[On-demand] Product Management Webinar: Indispensable PM

[00:00:00] Janna Bastow: Hi, folks. Welcome. Come on in. We’re just getting this webinar started come on in, get settled, find the chat, say hello. We’d love to find out where you’re all coming from. Welcome everybody. I can see that there’s already quite a lot of you here settling in, and I’m sure there’s a few more who are gonna be rolling up in the next few minutes.

As I said, come on in. Welcome. Find yourself over to the chat area. Say hello. Oh, I can see somebody saying hello from London already. Hey, hi there. Good to see you. Nice to have you here. Thanks for coming. Myself, I’m in Brighton, UK. Not sure if there’s other people from the UK or around the world.

But excited to have you here. I can see people from… We’ve got Matt over in Austin. Hey, Matt, good to see you here. Tommy from Austin Ben from Iowa Kerry from Bristol. You’ve got Scotland, Orlando, all sorts all over the place. This is fantastic. Oh, there you go, somebody in Hove.

Hey, Dominic. So, good to see you all here. We’re gonna kick off in just a minute. And just wanna make sure everybody gets settled in. In the meantime, feel free to open up [00:01:00] the Q&A section. Jump in there with any questions. I’ll be trying to keep an eye on them as we go through this chat today.

Or use the chat. This is gonna be much more of an open conversation here today, rather than following a strict plan. I’m excited to have you here, and we’re gonna kick off in just a minute.

All right. So big welcome. Thank you everybody for joining here today. We’re gonna be talking about how to make yourself indispensable in the age of AI, and this is actually… I put this together as a reaction to something that I was seeing out there. Because someone posted something about the fact that AI is gonna take your job next year.

You’re gonna lose your job to AI. And I just thought it was sensationalist, and I thought that it needed us to really ground ourselves in this conversation around why we’re not gonna lose our jobs to AI, and how we make ourselves indispensable so that we don’t lose our jobs to AI. So as you can imagine, I’ve probably got some interesting counterpoints here.

But I wanna hear your fears. I wanna hear your thoughts on this as [00:02:00] well. This is such a rapidly evolving conversation that I literally don’t even have slides today. This is based on a bunch of notes I’ve been taking on Post-It notes in front of me, and some conversations I had at MTPCon earlier this week, and just generally with product people that are all around me.

So thank you everybody for making the time today. I know we let you know about this one much more last minute than usual. But it should be a really good chat. Now, before I dive into it, I just wanna share a little bit about what we’re here, doing here at ProdPad. I can see there’s a bunch of friendly faces in here, a lot of longtime supporters, thank you all.

If anybody doesn’t know about ProdPad, it’s the tool that myself and my co-founder Simon built when we were both product managers ourselves, and it’s the tool that brings everything into one place. All that context about what it is that you’re actually building. What’s the vision? What are your goals?

How are you tracking against those goals? What are your customers saying? What sort of decisions have been made about what to build next, and what’s working, what’s not working? So all of that in one place that you and your team can use to basically help you make better decisions about what to build next, de-risk that next piece of work, make sure that the things that are going [00:03:00] in are in fact the right stuff, so that you’re not just burning developer time or burning tokens building stuff and not getting the impact out of it.

So it’s very much a tool for teams who wanna become outcome focused, who want to make that impact. And it’s completely free to try. We’ve got a sandbox version of ProdPad that you can jump into. It’s basically got all the different sorts of lean roadmaps, Now-Next-Later roadmaps, and OKRs, and feedback, and stuff like that, all sort of playing in one space that you can freely explore, edit, play with.

And then you can create your own account from there. Give it a try. We’d love to get your feedback on it. In the meantime, let’s dive into what we’re talking about today. And as I said, this isn’t a slide… sorry, this isn’t a talk with slides and everything like that’s been prepared way in advance.

This is a rapidly evolving conversation. Because I wanna talk about how we actually do make ourselves indispensable in the face of AI. Now, I think it’s really important to realize that product people are really unique, right? We are the most adaptable people in tech. I don’t know who here is of the same sort of cohort.

[00:04:00] I got into product 20 years ago. And I know that product people have historically over this time just tend to come from different areas outside of product, before product even really- existed as a discipline. And we were almost the jack of all trades, master of none, the ones who were developers but got a little bit more nosy into what the customers were up to, or were in the design side and wanted to try our hand at a bit of coding or, in my case, I was a customer support rep who’s good at talking to the developers and the customers.

I’ve seen people come from all different sorts of walks of life and adopt this way of working, this product way of working, many of whom weren’t even called product people for quite a while, even after they were doing product management. And so product people are really unique in that we are so adaptable, right?

We’ve got all these different skills, and we’ve seen these skills change over the history that that we’ve been honing this discipline, honing this craft. Product managers, we tended to come from a wide range of different backgrounds, you know? Anybody here… Let me know actually in the chat where were you?

What were you doing before you landed in product? Did you land in product accidentally, like me, [00:05:00] or did you, set out to be a product manager which we’re seeing with some of the the newer cohorts of product managers. Myself, I came from customer success support sort of thing customer success before it had that name.

I’m seeing people saying that they came in as a develop- oh, I’ve got everything. Yeah, I guess business analyst is a really big one. Anybody here a project manager before all of this? Ops hospitality mechanical engineers developers I saw marketing in there some UX design, all sorts of backgrounds, right?

And we’re all the people who are the type who got our hands in too many different places and fell into this role, right? It’s the classic jack of all trades. And this is actually, this AI stuff is a dream for many of us because it’s allowing us to be the jack of all trades and master of none and instead of necessarily relying on gaining those skills, like learning how to code as a product person, which used to be a thing, or learning how to write really sharp copy or learning how to do designs, you’re actually able [00:06:00] to create more and be the person who connects the dots, who sees the connections between things and sets stuff off in motion, which is a really powerful place to be.

