Integrating AI tools into the product management workflow isn’t about cutting humans out of the loop. There’s nothing in the product manager playbook saying, “yeah, yeah, just build this idea and ship it.” Instead, as ProdPad co-founder and CEO Janna Bastow suggests, use AI tools to remove some of the grunt work so that we can spend more time working on the important stuff that’s helping to transform product management.

In this episode of Product Momentum, Janna rejoins Paul and ITX Product Manager Sean Murray to discuss how AI tools are driving the transformation of Product Management. (Catch our first conversation with Janna here: The Product Leader’s Dilemma: Balancing Possibility, Predictability).

Swap Out the Grunt Work To Focus on the Premium

So much of what we do is just grunt work, Janna says, repetitive tasks that require little in the way of expertise. “AI tools remove a lot of that pain,” she added. “That’s the sort of thing that product managers can easily outsource to a GPT-type agent to help us reduce our effort on.”

But the real power of AI comes not in streamlining existing tasks, but in “creating time for higher-level tasks that require human interaction, like talking to customers and stakeholders and using those conversations to figure out what our strategy should be.”

AI as Strategic Copilot

Janna sees AI as more of a sidekick than a replacement for human engagement. “I really like the term ‘copilot’ that’s been flying around,” she says, highlighting an AI strong suit in providing insights and feedback that guide product managers’ decision-making and strategy development.

“[AI] is a copilot, an assistant. a sidekick,” she adds. “And it’s there to help us get to the point that we can communicate or make decisions faster and better. It’s all about making sure the whole org is making better products, and the product team is empowered to do so.”

Lowering Barriers of Entry Into Product Management

Years ago, would-be product managers steered away from the role – voluntarily and otherwise. As Janna explains, “The assumption was that we needed a computer science degree or that we should know how to code.” AI tools have lowered that barrier – maybe even removed it – attracting a more diverse range of talent. “It’s going to open product management up to people who otherwise weren’t going to look down this path.”

Learn more from Janna Bastow by reading her blog and checking out her webinars, talks, and podcast.

Be sure to catch Product Momentum – recording live from The Podcast Zone – at NY Product Conference. April 18 at The Times Center in midtown Manhattan. Join the Product Momentum team as we chat with conference keynotes April Dunford, Gabrielle Bufrem, Zoia Kozakov, and Holly Hester-Reilly.

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Paul Gebel [00:00:19] Hello and welcome to Product Momentum, where we hope to entertain, educate and celebrate the amazing product people who are helping to shape our communities way ahead. My name is Paul Gebel and I’m the Director of Product Innovation at ITX, along with my co-host Sean Flaherty and our amazing production team and occasional guest host. We record and release a conversation with a product, thought leader, writer, speaker, or maker who has something to share with the community every two weeks. Hey folks, today we have a really special episode today, returning guest and good friend of ITX, Janna Bastow. But before we jump into the conversation, I wanted to take a minute to introduce my special guest co-host Sean Murray, who’s been a good friend and colleague for the better part of a decade here. Sean, glad to have you on the show.

Sean Murray [00:00:59] Thanks. Really happy to be here. Happy that you took the risk of putting me live on camera with a product leader in our industry. Never say that Paul is risk averse. I’ve been working with ITX for a while now, helping clients with strategy, their product plans, and making sure that their product roadmaps fit to their strategy, product objectives, and overall vision for their product.

Paul Gebel [00:01:19] No real innovation happens inside of our comfort zone, so I’m glad to have you on the show. You know, the conversation we just had with Jenna was really one I’m excited to share with the Product Momentum community here.

I think one of the takeaways that I keyed in on most is really about value, and that word can be diluted. But what I think emerged in the course of our conversation is the idea that product managers over the past decade of scrum and agile practices and agile coaching and enterprise have kind of gotten bogged down in sort of the requirements jockeys of the organization. And I think what a lot of the novelty of AI is, is starting to turn into practicality, because a lot of those things are going to be freed up for us as product managers to start thinking about vision and strategy and talking to customers and helping to solve real human needs again, and not just writing acceptance criteria and curating backlogs, which is important, but I think the real, necessary, valuable work can be pushed higher up in the conversation.

