# AI Reshapes Product Management Speed and Judgment

**Podcast:** Product Momentum Podcast
**Published:** 2026-02-03

## Transcript

Paul, welcome back.
We just had a awesome conversation with Audgy Udegby.
It was fun.
It was funny.
We talked about three-speed problem, how AI is making delivery development so much faster.
How we speed up the parts of the process where humans have to talk to humans to figure out what to build and how to get it in customers' hands.
What'd you get?
Well, I I'll I'll get the the fun stuff out of my system first because the sci-fi reference at the end, the the broken earth trilogy, and and just on a serious note, thinking about things in the fictional space as a storytelling medium, I think is underrated.
So I think product managers need to read more fiction full stop.
The other thing that I was kind of struck by is how the thinking about product in the future as a sparring uh partner via AI, the idea that product might be uh ephemeral in the sense that we're thinking about things in basically 40-year-old processes.
The the mythical man month and the engineering bottlenecks are now largely obsolete, and now we have to get used to a new speed and decision making at that scale, and that speed is gonna take some some real grit for product managers to start to think through.
So I I had a blast with this conversation.
I I think OG is uh brilliant thinker for the the right the right person in the right moment to be to be sharing this kind of knowledge.
Absolutely.
Let's have a listen.
Today's episode, we have a special guest joining in the co-host chair.
Paul Gable, original co-host of product momentum is joining me.
And today we have Audgy Udeswe he helps transform products into marketing defining success he's led product teams to some of the most recognizable companies out there Callendly, Atlassian Typeform and Microsoft.
I have two of those tools actively open on my computer right now.
He's also a co-author with his wife Izene written building rocket ships product management for high growth companies have it right here a book that lays out frameworks for turning startups into market dominating forces throughout product like growth.
Beyond that, right, Audie is a mentor to the next generation of product leaders he's a pioneer in applying AI tools for building better products and I've had the privilege of hearing him speak at multiple industry conferences and we're really thrilled to have you on the show today.
Thank you.
Thank you Daniel I was a really great intro um I don't think I have anything much more to add unless we want me to no I mean let's let's jump right in.
Yeah lot a lot going on in the world seems like AI advancements are coming daily hourly.
I'm really curious to hear what your thoughts are on how that's impacting us as product folks, right?
What's changing?
What's staying the same?
So I think uh it's this is this is a moving question for me.
I get asked this a lot.
But I think the main thing is is sort of defining what product management is from first principles and then trying to see if AI does anything to it.
All right?
I think that's a fair way to think about it.
And so I think of product management as pointing technology much more closely to customers, meaning that we divine customer pain, customer need, what makes their lives less toilsome, what makes it more delightful, what makes them feel like, oh my god, this was like five times better than what I did before.
And this is something we call the zone of benefit.
And it makes them want to lean in once they want to, you know, to think about the first time you downloaded NAPS.
I guess I'm showing my age and how you felt.
You're like, oh my God, I can't have this, that feeling.
And then the second part is we try to make it so that the companies we work for, whether it's yours or a startup or something else, make money from that innovation, from that feeling.
That's really it, right?
Customer happiness, shareholder happiness, and probably your happiness because you're the biggest shareholder.
And so the middle is customer science, building orchestration and go to learn the new tools are changing, but the new tools of value, the new tools of selling at all.
But I think the overarching thing that they learn to do, this apprenticeship, this special apprenticeship is not gonna change very much.
I think just how to do it will change.
We were having a conversation recently with Teresa Torres uh about discovery and AI.
And she mean uh a quip about how we with AI tools, every yeah, we're also fast to be up like, hey, I can come up with an agent that will represent my customers for me.
How do we make sure y'all, as it gets easier and easier to you know, kind of talk to a pretend human that we don't lose the sight of the interactions with real humans, or yeah, our real users, real customers.
Yeah, I saw that kerfuffle on the internet.
It's such a an interesting uh thing where the product subculture is so big now that we have fights in public space.