So what I’ve seen over the years, so you’ll know that I’m one of the founders of Mind the Product, so I’ve been involved with the product community for years and years. And what I’ve loved about Mind the Product, I was actually there this week. Was anybody else there? And it was really fascinating to see what the conversations were about. Because over the years, while the conferences haven’t been themed per se, it created a space to get a sense as to what the general discourse was about at that point in time.

And when we started Mind the Product, when we first started talking to the product communities, this is going back about 15 years, the conversations were very much around, well, what is product management? Am I a product manager? Right? There were people who were still figuring out that they could do product management, or actually, they were already doing a lot of product management and how to get into that role, how to get their foot into it, how to get that step up.

And the very early conversations were very tactical, right? It was stuff about learning the frameworks, [00:07:00] learning the vocabulary. And then over the years, we started seeing the conversation shift, and we’d see this come to a head at these conferences we were running where we started talking more about more of the strategic work, right?

How we would set in place a larger plan, talking about roadmapping and start talking about OKRs. The conversation would shift to things like psychological safety and setting autonomy for the team, creating alignment. It we’d set conversations around outcomes, right?

How to get the team directed towards these right outcomes, how to create impact. There was then it sort of shifted towards accountability and ROI, how to make sure that the work that we were doing was actually really useful was actually Going to provide value for the business. So there’s a shift in the last few years around that.

And then this year, I mean, what do you think the conversation’s all about? It was all about AI, right? It was basically, it was just build all the things which I love to see. There was a lot of excitement. There were a lot of good conversations in that room. But very [00:08:00] much the conversation was around just building all the stuff.

There’s a bit of a frenzy going on right now. And I think it’s actually worth addressing that because I think we’re in another cycle, right? I’ve been here long enough now that we’ve seen this cycle sort of go round. You remember when Agile became a thing.

Agile wasn’t as, always as widespread as it is, but there’s actually some things that are in common with what’s happening right now. Agile allowed us to build faster. It allowed us to build in shorter, sharper iterations and get more out the door with a more efficient team, right? So we’ve been talking about Agile, and we take it for granted nowadays because back in the day, that wasn’t necessarily the way that teams worked.

They worked in a much more of a waterfall way, and this Agile thing was something to learn. We had to learn the tactics around it. And at the time, the Agile conversations were around the little outputs, right? We talked about story points and velocity and burndown charts and things like that, right?

And it was important to have those conversations, but looking back on it, we realize that we had to have all the follow-up conversations as well. Like, so what we did a [00:09:00] lot of story points. So what we had a good burndown. We’re actually in a really similar sort of place right now. I feel like we’ve gone full circle or, back on a similar sort of wave where we’re talking about AI, and the conversations around AI right now are very, very outcome…

sorry, output focused, right? People talking about how many lines of code they can ship in 30 minutes or whatever, right? How many products they can deliver. There’s somebody at Mind the Product who talked about how he and his team shipped nine live products in the last two months.

But there’s no conversation there around did they work? Is anybody using them? Did they add value to the business? The conversation seemed to be more around there’s more anxiety around token costs rather than impact on the revenue. And the sense that I got was that the conversations that we’re having this week and this year, that we’re having right now, are going to encourage a whole bunch of people to build a whole bunch of stuff.

There’ll be some great things coming out of it. There’s also gonna be a lot of spectacular failures, right? The people who are making these spectacular [00:10:00] failures are making them right now, and they’re gonna be telling us about them in a couple years’ time, right? So we’re gonna see the conversation evolve into something that probably looks similar to what we’ve already gone through.

We’ve already covered topics like how do we make sure that all this output is measurable and is actually making an impact, right? Now, it feels scarier right now because it is moving faster, and it’s not just shape, it’s changing how we deliver, right? The conversation around AI isn’t just how we deliver and how we as individuals or as teams use AI, but it’s also around what we deliver to our customers, right?

There’s new expectations that customers have. And actually if anybody was at MTPCon, or if you weren’t, then th- one of the talks that you definitely wanna catch is the one from Christian Idiodi. He was the opening keynote, and he was talking about AI in the future and where we’re going with things.

And he made a really sharp point, which is around how, as capabilities rise, expectations rise with it, right? So- [00:11:00] Here we are. We’re now able to ship our products faster. We’re able to, get the grunt work out of the way done and dusted. It doesn’t mean that we’re now going home early and taking shorter work weeks and that sort of stuff, right?

I mean, some people are, that’s great. But in general I mean, we live in a capitalist society, right? As we’re able to create more, as we’re able to improve on stuff, we’re going to do so, and expectations will rise with it, right? So as Idiodi was saying, like personalization is gonna get more personalized, right?

The quality of apps is going to go up. The expectations that we’re gonna have is going to go up. And AI doesn’t know what these new expectations are, right? These are new sort of bubbles of expertise that we’re gonna have to build into the way that we work. And AI can copy yesterday’s apps and make your app look like just like everybody else’s.

But when everybody else’s app looks the same, customers are going to expect more from that, and there’s going to be teams out there, there’s gonna be people out there who are gonna be able to identify different ways to improve on these things. And that will become the new [00:12:00] standard, right? Those will be the ones that stand out.

And so, what is delightful today is gonna become tomorrow’s baseline. You’re probably all familiar with, or if you’re not, you need to look up the Kano Model, right? This idea that the the effort that you put into something proportionately gives you back performance or satisfaction from your customers.

