10 Years After the Lean Product Playbook: PM in the Age of AI

1. AGAakash Gupta0:00

   Is there a risk that people jump too quickly into the solution space and don't adequately investigate the problem and solidify that they're solving the right problem with these tools?

2. DODan Olsen0:10

   Before vibe coding, you know, solution-space thinking is very prevalent. People start talking about, "We should build this feature. We should build this product." Sales teams are asking for features. Stakeholders are asking for features. Clients are asking for features. All that discussion is actually in the solution space. A lot of PMs are spending their time just managing the Scrum process, and they don't have time to do discovery. And now it's easier than ever to create a solution, which is kinda interesting if it's like, hey, if designing it and coding it is no longer the bottleneck, then it's like, well, what text you put in is the only thing that makes any difference.

3. AGAakash Gupta0:40

   What specifically has AI changed? This feels pretty timeless.

4. DODan Olsen0:44

   Yeah, it is pretty timeless. I mean, you know, at the end of the day, you still have to understand your customers, and AI's not gonna tell you, you know, about your customers.

5. AGAakash Gupta0:51

   Dan Olsen, I have been following your work for over 15 years. What has changed in the past 10 years?

6. DODan Olsen0:57

   I think really two main things have changed. One is ... The other big thing ...

7. AGAakash Gupta1:02

   How has AI changed product management?

8. DODan Olsen1:04

   AI has pretty much changed every step in the product management process. It can help you explore new opportunities that are out there in the market. It can help you identify segments. It can help you brainstorm feature ideas. It can help you do competitive analysis. But probably the most fundamental area it's changed the most is ...

9. AGAakash Gupta1:21

   You're a legend in the product management community for your work on The Lean Product Playbook. What was the thesis?

10. DODan Olsen1:27

    Yeah, the thesis was basically there was this term-

11. AGAakash Gupta1:31

    Really quickly, I think a crazy stat is that more than 50% of you listening are not subscribed. If you can subscribe on YouTube, follow on Apple or Spotify podcasts, my commitment to you is that we'll continue to make this content better and better. And now on to today's episode. Dan Olsen, I have been following your work for over 15 years. You're a legend in the product management community for your work on The Lean Product Playbook. For those of us who have forgotten in the last 10 years what that was about, what was the thesis?

12. DODan Olsen2:05

    Yeah, the thesis was basically that the, the, there was this term, product-market fit, you know, defined by Marc Andreessen back in 2007, but there was no, like, s- rigorous framework or systematic process for how to do it. And through my consulting and speaking, I realized that I could create that process, and that's the lean product process, which is a simple six-step process that, you know, thousands of companies have followed at this point to try to achieve product-market fit. Yeah, so this is the six-step process. Uh, basically, you start with defining your target customer. You figure out what are their underserved needs. Those two layers form the market part of product-market fit. And then from there, you define your product's value proposition. You figure out what your feature set should be. That's where MVP thinking comes in, so you don't over-scope it. You figure out your UX. You design the UX. You prototype it, and then you go and test it with customers to see how you're doing with product-market fit. And you iterate through a learning loop to try to achieve product-market fit or decide if you have to pivot or, worst case, you know, you pull the plug. But that's basically the process at a high level, um, for how to achieve product-market fit.

13. AGAakash Gupta3:05

    What has changed in the past 10 years?

14. DODan Olsen3:08

    I think really two main things have changed. One is when the book came out, product management wasn't as well understood as it is now or valued. And, um, you know, um, in the last 10 years, it's really exploded. People are way more product manager jobs. People appreciate what product managers do. And so, uh, there's more appreciation for the techniques and frameworks in the book, and more and more companies are actually applying it. The other big thing, which we're gonna go deep into today, is AI, obviously. AI, we've, we've been fortunate to live through-- I've been fortunate to live through a few different disruptive waves of the internet, you know, mobile, uh, and now we've got AI, and so it definitely is impacting how teams are creating products, and I'm excited to get into that with you.

15. AGAakash Gupta3:44

    What specifically has AI changed? This feels pretty timeless.

16. DODan Olsen3:48

    Yeah, it is pretty timeless. I mean, you know, at the end of the day, you still have to understand your customers, and AI's not gonna tell you, you know, about your customers, uh, you know. Um, you still have to figure out how to segment your market. You have to figure out your persona. It can help you brainstorm and come up with, you know, potential ideas and segmentation attributes. But at the end of the day, you still have to get out of the building and talk to people and, uh, to do your discovery research, basically. So it can help you synthesize discovery research, but you've gotta come up with it. Um, and then the next thing is you need to-- Once you've identified the customer problems, you've gotta prioritize which ones are the biggest opportunities. That's where my importance versus satisfaction framework comes in. And an AI's not gonna be able to do that for you. You're gonna have to use judgment. And, um, you know, I played around with GenAI. It's really good for brainstorming and creating convergent, like, divergent ideas, but it's not good w- as good when it comes time to eval- like, kinda converge and evaluate and prioritize ideas. And so that's where you still need to h- you, you still need to do that. And then your value prop. You know, I've tried a couple times to get, uh, ChatGPT to create a product strategy. They kinda sound good on paper, but when you scratch the surface, they're, the, the, the substance isn't really there as much. So I feel like that's the case. And then defining your feature set, that's another place it can help. It can help you brainstorm features, right? You say, "Hey, I wanna solve these problems for customers." It can come up with some really cool feature ideas. And then the biggest place, though, is in that creating the UX, creating the prototype. And we'll get into details of that. But with AI today, you can do it a lot quicker, and if you don't have a designer, you can actually do it now, where before you might not have been able to even do it at all.