But I’m curious, what did you hear in the conversation that you’re, you’re looking forward to sharing?

Sean Murray [00:02:23] Janna wants us to use AI to focus. She really talks about why we should use AI. She really talks about what AI can do to make us better product leaders. How can we focus on strategy? How can we focus on planning? Really, how can we be that guide for our teams instead of being like you said, you know, that tactical focused, we’re going to do this next. Let’s talk about really what’s in the future. How does our product grow. That’s what we should be. That’s where we should be at. The things that we have to do on the tactical level are important, and we do need to do them, and AI is going to do them for us. It’s going to make it easier for us. We have to spend less time there.

Really, what should we be focusing our time on?

Paul Gebel [00:03:03] Well said. It was a great conversation and I’m looking forward to sharing this one, so let’s get after it.

Hello and welcome to the show today we’re really excited to be rejoined by Janna Bastow. She’s inventor of the Now-Next-Later Roadmap and co-founder and CEO of ProdPad. She’s the product management and road mapping software expert for product people.

Janna has been around in the product space for a while, co-founder of Product Tank and Mind the Product, the global community of product managers, and she often starts and stops conversations with the question, what problem are you trying to solve?

So, Janna, as we welcome you to the show again, I’m going to take a page right out of your playbook. And to get us started, I’m curious to ask you what problem are you trying to solve?

Janna Bastow [00:03:47] I love that question. Thanks, and thanks for the warm intro. Yeah, I mean, here at ProdPad, we are trying to solve the problem of making sure product managers are feeling informed about the decisions that they’re making, and the rest of the team is clued into why those decisions we’re making. So, it’s all about making sure the whole org is making better products, and the product team is empowered to do so.

Paul Gebel [00:04:08] Absolutely. You know, we were chatting a bit before the show and you’ve been thinking a lot about AI, as have we all in the intersection between, you know, what’s possible and what’s practical. And there’s a lot of schools of thought starting to evolve. A lot of the businesses are trying to extract value. A lot of product people are trying to enhance delight for customers. And you’ve been experimenting with ProdPad. And I’m curious, you were sharing a couple of really exciting ways AI has been a value add, but also just a really surprisingly human sidekick to a lot of the conversations you have.

Can you share a little bit about the things that you’ve been thinking about? What unique advantages have you discovered that maybe surprised you?

Janna Bastow [00:04:51] Yeah, absolutely. I mean, we’ve been using GPT and other AI stuff since before it was cool. Like before there was GPT-3. There were some previous versions that we used for various things within ProdPad. Some of them were just, you know, betas that never made it live, and other things were driving the way that we’ve been helping product managers for years, I mean, things like: making it possible to de-duplicate and, you know, spot duplicates that you can merge within your backlog or auto suggesting tags so that you don’t have to do all that manual work. Right. A lot of what we do at ProdPad has been around just removing some of the grunt work for product managers so they can spend more time on the important stuff, like talking to customers and, you know, figuring out what the strategy should be.

But once real AI dropped and everyone saw when GPT 3.5 and 4 came out and there were some real opportunities there because we’ve been playing it for quite some time, we already kind of had access to it. You got early access, and so I think we got access on like the Tuesday and by the following Tuesday, which is one of our release days, we had something out for customers. And the first thing that we went with was something that allowed you to take your stub of an idea. You know how we all have like a post-it note stuck on your monitor, which might be a good idea. It allowed you to take that and flesh it out into more detail so you could answer questions like, well, what problem does this solve? And what would be the value if you did solve it? And what challenges or risks might come up with this? But we didn’t stop there, right? We didn’t want it to just be something to generate ideas.

