WEBVTT

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Thank you. Um, also thank you to Lenny

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for running this and for inviting me

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actually to be a speaker. Um, I don't

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actually go to a lot of conferences. Uh,

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but when I do, um, I really enjoy them

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and I will tell you I can't I lost track

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of the people that came up to me and

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thanked me for content for books. People

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ask me to they have tattered copies of

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inspired and they ask for signatures and

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it's you know hugely uh flattering and

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humbling to see that. I did warn several

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of them that my talk was actually all

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about

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my regrets

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uh of which there are uh quite a few.

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So that is what I wanted to talk about.

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But I have been here with you all day

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listening to every one of the talks. And

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um I learned something really

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interesting from every single one of

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them. I observed and I'm sharing this

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for a reason, but I observed that there

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are two kinds of product in the world.

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Two kinds. I've always called them
the project model and the product model.

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About half the speakers were from each.

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Obviously, I'm highly biased, but my

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world is both of them. And so,
it's super interesting for me to hear, but

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hopefully you all can think back on the

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day and you saw dramatically different

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definitions of the job. Now,
the truth is, as I was listening, I

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was like, "Oh, I got to talk about
this and I got to talk about that. I don't

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want them to leave thinking this." But

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then Robbie from Google and Ki basically

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said what I would have said. loved it.

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Again, I'm biased, but loved them.

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What I want to talk about here is a
little different. Honestly, it's uh

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something I've known I've needed to do

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for a long time, but I kept sort of

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procrastinating on it because uh this is

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a really hard question, especially for

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me. I have spent decades arguing certain

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points. Now, for those that don't know

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my work, I am actually one of those
people. I'm not interested in the latest

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process. I'm not interested in the

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latest framework. I don't really care

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what you created an agent to automate.

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I don't care because that's not actually

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the job of product.

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That might give you some tooling to help

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you do the job, but that's not the job.

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The job of product is to solve problems

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for our customers and achieve outcomes

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for our business. That's what this is

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about. So that's what I'm interested in.

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And because I focus on principles, the

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truth is they're pretty durable. In

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fact, every time a new technology wave,

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you heard a very polite way of saying I

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must be very old to have seen all of

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these waves. But yeah, every wave
you're like, will this invalidate those

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principles? You don't
really know until you look at

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it. And of course, as as you know, all
those waves were actually a lot of fun.

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I am one of those. I mean, the reason
I'm a product person is because I love

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the fact that what's just now possible

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is changing all the time. That's what
makes it cool. Otherwise, I would not be

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doing this this area. I wouldn't have

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chosen this as a career. But with AI,

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I feel like I had to look at everything.

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Even the things that honestly I was

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taught are sacred. It's like you don't

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mess with this principle. I wanted to

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look at everything. That's what I did.

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Now, the first thing I had to figure out

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was where do I start? Because the truth

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is I treat my content as my product and

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I am literally doing product discovery

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every single week with product teams. In

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fact, a lot of many of you have been
with me to know that's what I'm doing.

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I'm learning. That's what I've been
doing here today is really discovery on

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product content. And it was very good

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for me to hear these other views, all
of the other views. But anyway, the truth

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is I have a lot of things I've learned.

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Now most of the time I just write

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articles and publish stuff on more minor

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learnings. But what I wanted to do

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was to identify what I thought that I

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mean honestly I started brainstorming a

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list and it's a big list. It's kind of

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depressing but there's a big list. I

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wanted to pick the top 10 things that I

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genuinely regret. I genuinely if I knew

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then what I knew now now I decided to

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draw the line with the publication of

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the first edition of inspired which was

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in 2008 which I some of you weren't even

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born then but that's when I'm drawing

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the line but you have to realize I had

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been doing product for 25 years when
I wrote that. So I had been a product

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manager. I went through the whole

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engineering side and I was a product

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leader for two and a half decades. So I

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had learned a lot from amazing people at

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some, you know, honestly the anthropics

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of the day, really good companies. So I
decided let's draw the line there. Even

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though some of the things I'm going
to talk about are regrets that are less

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than six months old. Let's do that.

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Let's talk about it. 10 big things.
The first one I want to start with is

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business viability because that's
honestly the most embarrassing of them.

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There is no way for me to get around

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this. I completely understated the

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importance of business viability. Just
so that everybody knows what I'm talking

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about here. Business viability. This is

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a product manager's job is to make sure

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at least in the product model is to make

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sure that the solutions are both
the customer will buy it and it works for

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the business. That means you can afford
to market it, you can sell it, you can

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service it, it's legal, it's compliant,

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it respects privacy, safety, ethics.