Some things you get proportional… disproportionate amount of satisfaction from your customers, right? You put in a little bit, and you get a lot more out of it. And other things you have to put in quite a lot of work in order to just meet those bas- basic expectations of customers, right? Having even a basic chatbot like a ChatGPT, an LLM-powered chatbot was a delighter for many apps a year ago, but now is becoming more of a basic expectation.

And as we continue to create more and more and more and we’ve got different people trying out different things, we’re gonna find that the quality of products goes up. The expectations for the quality of products go up. The number of products will go up as well, right? And our role as product [00:13:00] people are going to be to explore those edges, and we’re gonna be able to explore those edges because we’ve got the tools to help us handle all the work that comes before it, right?

All the the grunt work and everything like that. Now, there are gonna be some people who are feeling threatened by AI, right? Some product managers made a buck, made a lot of bucks basically just shuffling around backlogs and rewriting strategy decks in different formats and writing user stories and that sort of thing.

But we’ve known for years, right? We’ve been talking about this for years in the general community, that that’s not product management. That’s the stuff that has to happen so that product managers can do their jobs, right? Make those crucial decisions about what to build next and communicate that stuff.

But actually, there’s a lot to be said for taking out that grunt work and giving product managers more space to do the things that matter. And so we think about the things that do matter. We’ve talked a long time you know, we all know Steve Blank’s quote “Get out of the [00:14:00] building.” And for years, a lot of product managers really struggled to get out of the building.

There were entire talks on, tactics to do so in a cheap, fast way to get in front of your customers because you were so busy doing everything else that you didn’t have time to get out of the building. Well, hey, good news is that we now have time to get out of the building, right? Like, where…

all the other jobs have been done. And so that’s where it gets really interesting is, the people who get out there and take a look at the market really, really listen to the customers, watch them do what they do figure out how people are using the tech of today, people are using the competitors of today, and then coming back with those insights.

And yes, using AI to synthesize those insights, to help them dig through them, to help them move faster with them, to try, a dozen variations instead of two variations. Lots of different things we can probably be doing with AI to speed this stuff up. But the core of it, which is really truly understanding that market, really truly understanding the customer need, is still gonna be needed.

And as a matter of fact, I think needed more, because as we create more and [00:15:00] more products, we’re just gonna end up with a lot of noise, and it’s gonna be really difficult for customers to figure out which things are good. And so creating products and experiences that stand out is gonna become more and more of a honed skill that product managers using the same methods that we had before will be able to discover and bring into these organizations, bring into the products that they’re building.

So I’m actually truly excited about what’s happening. As I said, I know that there’s some people who are feeling a bit threatened by it, but honestly, the product managers who really wanted to get out there and do the product management, this is a boon. This is a huge boost for us. And I can see there’s lots of stuff going on in the chat.

I haven’t been able to keep up with all that as I sit here and rant, so I’m just gonna have a little squiz and see if there’s anything that that I can speak to. If you guys have questions, by the way put them into the Q&A, and that way other people can see your questions. You can vote them up and that way I’m able to to spot questions amongst the chatter as well[00:16:00] 

Now how am I doing so far? I’d love to hear from people as to whether this resonates with what you’re hearing whether you’re seeing other stuff out there, whether you still got fears around this. Where does your head sit with all of this conversation? Now, one of the things that I like to do when I talk about AI, particularly with people outside the space, is compare it to plumbing, right?

And there’s a couple ways that we can do this, right? First of all I mean, I’m here in the UK. We’ve got Victorian plumbing. That’s like the tech debt built right in, right? And there’s always going to need to be people who manage that underlying plumbing and everything like that. There’s this expectation that stuff like plumbing, the hidden stuff, just works.

And coding is like plumbing, right? You don’t care how the login form works. You just expect the login form to work. You don’t care how your email or that message is delivered. You just expect that it’s delivered. As to whether a human crafted that piece of code or a human coded that or an AI coded that, [00:17:00] it doesn’t really matter to the consumers.

The expectation is gonna be that our design and development teams are going to be using AI to speed up the stuff that can be sped up, the stuff that’s invisible to users. And so this is where we really see AI coming in and creating big changes for how we work, right? Because consumers are not going to go for the artisanal version of a website.

And actually, I thought about this and thought maybe there will be a a space for that, right? I was musing on this about the fact that maybe there’ll be a market for handcrafted websites and we’ll put on the bottom of it, made by a human sort of thing.

Who knows? Maybe that’ll be a thing. I’m from the generation who used to build in XHTML, and I remember having those little proud tags being like, “This is XHTML compliant.” So perhaps there’ll be a subset of that. And I don’t think AI is gonna take away the art. It’s not gonna take away the the artisan market in many places, right?

So with websites, again, no one really cares how your login form was developed. But when it comes to things like art itself [00:18:00] I see it as just another tool that artists will use. Just like how- if you wanted a portrait of somebody, you used to have to go get a painting done and it would take a long time.

We now have photography. But just because we have photography doesn’t mean paintings went away. As a matter of fact, it actually allowed painting as a craft to evolve. And I think digital AI is going to give artists new tools. We’ll see some really interesting stuff coming from AI artists, but we’ll also continue to see an interest in offline media, right?

There’s still a market for real paintings. When you think about what art is, the perceived value is in the talent, the time it took, the effort that went into it, and the emotion that went into it. And so there’s still gonna be a market for the artisan stuff. But when it comes to things like, I don’t know, a piece of stock photography where you just need to communicate the message in an image, that’s where we’re gonna see AI coming in and sweeping up and [00:19:00] leaving only smaller pieces for the artisan sort of side of things.

Taking this back to plumbing, one of the other ways I’ve looked at it is somebody made a point recently about how with this old Victorian plumbing, if you had a plumber 100 years ago, if they were gonna fix that plumbing, they had old tools probably, just trying to figure out how to make that plumbing work.