We wanted to help you judge as to whether these ideas are actually any good. And in fact, we’ve got a unique view because we can see what your product vision is. We can see what your product strategy is. So, we could run this idea against your vision in that bigger picture and give you some constructive feedback, you know, is this a good fit or is this actually a bad idea?

Sean Murray [00:06:33] I really like the idea of it. Just what ProdPad is doing is helping you to focus your initial time, right? It’s finally time. And saying, all right, which track should I actually should actually follow down? What are some of the ways that teams could initially get started with in using AI in in their product management practice? I think there’s a lot of different ways to go, but it’s a daunting pool to dip your toes in.

So how could team teams get started? What’s the what’s the first step that you think they need to take?

Janna Bastow [00:07:03] Yeah, I mean honestly there’s so much that product managers do that is just grunt work, right? If you think about how many hours, how many days we’ve all spent writing specs for something that’s already been spec’d out by some other team somewhere, or, you know how often we spend writing and crafting the perfect user stories that could be interpreted properly by the developers when actually there are tools, AI tools, that can help you write that stuff.

So ProdPad now has user stories and it’ll just remove that grunt work or things like deciphering what’s going on in your customer feedback. You know, a few months ago, maybe six months ago now, we talked to one of our customers who was saying that they spend for every hour of customer discovery interview time. They spend 6 to 7 hours just deciphering it and figuring out what’s in there. What were the good parts, what do they need to listen to? And that involved, you know, summarizing it and tagging it and linking it to the right things. And so, we removed a lot of that pain by building in tools that automatically summarize or take all of your pile of feedback and tell you what the gist is, telling you what sort of signals and insights we’re getting from it. So, these are the types of things that product managers can reduce their effort on. You know, anything that’s like this repetitive task or, you know, requires you to craft a particular language around things. You know, you’re not using it to craft your, your marketing language. It’s that you’re using it to craft the language that needs to communicate it to the person who is, you know, adjacent to you in the company, your developers or your QA testers or whoever else.

And that’s the sort of thing that you can easily outsource to, to, to a GPT-type agent. Something like we’ve gotten ProdPad because it’s precise language that needs to be universally understood. And GPT has got really good tone of voice and understanding as to how to write the right levels of that sort of detail, particularly when you’ve primed it like we have.

Paul Gebel [00:08:50] Yeah, we’ve kind of joked earlier before the show about some of the uncanny valley words that can be artifacts or hallucinations, like the word ‘keen’ tends to show up a lot in my prompts, I think. I think you had one word.

Janna Bastow [00:09:04] Moreover, whenever you see moreover, and then in conclusion, you know which GPT-written right? And you don’t want to be caught out with that with when you’re writing a LinkedIn post or when you’re writing a blog or things like that, right? You’ve got to think carefully about how you’re using these tools. But when you’re writing specs, I mean, honestly, what you’re trying to communicate is your idea down on paper that somebody else can read and bring into their head as their idea, right? That’s what the purpose of these specs are. And you know, where you can use a GPT agent is to help articulate and help expand what you’ve already written. If you’ve got bullet points, you don’t want to just take those bullet points and send them to people, right? It might be a little bit messy.

What you can actually do is use this tool to help you a) clarify it, make sure it’s nice and clear and b) brainstorm. Right? So, you know, if you are coming up with a new login page, what sort of user stories do you need to think of? If you’re coming up with a new search page, what user stories need to come, do you need to come up with? And just making sure that it’s providing you with a well-rounded view as to what should go into this thing. But ultimately, we’re not cutting humans out of the loop, right? There’s nowhere in that that you should just go and say, yeah, yeah, build this idea and now ship it. What it’s doing, it places in front of you so you can review it, and you can add things and remove things. It’ll flag up risks and challenges, and it’ll flag up ways that you might measure it, some of which might not be relevant for you. It might flag up user stories that are out of scope, and that’s fine. What it’s saying is, you know, here’s seven user stories you might consider for this particular idea. And you can click the checkbox boxes to say, yeah, let’s accept these ones, but let’s not do those ones, or let’s move these ones over to a different idea because they’re good ideas, which should definitely do that. But it’s not within scope of what we’re trying to do.