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This is a big thing even before AI. It's

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big. Those of you working on AI

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products, you know it's even harder.

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Business viability is a really big area.

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But the embarrassing truth is

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in the first edition of Inspire.
I didn't even talk about it as a risk.

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Value, usability, feasibility. There
were three risks that we talked about.

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Viability was buried in there. I'm
embarrassed to say that. Now, I fixed it

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in the second edition, but that was 10
years later. This is one of those I had

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a lot of introspection because the truth

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is I kept asking how could I have gone

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so long with such a huge

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blind spot around products and I believe

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I know the answer to that and I want
to share it with you because it's very

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relevant even today maybe even

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especially today because in my career

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for those that might know I almost all

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of my career I was working on developer

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tools and platforms

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which I still absolutely love that

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space. Who doesn't love claude code? I

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mean I love that space. However, you
need to understand this. It's one of the

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few areas

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where a product manager can get away

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with pretty weak skills. Now, that's not

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the only one, but it's one of them. Now,

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that's not a a criticism. It's kind of a

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an advantage for those kinds of

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products. It's a much simpler space for

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viability. But for most products,

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especially for AI products, that is not

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true. And in fact, I used to be
very excited about my um knowledge of

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engineering because I felt like it
helped me learn new technologies. I came

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from an engineering background.
That's what I studied. And it was like big

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advantage. I felt like that was my my

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sort of superpower. But today

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I would argue going forward and for all

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of you to succeed at every level,

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business viability,

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especially from a holistic systems

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thinking perspective. Second, problem

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discovery. Now the tr you know,
I've always talked about product discovery

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has got problem discovery, figuring out
what problem you're going to solve and

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solution discovery, solving that

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problem. The truth is the mistake I made

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was I just did not understand

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how strongly people would be drawn to

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the problem discovery side of that

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equation. In fact,

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a lot of people view themselves as the
gatekeeper. That's their job as product

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managers to make sure they agree this
is a problem to solve. Yes, you obviously

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need to make sure you understand the
problem, who you're solving it for, and

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what the definition of success is. But

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honestly, that's not very hard. It's not

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very hard. And if you spend a lot of time
on that, you're not going to do the

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real part you're paid for, which is

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solution discovery. You might think when
a product fails, it's because you didn't

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um you know, it wasn't a big enough
demand, not enough people had that

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problem. you're almost always wrong
because what's going on is as soon as

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somebody else comes out with a better
solution all of a sudden we know that

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that was never the issue. So problem

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discovery I should have emphasized yes

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problem discovery important little bit

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of time save time for solution discovery

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that's the essence that's where

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innovation happens the next big issue um

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and this is another one all of these

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kind of have uh you know good and bad

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sides but um I spent a lot of time

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talking about how important it is to
understand the reason why we're working

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on whatever we're working on, whatever
problem we're working on. I didn't make

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this phrase up. John Door did, but we

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need teams of missionaries, not teams
of mercenaries. If you want missionaries,

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you have to make sure they understand

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the reason. And yeah, that is important,

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but that's so easy. And in fact, if you

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have a product strategy, which you

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should, we'll talk about that in a
little bit. the reasons you're working

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on these problems is spelled out for the

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whole organization to see. So there's no

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big mystery. So what I want to talk

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about and I was really happy to see that

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Robbie called this out. There is a much

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more important why than why are we

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working on this problem and that is why
are people not using our product. He

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called that out. I would love seeing that.
And honestly that's kind of a

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surprise for Google. for for a while
they thought it was all based on data

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and we're not going to talk to No, we

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need to actually talk to our customers
to figure out why. I try products

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constantly. I bet most of you do too.

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That's what product people do. We're
early adopters. We try it out. Most of

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them are crap products. You know this,

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right? We try it. We're not good. So, I

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churn. Almost nobody follows up anyway.

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Nothing. Not a survey, not a email,

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nothing to ask me why I churn. Probably

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the single most important question is

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why are people using our product or not

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using our product? And the part that

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really gets me is that's the key to

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unlocking so much innovation. And yet

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most teams never ask that question. The

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next one, humility. You know, the longer

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I go, the more important I realize that

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humility and a a truly open mind is so

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important to product people at every
level. What does that really mean?

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Humility. It means knowing what you

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can't know and admitting what you don't

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know. Many of you know this, but instead

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most people the message they took away

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from my books was the C the product

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manager should be CEO of the product,
which is kind of the opposite of a

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humility message. And

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yeah, this might sound like a

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personality trait to you, but it's not.

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I would argue this

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contributes directly to the root cause

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of so many failed products, which really

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leads me to maybe my single biggest

00:12:34.960 --> 00:12:36.797
regret.

