should be doing, because I was forced to ask that question

relatively early in my career. Whereas I think a lot of people don't ask that question until they're in their late 40s or their 50s, and then they don't have a lot of time left to figure out what to do. Great advice. And you lived in San Francisco for 20 years or so, right? I did. And yeah, so before we started recording, you asked me if I miss San Francisco. And part of the reason why my answer is definitively no.

There is a lot I love about Silicon Valley and the San Francisco Bay Area. The fact that everybody believes in creating this future and there's this optimism. In the Wall Street Journal today, I think it was the Wall Street Journal, they did a feature on Tim Cook. And a big theme of the article was about how tomorrow will be better than yesterday. And that belief is that I resonate with so much. I love it. And I love that about the Bay Area. But it also is...

I did my undergraduate at Stanford. And there was this meme, before they were memes, of being at Stanford is like being a duck on a lake. Where above the water, it looks like you're just coasting. But below the water, you're furiously running your legs. And I feel like that's a lot of the San Francisco ecosystem. Everybody's pretending like they got it all figured out and everybody's working really hard. And in some ways, not healthy for you. So I think my message would be, there's other ways.

There's other ways to have a big impact on the world that are healthier for you. So ask those questions. I see. It sounds like a red carpet effect. But yeah, thank you so much. And this is the last question. But since Grassroots is a platform where people share what they're reading, learning as their digital legacy, and then we want to ask you, what impact or legacy do you want to leave behind for future generations? Yeah.

I mean, I've been really lucky in that I made a decision about 13 years ago that really what I wanted to do was to help product teams spend more time with their customers. And when I started, I literally got laughed at. I'm not joking. People laughed at me when I said that teams should talk to customers every week. And now I regularly hear from people that are talking to their customers every week. And that to me is a pretty darn good legacy. I'm not done. There'll be more books.

There'll be more courses. There'll be more blog posts. But I'm feeling pretty good about my impact. Beautiful. Yeah. Thank you. And I know we love your book and we learned a lot. And thank you so much. Ah, thank you. Thanks for having me. And yeah, thank you for today and sharing all the insights and advice. Yeah. Thank you so much. All right. Thank you. Thank you.