Uh I was just um in a I was just in a conversation with Melissa, who's a good friend of mine, and I saw a post she made.
So I was talking to her like this week, but I saw a post she made and Teresa jumped in.
Um look, I think it's really simple.
I don't think the pattern for using AI in general is not generative.
We call it generative stuff, but the way you use it shouldn't be generative at all.
I think you create the core IP and then use it as an assistant to make it better, to find variations and so on and so forth.
So I would not start talking to synthetic anything for anything.
I think that's a huge mistake.
But often, if you're founder or you're even a feature PM, you have very small sample sizes, right?
Especially if you're building something new.
Synthetic data, synthetic users can be used to scale your already synthesized human-driven insights, right?
Because really the synthetic data is about mirroring the variation in humans about a thing.
But if you don't have the nucleus of the real human about a thing, what are you scaling exactly?
And how can you even compare if the scaling is off-kilter?
And so don't start with synthetic anything.
Start with real and then use synthetic to scale it so that you can tell when the scaling is going off the reservation.
I think it's really profound.
Expertise used to be hard to gain through you know the school hard knocks.
And now that're PM.
I fell in PM expertise, by the way, because you know, you can be a PM for 10 years and still do a shitty PM because the people who taught you aren't that good.
And there's no university to teach you.
So sorry.
I didn't mean to interrupt you.
No.
I I point to you.
We just got our tagline.
That's absolutely uh the valid take.
And and that's kind of where I'm headed, because now that intelligence is so commoditized and widely accessible, wisdom doesn't scale as fast as intelligence.
And your comment about first principles kind of reminded me of that.
Uh so I I'm curious what what your thoughts are on how for the past 10, 15, even 20 years, expertise with tools and processes used to be synonymous with expertise in in product.
But now that tools, processes are are outpacing the the those first principles so quickly, how do we build those checks and balances into our organization so that product has a fighting chance of even retaining first principles before boardrooms and and shareholders and and stakeholders get get a hold of how fast and commoditized things can start to move.
Yeah, we we had I think one of the conversations we had leading up today, we talked about judgment, right?
And I think the thing that we said was that if judgment if if AI tools are so prevalent, like what how what is judgment?
And you know, look, I think I keep saying like PMs are the judgment layer of the creative process of building technology companies, I think.
Um, that's our job.
And because you know, one of the things we say at product mind is that things are moving fast, but you can move fast in the wrong direction.
And so it's about five is about PMs at what point organizations that build technology well could in the right direction.
And I think it requires a judgment, it requires taste making.
This is why we love Steve Jobs, because he was a taste maker.
The other thing that I think is people need to understand what judgment is, right?
Judgment is continuous good decisions.
That's what it is.
It's it's not one good decision, it's not two or three.
It's a lot of them where you're mostly right.
And you know, the other thing about judgment is that it has to be speedy, right?
If you make one good decision and only one good decision every three months, then you this is that's terrible.
What you need to be doing is making one good decision every every day, right?
And then after 30 days, you've made 30 big decisions, and boom, now Bob's your uncle, you're in business.
So judgment comes from maybe two things in my career.
One is listen to people who are smarter than you, right?
Uh, because you don't want to make bad decisions just because you were a dumbass and you didn't listen, no matter how smart you are.
The second thing is just doing stuff and making mistakes.
Because if you're paying attention, you're gonna get the feedback loop, right?
If you do a lot of experimentation, you gain judgment for free versus gaining judgment for on on the dime of of your customers, for example.
But you have to do, not just think, uh perseverate, right?
You gotta do, and then you get to the point where your intuition about the thing, about what customers want, about what they care about, the frameworks you're using, like one I use all the time is simplicity and this idea of cognitive load.
Like, I look at a thing and I I'm asking myself, can people do this thinking, or they can do it with their spinal cord?
That's simplicity.
Right?
If you can do it with your spinal cord, then you don't you're not thinking.
It's in Twitter.
You just you feel it.
And there's some user experiences where you feel that, for example.
So judgment is always gonna be required in an age where AI is speeding up everything, judgment is gonna be premium.