So, it’s more of a sidekick than it is a replacement. I really like that term ‘copilot’ that’s been flying around. People are talking about with their AI tools, and that’s what we’re calling ours as well. It’s a it’s a copilot, an assistant. It’s a sidekick. And it’s there to help you get to the point that you can communicate or make decisions faster and better.

Paul Gebel [00:11:05] Yeah. The way that you put it a minute ago, it’s your ideas. Emphasis on your, not the models, your ideas written down so that somebody else can understand it. And I think that that’s been a source of, I think, a bit of buzz in the product community. There’ve been a series of articles kind of speaking down to some of that grunt work, as if it’s not valuable. That translation of ideas still needs to happen. Documenting requirements still needs to happen. But I think what this is starting to reveal is, you know, instead of cultivating that conversation of fear like we’re all going to lose our jobs, I prefer to look at the opportunity that this presents, and it’s actually helping product managers demonstrate the value that we’ve been trying to exhibit to organizations all along.

Wondering if you can tag up on that for just a minute about, you know, product managers are still, I think, uniquely positioned in the organization as this decider. We are the folks sort of standing between a user’s problem and a technology solution and trying to wrangle digits and pixels to, to make things work for human beings takes a lot of deep thinking. And I think while we’re removing some of the workload from that, it’s actually emphasizing the more important side of the work. Am I being too optimistic in my outlook that.

Paul Gebel [00:12:28] Would you hare this vision, or would you change it?

Janna Bastow [00:12:30] This actually aligns with what I think and actually harks back to a conversation I remember having with some folks at MTPCon in San Francisco last year. So this is in June. It was shortly after, GPT-4 had landed, and there was a lot of buzz around what it could do. And somebody was likening this new technology that we’re getting to the dishwasher, the creation of the dishwasher in the 50s. And what it was meant to do is free up housewives to have all this extra spare time. Now, we look back, we laugh because, you know, the housewives don’t have more time and that’s that’s fine. They found other things to go do with that time. And I think that there is going to be an element of that where it’s like, well, yeah, you’re not going to be washing the dishes, right? You’ve got something to do that, but you are going to find other ways to add value, like go out there and find other sources of income. Maybe I’m stretching that metaphor too far, but what we should be doing as product people, and we should have been doing this whole time and we would have been doing if we weren’t so weighed down by all this grunt work of nurturing our backlog and writing specs is getting out there and talking to customers, getting out there and speaking to different stakeholders to really, truly understand your position in the market and your opportunities and the steps you should be taking to win.

And I think too many product managers have fallen back on this old way of working, which is, you know, doing this grunt work and, you know, filling the time with it. And this is why they’ve been saying, oh, we don’t have time to get in front of the customers. I can only do a customer, a couple of customer meetings a week between, you know, all the effort and then, you know, turning it into specs that the developers can use. You know, 20-odd years ago, almost 20 years ago, when I got into product management, your job as a product manager was largely to shepherd work through to development. So, they built the right stuff. And nowadays people know that actually the best product managers are spending their time doing customer discovery or spending much more time with the customer, and that’s just going to make it way more possible to do with this new tech, because we don’t have to worry about writing those detailed specs, right? We can articulate them much more quickly. Right? Our backlog is kind of naturally groomed using tools, right? That flag up if there’s something that needs attention or something that’s a duplicate. And our customer meetings are, you know, it’s easier to book them nowadays and it’s a lot easier to synthesize them, which is really time-consuming piece.

So having two meetings a day goes at two meetings a week, goes to 20 meetings a week. And the insights you get from that are going to bring your company forward, bring your product forward by a huge degree.

Sean Murray [00:15:01] People were talking about is what are what are the benefits of, you know, all right, I don’t have I don’t have as much focus on this grunt work. Here are the things that I should be doing right? How do we how can we measure the increase in value that we can get from those things that we should be doing now that we have GPT?

