How you need to think about product strategy in the age of AI

Tim Herbig (0:00)

You might accelerate output by 100, but sooner or later, you will realize, does any of the things we're doing make a difference for customers or the business? But then it comes back to what do we want to achieve, which is essentially strategy and metrics. The fundamental questions you answer in product strategy do not change. You need to be careful where you use AI and how you differentiate with it.

Aakash Gupta (0:21)

Meet Tim Herbig, product strategy expert, a PM for eight years turned advisor, coach, and author of Real Progress. He's worked with hundreds of PMs to make sure their product strategy actually makes an impact.

Tim Herbig (0:33)

AI by itself in your strategy is not a value proposition. Everyone has access to the same frontier models. You can't compete on that technology alone.

Aakash Gupta (0:41)

Would there be some companies where AI could be the value proposition?

Tim Herbig (0:45)

Companies get easily lost in very machine-centric metrics. They tell me about tokens used, language, model efficiency. Point is, tokens used is not a value exchange for your customers. It's a value exchange for entropic.

Aakash Gupta (0:57)

So then you haven't really made a strategic choice.

Tim Herbig (0:59)

Yeah, but that's the thing. One of my favorite things that I look at to pressure test whatever people put in front of me is this quote from Roger Martin. And honestly, this quote, it's one of those light bulb moments that whoever I'm showing it to, you will never look at strategy the same. So here's this great quote where he says.

Aakash Gupta (1:17)

Before we get into today's show, please take a second to check that you're subscribed on YouTube and following on Apple and Spotify podcasts. If you want access to all of my favorite AI tools, I've gotten them to give you an entire year of their paid plans. Check out bundle.akashg.com for an entire year of bolt.new, Airtable, Speechify, Descript, Magic Patterns, Linear, Dovetail, Arise, and Mobin. And now into today's show.

In the era of Builder PMs and Cloud Code, everybody is focused on how do you build AI. But for my money, a much more effective use of a product manager's time than trying to become an engineer, is to actually influence the strategy, to make leaps on what problems we should be solving, how those impact the business, how we do things at the edge of what's technologically possible. And all of that comes back to building a great strategy.

That's why I've brought in my friend for over five years, Tim Herbig. I've been following his work in Product Practice on LinkedIn, and he has consistently been putting out the most thoughtful stuff on how you actually do product strategy in the age of AI. So today we are giving you a master class filled with anecdotes from his real work with real PMs, so that you can do better with your strategy work. This is one of those areas we keep hearing about. PMs don't focus too much on execution, they focus on strategy. But how do you concretely do that? Today we are going to walk you through everything you need to know. And if you stay till the end, you will learn how you can get one of five free copies of Tim's book that I am giving away. Tim, thanks for being on the podcast.

Tim Herbig (3:05)

Thank you so much for having me.

Aakash Gupta (3:06)

We have been trading emails online for a year, so it is my pleasure. And I want to get right into it. What do PMs need to know about strategy in the AI era?

Tim Herbig (3:16)

I love that question, and I love even more that I am just going to show you what I think the real deal has to be these days. So I think the problem is, how did we get here? Why do we even debate this question? And I think what we really have to understand is what happened over the last couple of years. So years ago, the limiting factor for most of product managers' work was, well, it takes too long to do this, and we have to be really ruthlessly prioritized what we're working on to spend all those precious engineering resources. These days, as everyone probably knows, like producing features get kind of cheap, especially for green field products, but even established companies can get stuff out the door much, much faster. But the problem, the downside of that is when features get cheap, not having chosen the right feature, funnily enough, gets more expensive because suddenly, you're flooding your product with all this output, all this fluffy stuff, all these great vibe coded lovable things, and everything you do to circumvent the complex engineering work, or even accelerate your engineering department. But this can come as a cost, because you still have to make people use the features you produced. So that's where the expansiveness comes in. And so what we're currently seeing, what I'm observing in the work that I'm doing is that companies are excited about amping up the output 100 times, but somewhere down the line, they have to ask themselves, did any of that make a difference? And you have to look at it from those two sides, of course. You have to look at it from the side of, did it make a difference for customers? But even more importantly, did it make a difference for the business? And so essentially, when we talk about product strategy, and especially strategy and AI, these two terms people love so much, I believe we have to actually take a step back, to really think about, well, what is the essence? What do we mean when we talk about that? What we really have to come down to is, do we have something in place that actually helps us say no to things? And do we have something in place that allows us to measure if we succeed? And you might recognize that, but these fundamental practices and core questions get buried under all the shiny object stuff that we see these days. And upon preparing for this podcast, I stumbled upon this quote from our mutual friend Ravi Mehta, who has this brilliant quote where he says, difficulty prioritizing is often a strategy issue, not an execution issue. And I think these days more and more people are actually feeling the pain of that. And I love that because this is like four or five years old, it is as timeless and valuable as ever, that it's not about execution. Execution never was the issue. So if we dive into that, what is actually the point of strategy? Why do we believe strategy is impossible? I believe that we have to think about product strategy like we think about the product. We have to be clear about for whom is this trying to solve a problem and how would we know it has worked. We're told to do this for the product work that we do. We rarely do it for our way of working. And I believe if you really break it down, your product strategy has to help teams and stakeholders to intentionally say yes or no to opportunities over the let's say 6 to 18 months, 3 to 6, doesn't matter, whatever time horizon works for you. And you basically know if the strategy makes sense, if the majority of the team's effort and energy is spent on work connected to strategy. And this sounds so painfully simple, but believe me, I've seen so many companies where, first of all, this understanding is not in place, and second, they definitely operate like that. So whatever you're thinking your strategy is, whatever shiny deck it is, whatever one-page it is, whatever framework, think about, does it help me say no to things? That's all that matters. It doesn't matter if it's like in the book, if it looks pretty or how much time you spend working on it. The point is, did it help you say no to things?