Humanness is gonna be premium, and judgment is one of the big parts of humanness when it comes to the creative process.
If you think all those NFTs were worth a lot of money, just check out what a Bastiat is gonna be like in 10 years.
It's gonna be like a billion dollars.
So anyway, it's gonna be more crashes.
Is it will come from Star Tissue, and how the boardroom will appreciate it is that we're hooking ourselves up with product leaders who are providing good mentorship.
Uh, but you said something else that really struck is like, right, you you build judgment by messing up, right?
Like you you learn good decisions by making bad decisions.
Um, you know, when you're mentoring product leaders, you know, what advice you have for creating a space that allows product managers to make bad decisions to make mistakes.
Yeah, I think the first level is sparring, right?
Make decisions and share it with your team, and they will tell you whether it's a bad decision or not.
And even if you know the person always said it's a bad decision, they're wrong.
Maybe they're five people, you know, wisdom of a crowd and all that stuff, right?
And you know, it's the more powerful thing about that process isn't you're wrong, it's why do I think you're wrong, and then engaging in the debate that says, you know what?
I don't think I'm wrong.
Like, no, think about it this way, and uh no, you are wrong.
Think about it that way.
So I think that's the first level.
The second one is just experimentation, like don't release things to ten thousand people.
Try to release it to five, right?
Again, don't underestimate release stuff to the finance department, they don't know what's going on in the property, they don't give a shit.
That's not their thing.
They're trying to do the money, and so when you pull them and ask them questions or show them something, that functionally they are like external people, and they will tell you whether it's shitty or not.
And then five real customers, ten real customers, because they're always willing to co-build with you.
It's a privilege, they're like, Oh my god, really?
I can I can weigh in this early.
I feel special, right?
And that's good.
And then of course, you know, I worked on Windows, and sometimes we release things to a billion people and we screw up.
Right?
I remember being in war rooms in Windows where we shipped a bug or something, and then someone really reaming you out because but you know, releasing the bug to a billion people at Microsoft was just another Tuesday.
So, like we had a way to deal with it.
So um yeah, I think those are the levels of uh sparring that you can do in order to gain um to gain wisdom without necessarily have blowing up the world.
Yeah, it's funny you said that, right?
As a day-to-day product manager, nothing makes me more nervous than like kind of running an idea and not having anybody challenge it.
It's like, guys, please, please challenge this.
It's probably not that good an idea.
Yeah, or it just has nuances you didn't think of, right?
Like it's just that's the the nature of the game.
This is why, by the way, not being political, we still need a lot of diverse brains.
You know, we we I mean, I think diversity is no longer a popular thing for us to talk about.
But in the in the creative process of technology, building technology comes very specifically, you can't just think from every angle.
I actually think that the reason that we Microsoft screwed up Gen 1 of Xbox is because they didn't hire people who look like gamers.
They just didn't, who were taste makers.
It was just a bunch of technology people trying to build a great fast platform.
It was it sucked.
But over in Nintendo Land, they had the people who were very creative that looked like their customers, and that was that was the difference.
Yeah.
As you're as you're talking, I'm biting my tongue off not to go down a video game rabbit trail.
So I'm gonna reel it back into into into product land so I don't get distracted the idea that people that you're mentoring and and the the guidance that you're providing I think one of the opportunities with AI in thought workers toolboxes especially in product is that you mentioned five ten beta users can be valuable and internal finance people are functionally external users I love that the other thing that AI provides is we can now whether through agents or just very little sophistication required prompt some training some you know like a piano player practices scales for eight hours a day largely what product and design and and engineers do they're performing live for the first time in front of the client we don't get to practice scales where we're kind of doing it live all the time and now with AI we have the ability to hone our chops a little bit and while synthetic data has its shortfallings you you you've outlined a couple already I do think that there is an upside where AI can help us hone our craft a little bit and and be more of a a place to challenge our assumptions to improve our confidence.
How do you view AI as a as a training tool, not just a synthetic data set or a faster QA?