One of the things that I’ve been wondering is: How do we convince maybe somebody that’s resistant to bringing this into their organization, bringing this new practice into their organization? How do we say, here are the things, here are the metrics that we’re going to improve on from a product practice because we are using these tools.

Janna Bastow [00:15:37] Yeah, I mean, this is going to be, a contentious thing, right? I mean, people are going to look for ways and I’m talking about like in this day and age, this economy, people are going to want to look for ways to measure what’s being done and make sure that there’s no wastage in, you know, the way that we’re working. And ultimately, the role of the product manager is to discover and create value, right. Figure out where it is that we could be creating value for the customers and therefore for the business in order to reach the business outcomes. And so it should be an easy translation to the way that we’ve been talking lately over the last, you know, ten years or so, we’ve been talking about being outcome-led as opposed to output-led should be an easy translation for anybody who, you know, might put up barriers to that going, well, you know, you’re talking about, you know, us removing the work on these output things, we can focus on figuring out what’s going to help us reach the right outcomes. Right.

No longer are we being measured by how many specs and story points and things like that we can get out the door. It’s more about whether these things actually worked and that’s the right way of doing it. But we are at a pinch point with the economy right now where people are looking much more closely at how we’re reaching those outcomes. So I think most people are going to be embracing anything that allows their team to be more effective. I do think some product managers are going to be left behind by this, though, because I think a lot of product managers have been making a lot of money, too much money just being spec jockeys. They’re writing to their specs and they’re taking something from here, and they’re writing it down and they’re sending it over to the next person, and they just repeat this. There’s a lot of ways to keep busy and not actually have hard work, right? You don’t have to talk to the customers if you’re busy writing the specs or, you know, to talk to the customers. If you know you’re weighed down by it, by, you know, user story stuff, then actually I think this is going to highlight those who need to have their jobs more automated, and they need to be focusing more on the harder piece. Right? The harder piece is talking to customers and figuring out the right questions and not asking leading questions. And, you know, picking out what’s really insightful from those. That’s actually hard. That takes a human. Where’s the rest of it? Actually doesn’t require a human anymore.

Paul Gebel [00:17:48] Hey, product people. Some exciting news to share about product momentum. We’re teaming up this year with Mike Belsito and Paul MacAvinchey and all our good friends at Product Collective, beginning in the Big Apple on April 18th. We’ll be recording live at the New York Product Conference at the Time Center, with conversations already booked with a great April Dunford, Holly Hester, Riley, and many more. To stay in the loop with these events and more, head to itx.com and sign up for our newsletter. And now let’s get back to the show.

Sean Murray [00:18:14] Okay, so a lot of people need to be prepared for the question of what is it that you would say you do here, right.

Janna Bastow [00:18:21] Totally fair. And they should be ready to answer that. And hopefully a good product manager. Anybody who gets that question, they’re going to be able to answer about how they’re creating value and how they where they’re going about getting that value. And that should be ideally from, you know, spending time with their customers or with the stakeholders that that they’re solving problems for in the case that their customers are internal.

Sean Murray [00:18:40] I think we also previously talked about the flip side of, you know, sometimes there has been a bit of a, you know, a hiring problem for product managers and for product people within the industry just because there is this barrier to entry of if you don’t know these agile processes, it’s hard for you to actually execute this job.

So, what are the advantages in terms of the new people that we could attract into product as a result of the automation of some of the grunt work that we do?

Janna Bastow [00:19:09] Yeah, I mean, in the past, being a product manager meant being much closer to the dev team than you were to the other teams. Right? You had you’re very much feeling the heartbeat of the agile process and what the developers were working on. You know, I remember back when I started, it was kind of a given that you had to have a computer science degree. I remember kind of feeling like I didn’t fit in because I didn’t have a CS degree. And, you know, you should know how to code and things like that. There’s been this question for years. Should product managers know how to code? And I think we’ve come to the answer, which is no. And as a matter of fact, it’ll it’ll hold them back because they could become solutioneers. If they do know how to code, a good product manager should have a good balance of an understanding of the tech. I call it having a sense of humor in line with how the tech world works.