17. AGAakash Gupta5:18

    I think that really is the unlock, right? Is with AI prototyping tools and with vibe coding tools, what used to be PMs sitting in a dock writing things up and then begging their designer for some resources or some time-

18. DODan Olsen5:33

    Yeah

19. AGAakash Gupta5:33

    ... to do some explorations off of a napkin sketch, PMs are now more empowered than ever-To go ahead and come up with some explorations in the solution space.

20. DODan Olsen5:44

    Yes, it's true. PMs really couldn't do a whole lot without designers. So let me walk you through the old flow. Um, I learned early on in my product career how important UX design is. So in my book, I have a whole chapter on UX design, and I like to describe the different artifacts that people could use and, like, in a preferred order. So I like to categorize them by interactivity and fidelity, as you can see here. We usually start with a product brief or a PRD, right? Some textual document. Um, and then we start doing hand sketches with our teams. We iterate those until we're happy with them, and then we can move on to clickable wireframes if we want. Um, low fidelity. They're low fidelity. They're usually black and white, a tool like Balsamiq. You can test with those. But really the best place in the old workflow to test was when you had clickable or tappable mock-ups.

21. AGAakash Gupta6:25

    Yeah.

22. DODan Olsen6:26

    Right? These days you use a tool like Figma to do that. In the old days, you might use InVision with whatever asset your designer gave you. And I've-- You know, for a lot of my clients, I-- this is where the, the rubber met the road. We would do waves and waves of user tests at this stage, and then once we worked things through and iterated to the point where we had confidence in product-market fit, then we would go code the product, and of course, we'd test the line product. But basically, in order to do that flow, you needed to have someone who could prototype on your team.

23. AGAakash Gupta6:52

    Yeah.

24. DODan Olsen6:52

    And that brings up something I've been talking about for a long, long time, which is the design gap on many teams. If we just take the high level activities that a product team needs to do to create a product, and we say it's basically defining the product, which is mainly PM's job, designing the product, which typically falls on the designer, and the develop, then basically there's different levels of UX maturity within a team and different org structures that you see. The most common one and level one is basically, "Hey, we've got developers," and that's it.

25. AGAakash Gupta7:17

    Yeah.

26. DODan Olsen7:17

    There are a lot of startups that are like that. Actually, a lot of AI startups these days are like that too, because at the end of the day, if you don't have coders, you're not gonna build anything. So that's like the least UX savvy level. The next level up is, hey, in addition to engineering, we have PM, but neither one of them is really a UX expert, right? That's the idea. You're gonna see... You can see when you see products from these kind of companies, you see the lack of UX design come through in their product. Now maybe, you know, one of these two can lean in and help try to cover some or most of that gap. Maybe the product manager, you know, has picked up some front-end skills, some design skills, or maybe you have a front-end coder who's picked up design, right? They might be able to get by, and maybe between the two of them, they can kinda cover it. Frankly, in the early days of Intuit, where I started my product manager career, that's how they got, got by. Before design was a thing, that's how they got by.

27. AGAakash Gupta8:02

    Mm.

28. DODan Olsen8:02

    The PMs and the engineers thought enough about UI to get it right that our product was easy, easy to use. But the real thing you wanna have, obviously, is the triad, the trio that we talk about. You've got product management, engineering, and UX who can do that. So, you know, unless you really had level five, it was really hard to like rapidly create good prototypes. The cool thing is with vibe coding, it's completely changed that. One, if you don't have-- If you're, if you're living with a design gap, you as a PM now can actually create those prototypes and you can create them quickly. And even if you had a designer, we know that designers are busy. Um, they get-- They're on multiple projects, so your project might not be a priority for them. You can now take it on yourself and get it done, and so you can get to a prototype more quickly, even if you have a designer. And so the new workflow is, you know, pretty-- It, it's pretty interesting, is you can just... You know, you're starting with text. Again, you're starting with text, you know, whether it's a product brief or a PRD. That's gonna be the input into your vibe coding tool, and now you're gonna get a live prototype. You know, before vibe coding, people would create what we call HTML prototypes. It would be full on HTML, CSS, maybe a little JavaScript, but no back end if they wanted to really kinda have it be really high fidelity. Nowadays, with vibe coding tools, you can totally have a front end, and you can even have a back end tool. And so you can get quickly to that live prototype to test your idea. And that's one of the key things about the lean product process, Aakash, is you wanna get through all those bottom layers and get to the prototype as quickly as you can, 'cause it's by putting that prototype in front of customers and getting feedback where the real learning and iteration towards product-market fit happens.

29. AGAakash Gupta9:34

    Yeah. I think that the biggest unlock for people was just testing [chuckles] those clickable prototypes that we were building, whether they were in Balsamiq or Figma. But now what we're seeing with AI prototyping tools like V0... We just had the CPO on the podcast. Lovable-

30. DODan Olsen9:52

    Yep

Episode duration: 1:19:37