Um, how can AI be used to to help bring product up overall as a you know kind of that piano player practicing their scales analogy, or or does that land in in mentoring conversations that you have?
Yeah, I think I think I understand what they're saying.
I'm not sure that I fully agree.
I think that like I think AI has limitations in giving you judgment.
I think AI has advantages in scaling customer science, but I don't know that it's a shortcut to the practice itself.
The only way I can think of it as a practice is that there's this idea, like everything we build seems so permanent, right?
It feels like because of how long it takes, it's a sudden gravitas to a thing.
If it takes a month or two, you don't want to break it.
It feels special, it feels like China to you.
But if it takes a day, it feels more impermanent, it feels more disposable.
So you can punch it a bit and you can shape it however you want.
I think that's the way I think that AI will accelerate the the craft, is we will embrace impermanence and then use the early variations as a way to find the perfect thing.
And I think that that process of using AI to churn out the danger with churning out many variations is that you get fatigue, right?
You get fatigued.
But if you do it properly, not too much, but not too little, you can use it to practice like the scales thing.
You can use it to test.
Even this is something super simple.
You can make 10 variations of a document with Claude or with Open AI.
And even if it's not about what, you know, it's not a soul solving a thing, even if it's just about which variation of this does my boss like.
Now you have 10 ways to figure out, right?
And there's something important there because very quickly you find out the right one.
Um I'm an ADPTSD from writing specs, you know, back in the day.
And then being afraid.
Yep.
And getting into a room and being reviewed by 10 people who could decide your bonus or your salary.
And but you only made one.
There's only way there's only what you know how the trick is, you sort of you review before the review.
What if you reviewed multiple different versions and you know feedback?
So by the time you got to the actual review, you reviewed the perfect one.
Yeah.
That kind of thing can help you with that.
Yeah.
Point well taken about it's it's certainly not a shortcut to judgment.
And I I would never imply that.
I think what you're getting at about generating 10 versions of the PRD is is more along the lines of this idea that I've heard called proto thinking.
So it's not it's not thinking, it's thinking thinking about how we think.
So when you're when you're prompting an AI, you're not telling it necessarily all the steps.
You're you're thinking through how you think about problems, and that externalization of thought is is what's been valuable for me because now I I you know it's kind of like a explain like I'm five trope.
I have to tell someone else.
I I have to teach someone, and the you know, you you develop expertise by teaching.
So AI for me has become a a boon because now I'm able to tell someone else how I'm thinking about a problem, which has in turn made me a better problem solver because I'm getting it out of my head.
I'm not staying up here.
I have to be able to explain what the problem is in ways that I never used to have to before.
So I like I like that idea of sp you know, and this connects to something we already talked about.
AI aspiring partner.
Yeah, right?
Yeah.
Um I I think it's just because of the modality we use now.
I use AI a lot to architect stuff.
Like I have my architect brain, and then what I have to explain to someone who's gonna do something is like a contractor.
And I think you're right, the act of explaining it sometimes clarifies your thoughts, just like, you know.
And you know, some I remember walking in a in a pod, like one PM, a few developers.
The developers don't really function as that.
I need another PM.
And those other PMs are busy building their thing.
So AI as AI as a aspiring partner is pretty dope.
I like that.
Love it.
Uh one do you want to shift gears a little bit?
You know, at industry, you've been speaking about the three speed problem.
I'd love to, I mean, I personally love to get a refresher on it.
Um, and for the right lesbian who weren't at industry, you know, what is it?
Why is it important?
Yeah, yeah.
So uh let me just set it up.
So for the past 30 years or longer, actually, since the digital revolution, we we've been constrained by engineering speed, right?
The the biggest cost to the technology company is paying developers or hardware designers or whatever it is, right?
Because I'm not assuming it's all software.
And so this is where the ratios come from.
You know, 1 pm seven developers or whatever that looks like in terms of averages.
And so fewer developers, fewer designers, because building is difficult.
And building is difficult because of the way that we program CPUs.