So you can have those conversations and you know, you understand what what complex means versus straightforward and that sort of thing. But you also need to be tuned into what the market needs and what the business needs and what the customers need. And so you need to be more well-rounded and actually using tech to replace that need to be involved in the tech can be really helpful, because it’s going to open product management up to people who, you know, otherwise weren’t going to look down this path, right. If you don’t have a customer. That’s right. If you don’t have a computer science degree or if you don’t know how to code. Totally fine. I mean, you know, in the future, developers won’t know how to code. They’ll just, you know, be using no code tools. And what they should be doing is being really good at communicating with stakeholders and pulling information out of stakeholders so they can discover they can figure out what the most impactful things are that they could do.

You know, one of the ways I, think about AI in and the future of product management is in terms of  –  AI is is meant to be good at tending towards the average. Right. It takes everything that’s been its learned before and it creates the same, more of the same. And, you know, it’s kind of uninspiring in some ways. You go that it’s got some limitations in what it can do. Right. And this is why I don’t think AI is going to replace a lot of people, but it will help them because there’s some things that product managers need to do that does need to be just average. Okay. So, the job of a product manager is to create something that’s technically feasible and usable and desirable, right? Well, technically feasible means making something that’s bug free, like just creating something that solves the problem and something that isn’t average is buggy, right? You want something that, you know, follows the norms of how everyone else built that thing and doesn’t have any surprises. You don’t want surprises in your in your code. So it’s going to help people create things that are bug free, right? It’s not going to solve new ways of building stuff. It’s going to build it the same way everyone else did. Which actually is fine when you’re talking about building most of your app or most of your product.

Most of the stuff we work on isn’t some new thing most of us are still building out. You know, a way to filter down to this list of stuff that you have, or a login page or the registration page or, you know, setting section or whatever else, right? Most of our apps are made up of a lot of the same stuff, but then there’s like a special, you know, maybe 10%, I don’t know, made up number of a work that is unique to our product, that makes it valuable. But for most of that stuff, you kind of want just, you know, average. You want something that just works, right, doesn’t stand out. It just works. And same thing with usability, right? You don’t want something that stand out different. You don’t want your login page to have surprises because people won’t know how to use it. You don’t want your search filters to be like surprise, we put them over this way. It’s like, no, they should be the same place that people sort of expect them to be. An AI will be able to create average, good, right, easily understood usable interfaces because they’re just like everybody else’s.

But where it comes to creating something desirable, this is where product people are going to stand out. Now that they’ve solved, you know, how to build it and how to make it look and that sort of thing. Your job is going to be to figure out what makes your app stand out. Why would somebody use your app? What does that 10% thing, that 1% thing that makes your app more valuable than anybody else’s? And to discover that you’re going to have to have conversations, you’re going to have to figure out ways to make something different and stand out and valuable to people that hasn’t otherwise been created.

Paul Gebel [00:23:23] Yeah, couldn’t agree more. I think I’ll probably make every, machine learning engineers eye twitch with this next statement. But you know, at the end of the day, GPT’s are just a database. They’re trained on models that are human output. They’re trained on text and images. But all of that stuff had to come from human beings first, and the model had to be assembled for the GPT to be trained on in the first in the first place. So I, I’m, I’m kind of thinking zooming out and, and contextualizing the thread of our conversation. So far, a lot of the context of product work has been far too tactical, and not enough vision and strategy and meaning behind what we’re building. And as as product managers look around, it can be both liberating. I no longer have to do those, you know, lesser value activities and focus on more valuable activities.