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I honestly had no idea and I just didn't

00:12:42.080 --> 00:12:45.997
appreciate how powerful and deeply

00:12:46.080 --> 00:12:49.037
rooted the desire for predictability

00:12:49.120 --> 00:12:52.077
was. And that's from both product people

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and senior executives and how at odds

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that desire for predictability is with

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not just humility but innovation and

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outcomes.

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Consider for a second I'm opening a can

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of worms here. I probably shouldn't but

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consider for a second the two big

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artifacts in the product world maps and

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PRDS. So road maps of course the

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prioritized lists of features we think
we need to build and when and the PRDS

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which is how we describe the requirement

00:13:24.880 --> 00:13:28.717
of those features. Now for a second

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consider how much of an enabler

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those artifacts are for thinking that we

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know more than we really do. This is

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such an important point and so many

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people misunderstand this. You know,

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people keep asking the question, do you

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still need PRDs? Do we still need road

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maps? I I never heard that one posed

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till this morning. Uh despite Claire's

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optimism, I guarantee your road maps are

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not going away.

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We all know that the issue is not

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whether they are there. And it's never

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been whether they are there. The issue

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is what are you using that PRD for? If

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you're using it because you're forgive

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me arrogance and you think you know the

00:14:16.720 --> 00:14:19.757
answer so you're putting it in terms of

00:14:19.840 --> 00:14:22.317
requirements for your engineers to build

00:14:22.400 --> 00:14:25.277
that's the project model that's the root

00:14:25.360 --> 00:14:28.237
cause of so many failed products. If

00:14:28.320 --> 00:14:31.917
however you have learned and tested and

00:14:32.000 --> 00:14:34.397
and gathered the evidence you need to

00:14:34.480 --> 00:14:36.877
know what's going to be built is going

00:14:36.960 --> 00:14:39.517
to achieve the outcome then the PRD is

00:14:39.600 --> 00:14:41.997
just your communication device. It's not

00:14:42.080 --> 00:14:44.877
only harmless, it's actually useful. The

00:14:44.960 --> 00:14:47.037
same is true with road maps. If you put

00:14:47.120 --> 00:14:49.117
a bunch of features that are somebody's

00:14:49.200 --> 00:14:52.077
idea of what might work and you put

00:14:52.160 --> 00:14:56.717
dates there, you're going to waste most
of your time. you're going to end up

00:14:56.800 --> 00:15:00.797
wasting most of the engineering capacity.
And yes, the engineering time

00:15:00.880 --> 00:15:05.837
has gone way down. You're still wasting
it. And the tokens aren't free. So

00:15:05.920 --> 00:15:08.957
predictability is at the root of this. And

00:15:09.040 --> 00:15:11.757
predictability is important, but it's

00:15:11.840 --> 00:15:14.957
not as important or worth uh trading off

00:15:15.040 --> 00:15:18.957
outcomes or trust.

00:15:19.040 --> 00:15:23.437
Politics. The truth is I I we all know

00:15:23.520 --> 00:15:27.597
politics is important, but I thought
good product work will carry the day.

00:15:27.680 --> 00:15:30.237
That was of course naive.

00:15:30.320 --> 00:15:33.357
And the truth is politics are

00:15:33.440 --> 00:15:35.837
everywhere. They're in the fabric of

00:15:35.920 --> 00:15:39.277
every company. And I now if you look at

00:15:39.360 --> 00:15:44.077
the last three years of my content, half
of it is with dealing with politics and

00:15:44.160 --> 00:15:45.837
the other half is dealing with the

00:15:45.920 --> 00:15:50.077
impact of AI. It is a big topic. This is

00:15:50.160 --> 00:15:53.277
probably the one with the long long most

00:15:53.360 --> 00:15:56.397
damage created from uh like the book

00:15:56.480 --> 00:16:00.797
inspired. My initial work was all about

00:16:00.880 --> 00:16:03.037
product teams and product discovery

00:16:03.120 --> 00:16:05.277
because to me I what I really love is

00:16:05.360 --> 00:16:10.397
the craft of products and I wanted to
write about the craft of product because

00:16:10.480 --> 00:16:13.757
there's a lot of principles and a lot
of techniques and most people were just

00:16:13.840 --> 00:16:18.477
building stuff and shipping it and seeing
what sticks and that's still true

00:16:18.560 --> 00:16:20.557
today. And that was an intentional

00:16:20.640 --> 00:16:25.117
choice to focus on the on the teams and

00:16:25.200 --> 00:16:27.597
the craft of product discovery. What I

00:16:27.680 --> 00:16:31.437
didn't appreciate was I I almost hardly

00:16:31.520 --> 00:16:34.397
mention product leadership, but I didn't

00:16:34.480 --> 00:16:38.077
realize the consequences of that choice.