But in a world where code is just language and architecture, meaning you can speak Tagalog or indie, but if you have an engineering mind, the constructor's mind, the master constructor's mind, let's go back to Lego, then you can write code.
You don't need to learn syntax anymore.
Yeah, you just that's that's what code is.
And also one of the big capabilities of large language models is content generation.
And that content can be English or it can be Hebrew or it can be code.
Of course, it can also be pictures and architectural plans or whatever else you train it for.
Well, that means that we now have infinite code engines, basically.
And so code is not gonna be scarce within five to ten years, it will be just everywhere, and it already is everywhere, basically.
Now, think about that.
There are three things that companies do to build great technology products, and also three layers to building a technology company, which is an entirely different thing.
But for the product side, it is customer science, it is again construction of software or hardware.
And then it's it's the moving from that into getting into customers' hands, telling stories, staging it and packaging it, whatever you want to do.
That middle thing, the building the construction used to take all the time, right?
So typically you start with maybe a month to synthesize customer science, take you three months, you broken up into sprints, and at the end someone releases something or invaluable.
This middle thing is gonna take no time at all, right?
In theory, right?
Because it has to go through people, we understand the mythical man month, it will not be nothing, but it is something, but it's much faster.
Theoretically 10x, say, but maybe even more.
And these two things, because they depend on people, right?
You gotta do customer science because you talk to people, not just synthetic, synthetic people, and then of course you're gonna sell this to people because they're gonna give you dollars, right?
You're not gonna just sell it to their your agents, maybe one day, you will sell it to their agents.
Who knows?
Um, but it's an unbalanced equation.
If you do any math, the your equation just became unbalanced.
And we spent a lot of time balancing that equation.
40 years.
Right?
Waterfall, test-driven development, agile.
Name every variation of people who understand uh life cycle, take on software lifecycle management, and the debate's rage on, they rage on.
So we now have to rebalance it.
And honestly, because that part was some of the hardest things we did, it's gonna take some time.
So this is what we call the three-speed problem.
You'll s you know, at at the industry, what I said the trope I used was like your CEO is gonna code the feature, and then he's gonna be like ship it, and you're gonna be stuck.
You're gonna be like, holy shit, this dude controls everything.
He wants me to ship his shitty code, which has uh SQL injection errors.
Now, what do I do now?
So um that's a three-speed problem.
All of us are gonna spend a lot of time balancing that equation, finding the practices, the team structure, the team ratios, the new AI tools that help us keep this thing fast because we want to slow it down, but then speed up customer science and speed up GTM.
And I think the next few years, you know, from Lovable to whatever comes next, we'll be about figuring that stuff out.
And there'll be a lot of money made when people figure it out.
I didn't offer a solution, but I guess I'm pointing out a problem.
And of course, at Product Mind, we have recommendations for speeding up customer science and solution, you know, problem discovery and solution creation.
You know, we spend very little time on the go-to-market, which is a mistake, by the way.
I think that that's a place where there's a huge amount of opportunity for product people and our thinkers and founders.
I mean, it's yeah, identifying the problem is kind of a key step, right?
As opposed to just spinning around in circles hoping that hoping that it just works out for us, right?
Yeah, kind of that kind of brings us back to the first principles that you were mentioning, right?
The first part of the of the three speeds and doing discovery.
Yeah, I'm curious then, you know, in this new world, what what are the skills that product managers really need to double down on?
Yeah, you've mentioned storytelling.
What else?
Yeah, look, I think there's some old skills that I want to mention because I think that even those are worth uh bringing up because a lot of PMs don't have them.
I think there is leadership, you know, learning, you know, being the kind of person that people follow, a lot of has to do with judgment and so on.
There's communication, which is slightly in a point guard.
You gotta the team gust gotta know what they're doing, right?
Everybody, up, down, sideways, right, downwards.
There's customer science, all the things in the grab bag of PM of interviewing, synthesis, applying creativity, coming up with a solution.