It can also be intimidating because I think for a lot of folks, the novelty is starting to wear off. The ability to push a button and generate a 300-word essay, because everybody now has access to this technology, it’s not as novel anymore. And people are trying to reconcile with the practical intersection of it and, and where I’m, where I’m going with all this is, is actually I’m wondering if you could share the anecdote that that you shared ahead of the show where at ProdPad, you shared your vision and strategy, you bunch of initiatives, and you’re mentioning a story where the model showed that one of these things has been kind of languishing in your own backlog. Yeah. You’re nodding. So, I’m going to let you pick up the story from there.

Janna Bastow [00:24:56] Yeah, absolutely. I mean, this came out of I mean, this isn’t even beta testing. This is like internal tests. And the way that we build AI here is that we have our team working on models in the background. Right? They figure out, okay, we feed it this and this and this and we prime it this way. This is what it’s going to come out with, but it comes out in, very basic text format, right? Like it just gives us the I think it might come out in Json or something like that. Who knows. But my team basically. Used our own data to test this stuff on. Right. We needed some live data to play with, and so we gave it our roadmap and our objectives.

And you know, our strategy as a, as a company, what we had in ProdPad and said, okay, well if you had this, can you help us figure out which of these things are aligned with those objectives, which things on our roadmap are aligned with those objectives? And the vision that we have in ProdPad and which ones aren’t aligned? And this was basically just something that had no interface. It was, you know, just a super simple thing that we built in the background and it was able to give us feedback and it said, well, you know, of the, let’s say ten things on your roadmap. You know, these ones all make sense. They’re all aligned. And it gave really good feedback on, you know, where these were.

But it also came back with a few of them and said, well, well, these ones I can’t really see why they fit in the roadmap. And I looked at them and I sort of went, oh yeah, well, if you rephrase it, I can help explain better to both the humans looking at it. I can see why it was understood. It was misunderstood. So, I want to explain it better to the humans who are reading my roadmap, but also to the bot. But then one of them it came up with. Yeah, I can’t see why this one’s on the roadmap, doesn’t seem to have good alignment. And I looked at it went, yeah, actually you know what? It’s right. We put that on the roadmap months and months ago. And it’s just sort of been, as you say, languishing there. It hadn’t been moved. And so based on just this really, really simple tool, no interface, just something that our backend devs had pulled together in literally hours, was able to tell us as to whether our whether, you know, something on our roadmap that didn’t fit, we were able to change our strategy based on it. And I mean, this has been, you know, hugely powerful.

So we’ve now, you know, we’re releasing stuff like this to our customers and saying, hey, you now too can figure out what’s on your roadmap. You too can figure out whether these ideas align with your vision or whether your objectives or any good. So, we’ve got these sorts of tools, but it was just like very, very early days that we realized, oh, this thing could be really powerful. Let’s see where this thing can go.

Sean Murray [00:27:15] That’s awesome.  I think your anecdote kind of leads me into something I’ve been thinking around that about, around your popular question of what problem you’re trying to solve and how you can use that question to identify high functioning product managers. I think that if your answer to that question of what problem you’re trying to solve is around, like the product roadmap or product plan level, you’re not thinking high enough about the problems in the strategic product objective or vision range. Right?

So, I think the application of AI and product management should really pull you up into thinking more in that strategic level, more at that product objective level, and really try to help you achieve that vision, right. Do you see the future of the answers to that question more on the strategic level as opposed to at a really tactical level?

Janna Bastow [00:28:09] I actually think it’s both, because let’s look at the real life of a product manager. You’re constantly you get whiplash between, you know, the strategic high-level stuff and the detailed low level stuff. And people are constantly tapping on the shoulder and asking you questions. And so, you know, we’ve been aiming to help product managers see the bigger picture and make better informed decisions based on what they’ve already got in there, where they’re already assuming they’re going. But also sense check where it is that they’re putting down that they should be going. Right.