00:16:38.160 --> 00:16:40.717
And the result is so many companies and

00:16:40.800 --> 00:16:45.677
I'm I'm sad to say this, this is still
true today because by far somehow all

00:16:45.760 --> 00:16:49.437
these years later, Inspired is still
selling like crazy. A lot of teams just

00:16:49.520 --> 00:16:53.997
read inspired and they think all they
need to do is set up product teams,

00:16:54.080 --> 00:16:57.997
empowered product teams, a strong
product manager, you can be awesome, and

00:16:58.080 --> 00:17:01.357
they think that's all they need to do
and they'll be good. And of course, what

00:17:01.440 --> 00:17:05.677
so many companies have learned is that
in empowered product teams, you don't

00:17:05.760 --> 00:17:07.837
just need less management, you need

00:17:07.920 --> 00:17:10.477
better management. And the role of

00:17:10.560 --> 00:17:13.357
product leadership is so critical. You

00:17:13.440 --> 00:17:17.597
just heard from Kyrie the point about
context. That is what's so critical. At

00:17:17.680 --> 00:17:19.837
a minimum, it's the product strategy,

00:17:19.920 --> 00:17:22.317
which is your your prioritized list of

00:17:22.400 --> 00:17:25.277
problems to be solved. Another one that

00:17:25.360 --> 00:17:28.317
just um it's tough corporate governance.

00:17:28.400 --> 00:17:31.677
I I'm not talking about PMO, which is

00:17:31.760 --> 00:17:33.677
process governance governance. I'm

00:17:33.760 --> 00:17:35.517
talking about corporate governance here.

00:17:35.600 --> 00:17:39.037
Oversight of the company. I I we've own

00:17:39.120 --> 00:17:43.357
all known that's a problem, but um I
said this isn't something product can do

00:17:43.440 --> 00:17:47.597
anything about. And uh one of the most
painful lessons over the years is

00:17:47.680 --> 00:17:49.757
helping so many companies actually get

00:17:49.840 --> 00:17:52.397
better at shipping great products only

00:17:52.480 --> 00:17:55.917
to see they become a target for

00:17:56.000 --> 00:17:57.757
people with very different motivations

00:17:57.840 --> 00:17:59.437
that are pro going to pull the product

00:17:59.520 --> 00:18:03.197
in a different direction. So that's sad.

00:18:03.280 --> 00:18:06.877
If you've I would encourage everybody
to read Eric Reese's new book

00:18:06.960 --> 00:18:09.037
incorruptible.

00:18:09.120 --> 00:18:11.917
You know that this is a funny one.

00:18:12.000 --> 00:18:16.157
product is just not as gental as I made

00:18:16.240 --> 00:18:19.197
it sound in my books. It almost sounds

00:18:19.280 --> 00:18:23.677
academic, right? Where okay, your job is
to solve problems in ways your customers

00:18:23.760 --> 00:18:25.997
love but work for your business. Yes,

00:18:26.080 --> 00:18:28.717
that's true. But it kind of hides the

00:18:28.800 --> 00:18:32.397
fact that it's not enough. You actually

00:18:32.480 --> 00:18:37.277
have to solve problems in ways
that are dramatically better than your

00:18:37.360 --> 00:18:38.637
competition if you're going to get

00:18:38.720 --> 00:18:42.317
people to switch. And the truth is that

00:18:42.400 --> 00:18:44.717
product today a comp in the competitive

00:18:44.800 --> 00:18:48.797
open market product is a full contact

00:18:48.880 --> 00:18:52.077
blood sport and most people from my

00:18:52.160 --> 00:18:55.597
content you would not get that and a lot

00:18:55.680 --> 00:18:59.917
of teams aren't prepared.
And the last point

00:19:00.000 --> 00:19:02.477
uh and you know I uh this is a point a

00:19:02.560 --> 00:19:03.917
few people have brought up which I'm

00:19:04.000 --> 00:19:07.037
thrilled to see but fundamentally good

00:19:07.120 --> 00:19:11.437
product work is about thinking.

00:19:11.520 --> 00:19:14.637
It's about thinking and I here's what's

00:19:14.720 --> 00:19:19.037
the the mistake. I did not appreciate

00:19:19.120 --> 00:19:22.157
the lengths that people would go to in

00:19:22.240 --> 00:19:25.917
order to avoid thinking.