Nowadays, you have better tools, right? We’ve got plumbers with what are those snake camera things? You wouldn’t pay a plumber extra just to use their artisan tool process to unclog a drain. You just expect it to work, right? And so you’re gonna go with the plumber who has the tools that allows them to go faster, and therefore, they’re able to deliver cheaper.

People are going to expect that things like underlying code, the things that they can’t see, are going to be done as quickly and as efficiently as possible, and if that’s using AI, then that’s using AI. But that’s not the part that’s most interesting to your, to you as a product manager, [00:20:00] right? I think product managers have long been held back by having to do things like spec out the same sort of pages over and over again.

Like, who here has specced out something like a login flow? I know I have multiple times with multiple different apps. And each time you spec it out, it’s probably, like, several pages worth of specs, right? Rules as to how this thing works. And ultimately, shouldn’t every login page basically work the same, right?

Like, there’s nothing special about your login page. It should work just like all the rest of them. And this is allowing product managers to now just say, “You know what? It has a login. And yes, make it look like everybody else’s login. I don’t want new functionality. I don’t want surprises. I don’t want new usability quirks in how something as simple as a login flow or, a tag management system or whatever works.”

It’s going to allow product people to now think about The other chunk of their app that makes it special. So let’s say it’s an 80/20. I don’t know whether that’s exactly it, but 80% of your product is kind of the boring [00:21:00] stuff, and it’s the same as everybody else’s, and that’s fine. It should be the same as everybody else’s.

It should just work. You don’t even question why and how it works. It just works. But what makes your app special? What makes it valuable, different? What’s your moat? What sort of things can you add? And now that we can spend more time in this, we’re gonna have more products pushing the envelope on what what really makes them stand out.

So I’m actually really excited to see what we’re gonna be using or how we’re gonna be using this tech to give ourselves the space to think bigger and to push the envelope further, right? We’re not just going to build the same app that we would’ve built two years ago and then take the rest of the week off.

We’re gonna build the same app we would’ve built two years ago in the first day and then spend the other four days pushing the envelope, doing something interesting. And it’s when you get all these different variations, all these different new experiments happening, not just within a company, not within of a team, but across the entire discipline, that you start seeing real innovation.

And it’s gonna be product people, right? The people [00:22:00] in the middle talking to these different sides of the business. And whether those sides of the business are agents or are real people, it doesn’t really matter when it’s the underlying stuff. But when it comes to the innovation, it does matter, right?

It matters that you’ve got people really looking at what makes a difference for the market and what’s really valuable for the customer and what’s really valuable for the business, and tying it all together and trying stuff in that area to make the calls about what sticks.

And somebody else made a really interesting point in- I might follow up with this article if I can find it again. But it was talking about how AI is not gonna fully replace humans, and they made the point that over the years you can always see that where humans have been able to add tools to the process. Adding those tools to the process and keeping the human in is more valuable than just having those tools.

And so the argument goes that, yes, something might be more valuable, might go [00:23:00] faster, might be more efficient, might be better in certain ways if an AI does it. But having a human plus that AI is always going to be more effective. It’s always gonna allow you to push it that much further, do more with it.

And so it’s not so much about whether AI is going to take our jobs, it’s like it’s going to allow us to then use AI to further our jobs, to do more with it. And again, for product people or for people who are doing stuff that is really easily replaceable by AI, they’re probably not gonna have the same job.

None of us are gonna have the same job. But as long as we are adaptable, which we are, ’cause we’re product people, we’re gonna be able to use these new tools in order to further our own careers and do so much more with it

I was saying this to somebody the other day, this is at MTPCon, about how AI is like having a number of direct reports, right? You’re now orchestrating these different direct reports, and being threatened by AI is a little bit by like being threatened by your direct [00:24:00] reports.

It’s like, no, you just got a promotion. You now have a team of three people, and you can do so much more. You’re not threatened by your direct reports. They’re enabling you and your team to do so much more. Your AI agents, right? They’re not gonna take your job. You’re gonna work with them to do more as a team.

So think of them as a team rather than as something that’s gonna take your job. Your job all of a sudden got more interesting because now you’re directing. You are setting the pace. You are pushing the envelope on what can be done. So this is why I’m really excited about it, right? It’s not gonna take product management jobs.

It’s gonna allow product managers to do so much more. The discourse around product ops has sort of, touched on this in the past anyways. We’ve already been having this conversation. Like, I talk to so many product people, and I bet it’s still happening, where they’re spending so much of their time on operational busy work, and we sort of started making this this differentiation between, operational busy work like the product ops sort of work, and the actual real PM work, which we now sort of define as, doing the discovery and doing the stakeholder management and [00:25:00] doing the oftentimes the harder but softer skills type stuff that the connecting the dots in ways that that others might not be able to see where they are in the business.

The operational busy work being things like, figuring out how tools play together, what to do with your data, or how the process itself actually runs. And that was taking away time from the real PM work, and you’re seeing teams already move, make this move, right?

Product managers weren’t threatened by product ops people. The product ops people were taking the part of the role that they were better suited for and operationalizing it, right? Taking it away so that they could focus more on the product work. And every division has an ops role, right?

You have sales ops and sales people. You have marketing ops and marketing people. Now we have product ops and product people. The real PM work is not going away. The operational busy work, the grunt work, that stuff is getting easier and easier. It’s still gonna exist, and you’re still gonna need people to do it.