There's creativity itself, which is, you know, two people can look at a problem well defined, and so one c some come up with like a pedestrian solution.
And another one comes up with a brilliant solution.
You look at it, all you're like, Holy shit, what did you even think of that?
That's creativity.
And then, of course, it's just the ability to ship.
All right, you gotta put code into people's hands.
You gotta put code into people's hands, you're gonna keep doing it.
And so those are the things, five things that I personally look for when I hire and I've hired like hundreds of PMs.
But now, because the tools have changed, because the world has changed, even though people appreciate it or not, what are the new skills you gotta layer on top of that?
Because those skills don't ever go away.
But what are you gonna lean on it?
And so the way I talk about this is the first thing is just like curiosity, right?
We are in day one, as as Bezos would say.
When day one, I know nothing now, and you know nothing.
Our instinct is to protect our experience, or maybe your high salary, and and if you do that, you're like, Oh yeah, I'm still the man, I still know people, I still know shit.
But look, very few people made it from pre-internet to internet, right?
The the the old people were protecting their egos, and they got swept away because they tried to build the old thing they built, uh, in the new way, but the new medium that required brand new thinking, and so they you know maybe they're already rich, but a lot of people weren't rich, they just lost their job.
So the point being, you're gonna come at this with curiosity with some humility, and then the last one is agency, right?
Agency meaning whatever you learn, turn it into action, turn it into suggestions.
Uh, don't just tell the salesperson you can't have the feature.
You say, Well, you can't have that one because that's dumb.
But how about this new thing that we could do?
We make some money and you can get your bonus and I get some stuff into customers' hands.
You mean to have agency, you need to not wait for permission to build a prototype of something that your organization cannot imagine, but gives 10x acceleration, and then you say, Hey, 10x acceleration, doesn't that sound good?
How about all these your stupid like restrictions that I can't use Chat GPT?
What do you think of it now?
And that's how you go.
That's how you go forward.
And uh, so I I talk a lot about that.
But look, the hard skills are already coming to focus.
It's you gotta be able to prompt really well, you gotta be able to write evals, you have to be a PMS PM.
You have to build a prototype.
You gotta build it.
The the first two prototypes are three, right?
That's your new spec.
Your prototype is a new PRD.
Why would you write a document in 2025?
Uh no, by the way, I say that as a joke.
It prototype without the uh markers of why it's important, meaning like what's the vision, what problem you're solving.
You know, because code is just code, it's like a picture, like, but it's not just a picture, like in iOS in the XF data, you can add more information, right?
So we're gonna create the exit of our prototypes and add the information about the vision, the goals and the what on why it's important, why where we're doing this.
But if you just pass on a prototype, it's it's uh it becomes completely fungible, it becomes ephemeral.
Yeah, and so that's what we should do.
Not developers write code, we write code and tell why write prototy when I put it like say why this prototype matters and why the ways to take it forward and explore in places that are unknown.
Well, but that's way worth more than a picture.
Well a nice stigma, if that makes sense.
Right.
So that's what I was saying.
Yeah, yes, I would say through City Humility agency, and beneath that, they've all been skill sets of constraining models properly, writing actual code versus writing PRDs.
Oh, building process.
Like one of the things that we do is like the the uh point guard is a guy who sets up how the thing moves.
That's process, right?
So what is the new SDLC process on your squad that you've optimized?
You gotta be able to construct that, if that makes any sense.
Those are some of the skill sets that are emerging that we need to build.
The the first is you you mentioned the skills about communication, and I think the golden rule of communication, you've you have two ears and one mouth, so you should be listening twice as much as you speak.
I think that's you it's so easy to churn out AI slop and you know, we can all kind of detect it, our AI meter, you know, we've we've all kind of calibrated to like, oh, like obviously that's copy and paste.
So I think learning to to listen more and and communicate well means that we're uh we're editing, we're going through the the problem solving and and crafting and drafting process.
I think that's more important now than ever.
That that was the the first thought that I had.