00:19:26.000 --> 00:19:29.517
Uh, I wish I was joking. Uh, what does

00:19:29.600 --> 00:19:32.237
it show up as? It shows up as a craving

00:19:32.320 --> 00:19:35.437
for process, frameworks, and

00:19:35.520 --> 00:19:38.557
predictability. I structured inspired as

00:19:38.640 --> 00:19:43.357
people, process, and product.
Big mistake. And I am worried that large

00:19:43.440 --> 00:19:47.037
language models will be used as an
alternative to thinking, but the truth

00:19:47.120 --> 00:19:49.757
is that's already happened

00:19:49.840 --> 00:19:52.877
with process. And the truth is Elon Musk

00:19:52.960 --> 00:19:55.437
was right about this. In many companies,

00:19:55.520 --> 00:20:00.157
process is used as a substitute
for thinking. So, please don't fall. I

00:20:00.240 --> 00:20:02.317
should have called that out. Called out

00:20:02.400 --> 00:20:04.637
thinking, called out the necessary

00:20:04.720 --> 00:20:07.517
foundation of product sense much more

00:20:07.600 --> 00:20:10.397
loudly and clearly. All right, those are

00:20:10.480 --> 00:20:14.477
the 10 big things that um I really

00:20:14.560 --> 00:20:16.797
genuinely regret.

00:20:16.880 --> 00:20:19.757
However, I will tell you, funny enough,

00:20:19.840 --> 00:20:22.717
ironically, I am feeling really good

00:20:22.800 --> 00:20:25.357
about the content overall, but more

00:20:25.440 --> 00:20:28.797
importantly, about all of our future as

00:20:28.880 --> 00:20:33.597
products. And I want to try to explain
why. The main criticism that I've

00:20:33.680 --> 00:20:35.677
received on my content, honestly, over

00:20:35.760 --> 00:20:39.277
the last 20 years is that um people wish

00:20:39.360 --> 00:20:43.757
they could work like is described
in Inspire. They wish they could. And they

00:20:43.840 --> 00:20:45.997
tell me there are two problems. One,

00:20:46.080 --> 00:20:49.597
their company is addicted to output

00:20:49.680 --> 00:20:51.917
and the predictability of that output.

00:20:52.000 --> 00:20:54.477
And two, it's hard. They think it's

00:20:54.560 --> 00:20:57.117
going to be hard to work that way. But

00:20:57.200 --> 00:21:01.757
look, in no small part, thanks to AI

00:21:01.840 --> 00:21:05.757
today, more places than ever understand

00:21:05.840 --> 00:21:08.557
the need for outcomes and not just

00:21:08.640 --> 00:21:11.997
output. And also, it is dramatically

00:21:12.080 --> 00:21:16.317
easier. You know, we talk about product
discovery is build to learn. Everybody

00:21:16.400 --> 00:21:17.917
in this room, I hope you don't leave

00:21:18.000 --> 00:21:21.277
this session without an understanding

00:21:21.360 --> 00:21:23.437
that there's two kinds of building.

00:21:23.520 --> 00:21:26.397
Building to learn and building to earn.

00:21:26.480 --> 00:21:31.197
I that comes from many of you know a guy
named Jeff Patton as a term, but we have

00:21:31.280 --> 00:21:34.717
lots of terms for this. But it's the
difference between product discovery and

00:21:34.800 --> 00:21:38.957
product delivery. If you want to spend
your time doing some pull requests on

00:21:39.040 --> 00:21:43.357
the front end, fine. Maybe you
should just go be a developer.

00:21:43.440 --> 00:21:45.917
But if you want to make sure that what

00:21:46.000 --> 00:21:48.317
your engineers do build and provide to

00:21:48.400 --> 00:21:50.957
your customers, you should be building

00:21:51.040 --> 00:21:56.157
the learned, it's a totally different
approach, totally different job. Your

00:21:56.240 --> 00:21:59.197
job is to make sure that when they
do build that thing, you achieve the

00:21:59.280 --> 00:22:01.837
outcome you need. So here's the thing.

00:22:01.920 --> 00:22:04.317
Thanks to AI, the principles of the

00:22:04.400 --> 00:22:06.877
product model, the craft of product

00:22:06.960 --> 00:22:10.317
strategy and product discovery

00:22:10.400 --> 00:22:15.197
have never been more important. All right,
I really hope this was useful to

00:22:15.280 --> 00:22:17.277
everybody. I do want to thank Shri Doshi

00:22:17.360 --> 00:22:22.237
and Teresa Torres who gave me feedback
on early versions of this. And I again I

00:22:22.320 --> 00:22:23.997
want to thank Lenny for putting this

00:22:24.080 --> 00:22:25.997
party together. I hope this was useful.

00:22:26.080 --> 00:22:29.560
Thank you very much.