We might need fewer people to do it ’cause they’re gonna have tools to do but we’re able to push the envelope on that as well. So I actually see this as, like, our next glow up, right? We’re [00:26:00] now growing up as a discipline, and this is gonna allow us to do so much more. So what can you actually do with this so that you can make sure that you’re not gonna get replaced?

Like, to start with we’ve been talking about this since we’ve been talking about product op stuff, right? Just take a look at your week. Audit your week. How much of that time is spent on busy work, and how much of that time is spent on strategy, communication, taste-making, curation talking to customers, making core decisions?

If you’re finding that actually a lot of it is based on busy work, then start figuring out how you can take the step ahead to allow yourself to spend more time in that strategic real PM space as opposed to in the busy work space. That way, when new jobs come up and people are looking for people who really, really hone their time in the product management space you’re already clued in on how to do so, right?

You’re already making sure that you’re using the best tools to remove that busy work.

There’s gonna be stuff that you [00:27:00] can hand off. I’m sure many people here are already doing it. Stuff like summarizing lots of feedback, drafting and formatting documents. That stuff can be handed over to AI now really safely, frankly. Whereas the stuff that you can’t be handing over, this is where you need to hone your skills, right?

That judgment, that strategy, that taste. Figuring out the best ways to pull information from your market, from your customers so that you can use it in ways. And yes, you can use AI to help you get there and help you synthesize it, but you’ve gotta be the one getting out there and getting that information out.

Taking all this extra time that we magically have to get out of the building, right? We should be getting out there and talking to customers and reading the market, watching real usage, using our products ourselves. You know, finding those unmet needs and figuring out where we can actually add that value as a product team, as a product person.

Making sure that you’re using AI tools not as just a [00:28:00] task doer, right? Don’t just ask it to write you a PRD and then walk away. At Mind the Product, there’s actually a confessional thing and somebody said, “Oh, I confess that I don’t even read my PRDs before I send them through for review.” And I’m like, “Oh, no,” right?

This is not the way to be doing it, right? It’s not speed up for just the sake of it. It’s “use it to get you to that next step where you can then look at it and review it and do more with it.” But you shouldn’t just be using it as just a task doer. Use it as a co-pilot, right? Use it as something that helps you push back on your framing, right?

Have it wear different hats. Train it to talk like different stakeholders so that you can anticipate their needs. There’s lots and lots of guides on how to do this. We’ve even done some of our own as well, so I’m not gonna dive into that. But using AI smarter to help you push that envelope further rather than just, pawning off work and hoping that it does your homework better than you do.

That’s not gonna work. You wanna use it to push the envelope and really, really get you thinking and get more out of you, get more out of your [00:29:00] brain. And then very much, we’ve been talking about this for years as well, because product managers over the last few years have needed to become more and more accountable, right?

Really, really show the return on investment for what they’re doing. This is something else that’s gonna make you completely indispensable as a product manager is if you’re able to show that you are able to understand the objectives for your business, as well as create change with them, right?

So every time you’re seeing these wins, track that stuff. Even if you’re not seeing wins, track that stuff and track what you’re learning from it. Show the value of having a person organizing this and figuring out which of this which of the experiments are working, which of these experiments are not working, why you made decisions, right?

Make sure that your decisions are defensible. And yes, it might be augmented with AI, right? You’re using AI to help you sort through a bunch of stuff, but then you’re the one making those calls and you’re the one able to show the difference that you made. And again, you can be using AI to make it easier to gather this information and keep a log of it.

But you definitely [00:30:00] wanna be tracking this stuff so that you can show that you are an outcome-driven product manager who knows how to use the tools to get you and your product and your company further.

So, I’m really excited. I think the grunt work is going, and the real job is really starting to begin. I’m seeing some cus- some questions coming in here, so I want to just take a look through here and see what we’ve got and see if we can answer questions for the rest of this period. All right Matt asks, “As AI makes it easier for non-technical teams to create prototypes, specifications, and even working software, how do you think the relationship between product and engineering will change?

Will this improve collaboration, or could it create more tension if product teams start to believe that they can bypass engineering judgment?” Ooh, I like this one. All right. And actually really interesting that you put it as bypass engineering judgment because remember that the people in engineering have this ability to have judgment and taste in their area as well.

So, while I think a lot of engineering jobs are gonna get easier certainly with writing code and things like that [00:31:00] I still think there’s going to be a need for people in that place and people sharing their insights, their knowledge, and making sure that the team, whether on engineering side or product side, are sharing their judgments and putting their heads together to solve problems.

As I said, humans with AI are more powerful than just AI doing it themselves. And I think this is one of the things we’re gonna see backlash on in the next couple years. You know, mark my words, I think we’re gonna start seeing people go, “Oh, I replaced all my developers with this suite of agents,” and these sorts of problems start happening, right?

So I can imagine that you end up with difficulties getting alignment, difficulties getting the right quality of work out of things. Difficulties making sure that your… You know, if we struggle to get our developers from going down rabbit holes, what happens when you’ve got your AI agents going down rabbit holes, right?

That gets very costly, not just in time, but in tokens as well. I think that the relationship between product and engineering at its core will still stay the same, right? You [00:32:00] still need to have that understanding of each other’s domain, that input from both domains, and the handover.

Even if handovers are happening faster and more automated, you still need to have that relationship between the two spaces. So, yeah. I’m gonna watch this space and see how teams actually do handle it particularly as teams might be over-indexing right now on getting rid of engineering talent.

Ooh, okay. So there’s another one here, and a couple people gave this a thumbs up, so we’re gonna tackle this next. Somebody asked, “If AI makes product management more artisanal with greater emphasis on individual taste, judgment, and craft, how does that scale across a company? Is there a risk that we end up with brilliant individual product managers, but less consistency in how product decisions are made across teams?”