The second was your mention of ephemeral, so it's probably a whole separate podcast in and of itself, but my as a as a futurist, I believe that the UI of the future is gonna be much less about a user journey as we thought about it in the past, like I have a problem, I'm gonna go from step A to B and I'm gonna have these delights and experiences and frustrations and goals and it's gonna be much more like the UI asks us what we want and then it just does it and then the pixels will generate and then be dismissed when they're no longer needed.
I I I believe that products in the future are gonna be much less about screens and and widgets and chiclets and drawers and tiles and and more about what do you want to do and then it just kind of does it.
Again that's probably a a a conversation for another day but the less we're I I wanna I will I want to weigh in on that I I do think that in in the gaming world we've always had generated we there's this whole trope about generated worlds right generated experiences.
And in the last five years they've become pretty sophisticated like um this game I don't play games because I don't have any time but I pay attention to the innovations there.
And I think there's this open world gang where you can basically explore like almost an infinite set of planets and it's all procedural regenerated.
No man's and so no man's guy.
There you go.
There's a gamer right there.
So you've been identified, brother.
I'll take it.
I'll take it.
Crabley.
So no man's time and obviously all the clothes that come after it.
Um so that's exactly what's gonna happen with user experiences, right?
The the one of the capabil we I don't like using the word artfield intelligence, right?
I talk about five things that like to tell the intelligence gives you in the your unique things that it gives in the toolbox.
One is content generation, the other is MLP in and out.
To the third is uh data synthesis, right?
And correlation.
Uh fourth is autonomy, right?
And I think the fifth is I keep forgetting the fifth always when I talk about this, I forget the fifth.
But anyway, the the interesting thing, oh personalization, that's right.
And that's the one I actually needed.
So these things can personalize to eight billion people, which is risky.
Ethically, this is like mad, right?
If you thought Google was like targeting content to you or Twitter or TikTok, like we're about to enter an era of pure separation.
Everything is for you.
So the but the point is, at least for user experiences, is you will go to one of these AI experiences, it will sort of memorize stuff about you, and then if you want to drive software, it'll generate the user experience that's for you for you that you understand.
Again, it will use some of the principles that I've talked about, simplicity, but you will understand it.
And the next person comes and said the same thing, and it's will generate the thing that they can understand, if that makes any sense.
So, yeah, we're gonna have procedurally generated user experiences, and it will be amazing, right?
Because then the learning curve of software, which we've dealt with forever, from command line to menus will disappear.
And then this will become a truly like species-changing thing.
Like everyone will it'll be accessible to everyone, which is yeah, as we can tell.
Hopefully, I can tell me a good story right now.
It'll be amazing.
I just heard uh bunch of storytelling, storytelling, see.
Yes, that's a great story, right?
I I feel like a bunch of design just screamed in terror and they don't know why.
No, design design systems are going to go the whale the dodo.
They are going to whale the dodo.
So tell let's let's uh let's spread that gospel so people are people are sufficiently afraid.
All right, pick picking fights here on product momentum.
Fantastic.
Um Audie, this has been a great conversation.
Have a few big takeaways out of you know, probably three dozen.
Wait, Paul had another question.
Come on.
So I'll I'll squeeze it in.
We can we can uh we can work.
Yeah, so it's segu segue out in post.
The the question the question I I I hope this is a succinct question, and I think it it might be a good one to wrap on, is forever we have conflated the idea of skills with role.
Like I am a product manager, therefore I have these skills, and I think what you've been talking about in uh throughout our conversation has been these are the skills that are evergreen, regardless of the role or title or technology, um, communication, storytelling, the meaning, the meaning making that that product managers do.
And I think what what we're kind of all been talking about for the uh conversation today has been saying you're a product manager is becoming less valuable than honing the skills of communication and the skills of problem solving and the skills of team building and being able to do discovery.
And it it's even hard to talk about because when you post a job opening, you post for the role and you and you list all the skills as if they're the same thing.
But I think the role that product managers fill is becoming a different role, but the skills are starting to to uh become preeminent to the role.