Yeah, that’s actually a real risk. And you know, this is part of the product management job, which is to get that alignment, right? So it’s very possible, and I think this is one of the things we’re gonna see, is individuals running off, and they’re able to craft all this stuff. They’re able [00:33:00] to make things.

But if it’s not in line with what the company strategy is, what the company needs these c- these teams to be doing, these products to be doing we’re gonna end up with a whole bunch of stuff. And you might end up with product managers who go, “Cool, I built a bunch of stuff. I shipped mine faster than yours.

Eh.” But doesn’t necessarily mean that they built something that was a value for the business. And this becomes part of the job, right? It already is sort of part of the job, right? You don’t necessarily need to have AI to have product managers running off in their own direction.

This is why you have product ops and product management leaders who help the teams pull in the same direction. The threat now is that we can just do these things faster, and therefore you have to be more on the ball. And so who’s gonna be on the ball keeping that stuff together? The product managers who stick it out and are able to use AI, but also use all the other usual constraints and inputs to build the best possible [00:34:00] thing

What are the biggest mistakes that people make when trying to use AI to increase their productivity? Oh. It’s actually an interesting question because I wonder, how we measure these biggest mistakes, right? I mean, we’re already seeing some really measurable ones. Somebody went up on stage this week at Mind the Product to say that they… And they actually had a graph of their token cost shooting up, right? I am sure that is not the last we’ve seen of that.

And I’m sure there’s already people right now just burning tokens doing all sorts of stuff. But also being more productive. If you’re not pointing in the right direction, it’s not more productive. It feels more productive. You got more stuff done, but it doesn’t necessarily mean that you’re actually making a bigger impact.

We kind of know this, right? We always knew that more story points out the door, more productivity doesn’t necessarily mean better work. But I think we’re gonna have to come back to that lesson and relearn it because we’ve gotten addicted to this, like, fast is good thing right now, and everyone’s doing all these really [00:35:00] fast changes, but they’re not really checking as to whether it’s making an impact.

So, yeah, definitely seeing costs of it, right? Like, literal token costs, but also seeing people running off in the wrong direction building stuff that doesn’t matter or probably doesn’t matter. They haven’t proved that it matters yet and, we haven’t really yet seen the success stories from companies who are fully AI-driven, for example.

We’re seeing them launch a bunch of stuff, but you’re not really seeing the stories of them getting a lot more out of it yet. So I think that will come, but we’ve got to, see how things settle out.

Ooh, Katie asks: “What are the top three skills you’d invest in to make the role, the product role indispensable?” Ooh, top three. Okay. I mean, these are gonna be the same as they always have been, frankly, right? The ability to let’s start with storytelling and getting people on board with things, right?

Creating that alignment, so working with different stakeholders to, And whether you’re working with different stakeholders or whether you’re [00:36:00] working with your, team of AI agents, or probably a combination of both, your job is going to be to make sure that you’re setting the context, that you’re setting the direction, that you’re keeping people on track.

If these people are working 10 times faster, then you’ve gotta be those few steps ahead of them to make sure that they aren’t running off in different directions. So just that, that ability to get people on board with a common goal and get them moving towards it. Another one is curiosity, right?

I mean, this one broke my heart. I was just talking about the confessional where somebody said that they, they didn’t read the specs, the stuff that AI was giving them before they sent it on. That just shows, a huge lack of curiosity, right? Like, I love reading stuff that comes back from AI.

I love seeing as it’s writing, I look at the thought process and see how it came to these conclusions, and that gets me thinking of the next questions I want to ask. I end up branching mine off into different directions to start asking different questions off into different directions, right?

There’s so much more opportunity to be [00:37:00] curious and to dive in and to have those questions answered. And whether, if they’re factual things, then it’s stuff that AI can answer for you and pull that information up for you. If you’re curious about how it came to that conclusion, then it gives this opportunity for you to banter with it, right? To debate with it about how you would tackle it, just like you would debate with a colleague, whether you’d ask questions about how they’d come up with something.

So curiosity I think is really, really key because that curiosity is going to allow those product managers to question their AI, to question the inputs that they have, and to pull out the most information. And I think tenacity, right? I think we are up against it, right? It’s getting tough out there as our roles keep changing.

Product managers, yes, we’re adaptable, but we do have to be ready to change or, not fall in love with a particular way of working, not fall in love with the way that it worked two years ago or two months ago. Get used to the changing ways and adopting new tools, figuring out how to use them and sticking with it even as [00:38:00] everything keeps keeps moving.

All right. I’m gonna take a second to take a a breather here, ’cause we’ve got lots more questions coming in. This is brilliant

Katie says that there’s definitely a book idea of AI: Now, Next and Later that I could put out there. All right, I’ll think about that. All right. I’m seeing lots in the chat. I’m not able to keep up with all of that, but I am keeping an eye on the Q&A. So, I wanna see your questions in there.

Tom asked the question, “Are you gonna write this up as a manifesto?” And I think that was a pointed question because there is actually a Makers’ Manifesto that has been launched just this week. So myself, and I think it was about 40 other product leaders were involved in it. I’ll send it through as a follow-up, but you’ll also see me posting about it on my LinkedIn.

But it’s basically like the Agile manifesto but for the AI world. And helps set the principles for good product management practices or good crafting practices, building [00:39:00] practices for us makers in this world of AI. So, thanks for that prompt, Tom. And I’ll share that around with people so you can see what we’re all about.

Ooh, Jonathan asks “Do AI augmented workflows help teams get towards a state of continuous value delivery favoring Kanban methods over Scrum? Will Scrum become increasingly irrelevant?” Ooh, interesting. Possibly, yeah. Yeah. I mean, I have long advocated for continuous delivery as product people. Now, I know that continuous delivery is kind of one of these tech topics, right?