And that that might be too much of an abstract take, but as you've been talking, the the skills aspect of it has been kind of top of mind for me as you're kind of uncovering the the shipyard methodology, the three speeds, where the bottlenecks are, all of these things come back to honing those skills that are agnostic of the role that we fill in the organization.
Yeah, look, I I've always thought the the skills, the mindset was way more important.
I think that the role title just gives us a way to put it in a box, yeah, and we can ship it.
But it the the title isn't me.
Look, Microsoft calls product managers program managers, right?
And they've refused to they've refused to change.
Um, so that was an early so far.
Early part of my degree, I was called a program manager.
And so yeah, the title is nothing without the skills because the skills, some people have shitty skills.
Like even the thing, the five things I talked about, a lot of PMs aren't good very good at it.
In fact, I don't think people synthesize those five things really well right basically or even talk about it.
Like we don't sing from the same hand sheet basically for those things.
So you sort of make it up in different ways.
And you know there's a lot of variations of PMs platform user experience whatever.
I don't really believe I believe in a full stack DM so that's a whole other podcast.
Yeah so but yeah I agree with you is a skill set the skill set is is maybe the only thing that matters it's also a niche skill set like I said it's not a lot of pedagogy there's only apprenticeships.
So um which by the way bothers me which is why we I wrote the book because I want more people to have the skill sets and if you go from the the first part of the book is like the core things skill sets and skills you need to do to ship really great products.
And the laugh out of the team is how to lead people who have those great skill sets in a larger team and uh you can it it's unlike any product book you've read because it starts from simplicity to pricing right versus all the bullshit that people talk about like data nah.
So uh so and I I I yes, I agree with you.
I don't think there's much more to add to that.
Well, I'm glad we got that one in, right?
That that's an important one.
Actually, what like was one of my takeaways, right?
Yeah, in the in this world of AI, new tools, right?
Gotta gotta stick to first principles, have to maintain those skills, yes, of of storytelling, being yeah, being communicators, right?
We should use AI to improve our product work, but we shouldn't use it as the first draft writer, right?
I think yeah, that that was a good one.
Um, you know, experience doesn't equal judgment.
Judgment is super important in our role as product managers.
We build that up through making good decisions, right?
And in order to make good decisions, we need to make sure that we have good mentors, right?
We're talking people who are smarter than us and we're making mistakes, right?
We're learning from our mistakes.
And then yeah, one of the last takeaways I had was in this world of AI, right?
Maybe if the cycles for kind of coming up with solutions get faster, we come become less attached to them and then becomes easier to iterate, or we're not we're not living in the world of like sunk cost of like, hey, we just spent a year on this, like this thing needs to last forever.
Like we spent a day on it.
Let's let's keep going, let's keep making it better.
Uh let's learn quick from it, yeah.
Yeah, mindset, sir.
Yeah.
Before before we go, um something we'd like to ask all our guests.
Mostly I do it selfishly so that my goodreads list gets longer.
Uh yeah, what's in your bookshelf?
What are you reading?
Wow.
So I read a lot of uh my work is still is very my my work in my brain tends to be serious, right?
Uh so I have uh one of the books I met Tony Fabell last year and he signed a build, his book build.
Uh Tony is a legend, you know, X uh Apple X Nest, I guess.
He created nest.
Um so just a real legend.
And if you don't know Tony, he before he did Apple he built there's a company that died.
You do you know the company?
Uh Tony worked at it's not mutant.
It was something before the mutant that he created.
So just incredible thinker.
So I recommend that if if it's nonfiction but I spend a lot of time reading fiction because that's the way my brain gets creative.
So I the the book I'm gonna try to get into is um a science fiction trilogy by NK Jemison right I think the she wrote a trilogy and she won three Hugo awards even more than in a row.
So that's better than Ask Timov so I'm gonna get into this over this holiday.
Awesome.
That the Broken World trilogy yeah yep love that oh it's been a blast I learned a lot um thanks for coming and joining us thank you Danielle thank you Paul this was a pleasure thanks, OG.
Been a blast.