It’s kind of the CTO’s problem, not the product person’s problem, but it’s such an enabler for good product management, right? Good product management being the experimentation mindset, the ability to iterate and to learn quickly. And if you’re not able to deliver as often as you should be able to, you end up with things getting stacked up, and [00:40:00] deliveries become more stressful and you’re not able to iterate or learn as quickly.

And so it is a product manager’s problem. So I’ve long talked about how continuous delivery is an enabler for continuous discovery. And as the process of delivering becomes more and more automated, it makes it kind of a no-brainer, right? Now very little effort to have a continuous delivery process.

And I say that, with my hands up, knowing that it’s not yet a fully solved problem, right? There’s still a lot going on underneath there. But we’re certainly closer to that than we ever have been. And yeah, I think it will make things like Scrum less relevant. This idea of planning things out in two-week cycles and doing your releases every two weeks.

I think we’ll start getting to the point where actually we can move that much faster because we’re able to keep our eyes on a wider set of things. We’re able to make changes faster and we’re able to learn from those [00:41:00] faster. The feedback loops become faster and faster and faster. As to what exactly it becomes and how we manage that stuff I don’t know.

I’m really curious to see how it evolves, actually.

There’s some really good questions in here. Thanks, everybody. All right. Robert asks, “How do you see the interpretation of AI and its capabilities across the levels of an organization? C-suite’s interpretations of what AI can or will does not always align with product sales support, et cetera. How do we keep expectations clear when capabilities are changing on a monthly basis?”

I mean, this is another part of the job, right? I feel for anybody in ops roles or anybody taking on op stuff like helping to decide which tools to use and security policies, privacy policies for companies. I was actually saying to a colleague the this week that I’m not really seeing as much conversation right now around things like getting the team aligned using the same underlying tools, using the same context for [00:42:00] their tools.

Right now, there’s a lot of conversation around how anybody can just build something and start moving faster, being more productive. But I think, and what I was betting, was that there’s gonna be more and more conversations as the C-suite starts looking at the tools and as the wider organization starts looking at tools around privacy and compliance and auditability, making sure that teams are using the right using common sets of context for their work not repeating the same work over and over again, not just running off in lots of different directions.

Not just token maxing. So you’ve heard some stories recently about companies going, “Yeah, we’re gonna use all the tokens,” and then getting hit with these giant bills. That’s gonna be managed better. There’s gonna be more conversations around that. So I think it’s one of these things that we’re still really early and we’re figuring it out as we go.

A lot of companies… I mean, I was talking to somebody at MTPCon this week, their company doesn’t let them use AI for anything just yet, right? And they’re not the only ones in the room, right? So some companies who are, like, way further ahead than others who, and others who are way further behind.

And I think there’s gonna become more and more [00:43:00] discourse around how organizations do make use of these tools. And as models change, as capabilities change, I think it’s gonna be an interesting job for some humans to to keep on top of and to help set that set the rules. So again, AI is not going to take all our jobs.

It’s just gonna make them more interesting . And we’re already seeing that. Oh, I’m gonna take a little sip here as I jump into the last few questions.

Elizabeth asks “I’m seeing lots of PM courses now focused on building skills to vibe code or even use Claude Code to build production-ready products. To what extent is that a good direction to go in versus focusing on the more traditional PM skills of customer discovery and empathy and strategy, et cetera?”

I mean

I think it’s always good practice for a product manager to [00:44:00] have a hand in crafting something, right? And vibe coding makes it super easy to go and create things, right? Now, I’m not saying that I think product managers should be creating things using vibe coding that they then turn into production-ready products, because there’s a big difference between getting something that’s ready as a prototype and something that is scalable and reliable and is understandable by the rest of the team, fits the wider bill.

But just like, a product manager should try their hand at… if I was talking to a product manager 10 years ago, absolutely you should try your hand at wireframing and sketching and, making mock-ups by hand and paper and, whatever tools are out there. You should try your hand at design.

You should learn the principles behind stuff. You don’t need to be the best person at each of these things, but you should have a vocabulary and a sense of humor in line with how these things work so that you’re not asking developers and designers and whoever else in your team to create impossible things.

You’ve got a hand in, a set of understanding yourself as to how this stuff [00:45:00] works. So, no, I don’t think product managers need to be learning how to do production-ready stuff, and I think people are underestimating what they mean by production-ready, right? There’s a big difference between creating something that runs on your local host and running something that, creating something that runs for the thousands of users that it potentially could be useful for.

But I do think that learning vibe coding and playing with these tools, learning the vocabulary around them is absolutely critical. I think it’s something that is gonna be an expectation. Just like people expect you to know how to, put together a slide deck today, people expect you to know your way around how to use inspect element in your app and, what that means for how you can manipulate stuff on the screen.

So I think there’s stuff like that that we can be expecting from these new cohorts of product people.

We got some more questions in. Sam asks, “What are the common AI traps for PMs to avoid?” I’ve touched on some of these. But AI has… And we know this. AI has this ability [00:46:00] to agree with you or to build on your ideas without pushing back, and it becomes really easy to have it create something that looks like good quality.

It looks like good quality because it looks good. It’s in this nice presentation format. It’s better formatted than your user stories ever were. It’s better designed than your designs ever were. But I think that’s a bit of a trap because people go, “Oh, well, that’s quality, and therefore it must be good enough to go,” when in reality you realize that actually underneath that, it’s often missed big assumptions, right?

It hasn’t been checked against the wider market needs. Oftentimes it’s completely misunderstood something, and you don’t realize until you properly read it. So it makes it easy to create stuff. It makes it time-consuming to go and review its stuff, especially if you have it creating a whole bunch of stuff.

So I actually recommend not using AI to just create bigger and bigger and more elaborate stuff, but actually trying to get it to Give you the highlights that you can then build on yourself rather than just [00:47:00] running with whatever it says you should go do. ‘Cause it’ll probably think your ideas are brilliant, and they might not be.

And I think this will be sounding about the cost of AI. Somebody was having this conversation with me at MTP Con a couple days ago, and they said, “Oh, well, you know what? It’s basically free to build now, so why wouldn’t we just go and build?” And yeah, I get that it’s a lot cheaper to right now let’s see what happens when token costs continue to rise.

It’s a lot cheaper to build something right now, but the reality is that just ’cause you build something doesn’t mean it’s free, right? A feature… I was saying this to somebody. A feature is for life, not for, just for Christmas. And that’s an exaggeration. Like, you can roll back features. But once you start giving people features, it’s hard to take them out of their hands, right?

People tend to just add it more and more and more. So we’re gonna end up with these really, really feature-rich products, and everyone knows that more features doesn’t necessarily mean a better product. You know, having that feature means that it then needs to be tested, it needs to be marketed, it needs to be trained up on [00:48:00] so people can sell it.

You need to figure out how you’re going to distribute it and get in front of people. But also, it dilutes the value. If you’ve got, 10 different things going on a screen, but only one of them is the real wow moment for your customers, the real thing that adds value, then it’s gonna make it harder for them to find that value thing because there’s so many other things for them to do.

So the cost of adding all this new stuff might be that you actually decrease your profits, you decrease your revenue because you are making your products less usable. And some of these things are harder to put a finger on. It’s easy to say, “Yeah, it was free to put this feature in,” but it’s a lot harder to say, “Here’s the impact that it had for our business, and here’s why we actually need to roll this back to, or hone this down to these few things that we are gonna do.”

And I’ve got another question here from James who says, “What’s your feeling about product manager job applications expecting that a PM has a repo?” Oh, is that happening? Oh my God. All right. “Seems like a trend that completely defeats the value that a PM provides to the [00:49:00] process of bringing someone to market.”

Oh, okay. I mean, look, I remember being a product manager in the early days way back when, and the expectation there was that you knew how to code. If you didn’t have a CS degree, you weren’t gonna get into somewhere like Google or Facebook or places like that, right? And that’s why I never worked with Google or Facebook or companies like that, among probably other reasons ’cause I didn’t learn to code, right?

I knew just enough to be dangerous and not always in a good way. I was using jQuery and Bootstrap and things like that, which is kind of like the AI of the day, right? The ability to move faster and build more, but not necessarily do more with it, right? So any job that I think is requiring a PM to have a repo is probably putting up some red flags about what they’re actually expecting their product managers to do, right?

If that’s their expectation, are they really expecting to do real product management, or are they expecting you to vibe code stuff that is gonna go into production but you’re not gonna be given the support of a development team? Now, I’m not saying [00:50:00] avoid jobs that ask for that. But I’m also not saying go make a repo just to get the job.

I think you should know what a repo is, know how to use vibe coding tools but not necessarily be the biggest expert in it. That doesn’t necessarily have to be the requirement. But have the vocabulary and ability to talk about it, but most importantly, be able to talk about good product management principles.

Be able to talk about good product management practices and what you’re going to bring to the table, and why you’re going to be able to discover the things that this company needs to know so that they can build the best product. And whether that’s you vibe coding or somebody else real coding or vibe coding or whatever I think that comes down to a taste of the company.

But it gives you a sense as to what that company really is asking for and what that culture is like in that company if that’s what their requirement is. Actually followed up with a comment saying he saw one application where they were asking us to use the agent to do the application and needed us to share our agent logs.

Interesting, right? But he did point out that was an agentic platform, so that’s quite literally their product. Obviously if the product is- [00:51:00] AI tools, then definitely know how to use AI tools before you go on. Yeah. All right. So that’s fortuitous because we’ve just run out of questions, and we’ve just about run out of time as well.

I can see that there are a ton of comments here. I’m sorry I wasn’t able to keep up with all of those. But I really appreciate everybody being here and jumping in on the conversations. Brilliant to have you all here. Just as a follow-up if anybody is looking to up your game with product management and using AI tools to help you make better decisions about what to build try out ProdPad.

So as I said, it’s a place where you gather all that context into one place. You get your team on board as well, so they’ve got all the shared context about what it is you have built, what it is that you are building, what your customers are asking for, what the big picture is, and you can use our AI copilot to connect the dots all together and help you make better, faster decisions and be more confident that you’re building the right stuff.

So give it a try. There’s a a free trial. You can get a demo from our team, or even jump into [00:52:00] the sandbox, prodpad.com/sandbox. And just to wrap up, we’re gonna be back here in twice in the next few weeks. So, next Thursday, on July 2nd, we have Julie Hammers, our Head of Product here at ProdPad.

She’s gonna be leading us in a chat all about all the things that we’re doing here new at ProdPad. For those of you who are interested in what we’re doing jump into that conversation. You’ll have a chance to ask your questions, see some of the cool stuff that’s going on underneath the hood.

And following that, the Tuesday, July 7th, we have a webinar discussion. It’s gonna be myself and Shardul Mehta the guy from Street Smart Product Manager talking about why and how roadmaps don’t get funded and how to have that conversation with your executives about how to get buy-in for the work that you’ve got coming up.

So I look forward to seeing everybody there. Thank you so much for your time, all your questions today. Really hope that this was helpful. Thanks again. Bye for now. Until next [00:53:00] time