So it’s helping at that strategic level, but also when it comes to the more tactical level, you know, being able to answer questions like, hey, is this on the roadmap? Is this something that we’ve had feedback about? Could you summarize this feedback for me? Right. Like these are all things that we’re using AI for as well. One of the it led us to the next thing that we started building, which is our copilot chat bot in ProdPad. And it’s actually just in beta now. So if anybody wants to try this out, get in touch with us and we can help activate it for your account. But basically what it does, it has access to your ProdPad system, right? It knows what your vision is. It knows what your customers have been asking for. It knows what ideas are coming up in your roadmap. It knows everything that the product manager should know and therefore it can answer the questions like the product manager.

You know, we realized this was going to be valuable when we had a new salesperson start last year, and this new salesperson didn’t know the way around ProdPad yet, but was asking lots of questions and was constantly asking the product team for answers to stuff. And we were able to redirect him to this bot sometimes and say, hey, you know what? The bot will be able to tell you. And he could he could use that as a way to understand what the product manager would have answered anyways, but didn’t take any of the product managers time. So I think this is going to be like a second brain for the product manager, right? You’ve got to have your brain in like the high level and the super low level, and that’s hard, that’s taxing. And people just miss stuff. Right? Even the best product managers can’t hold on to all that. We don’t expect them to.

But if you had a sidekick, a copilot who knew all this stuff, you could ask it yourself where you could actually direct your team to go ask it, and the whole team becomes more informed.

Paul Gebel [00:30:14] I think that that context really brings everything home. I think there’s really a lot of excitement, there’s some career concern, and I think that it’s far outweighed by that idea of leveling up the conversation to really add value to, to look for those anomalies, look for those delights. You mentioned something about the reversion to the mean and sort of all models kind of trending towards what’s been I think that opens up the opportunities for us to look for the anomalies, to look for the outliers, because that’s where the true innovation is always going to lie. So as the model points us to maybe the, the obvious or the pattern or the expected outcomes, that’s just more efficient. We can look for those there’s opportunities for curiosity and imagination to really kind of bring some joy back to the practice of product management again.

We just have time for a couple more questions, and I’m going to ask a two-parter to close this out here. I see you have a beautifully colored sorted bookshelf behind you. So first part of the question is what’s what are you reading or watching; keynotes or blogs that have been inspiring to you? And then the second part is where can folks go to find your writing for what you’d like to share with the world?

Janna Bastow [00:31:27] Yeah, absolutely. Thanks for the question. So I mean, this is my backlog of books, but my active reading pile, I’ve got Design of Everyday Things going on right now. And I’ve also got a Lean Product Playbook in there as well. So I’ve been having those two out as between and reading those.

Janna Bastow [00:31:45] You know, I tried to get my hands on, you know, product books and psychology books and business books and a wide range of different things, just to make sure that I’m up to date with what’s going on and, you know, sort of broadens your horizon as to how you might do stuff. So you sort of see a mix up there.

In terms of my own writing, I write at ProdPad.com. I’ve got regular blogs that go out there, and we’ve got a newsletter that highlights that top of those, the top posts there. So we’ve got ProdPad to able to sign up for the Outcome newsletter. And then I tend to do sessions like this and talks and other bits and pieces, so I’m sure you can find me around. If you’re looking to connect, find me. I’m Janna Bastow. I’m the only one on LinkedIn, so I’m easy to find. Just remind me of where you found me. And that helps jog the memory as to why we might be chatting.

Paul Gebel [00:32:32] Well great recommendations. Design of Everyday Things is a classic. I can personally vouch for the ProdPad blog is one of my go to sources. The Now-Next-Later post is….

Sean Murray [00:32:41] A must read for…

Paul Gebel [00:32:42] Some required reading. Absolutely.

Janna Bastow [00:32:44] Yeah, we and we’ve actually been adding to that as well. So I mean. The Now-Next-Later post you’re talking about is one that we’ve had it for a while, but we’ve actually started fleshing that out into more details. We’ve got a guide on how to ditch your timeline roadmap in favor of a Now-Next-Later, a course that you can take that actually takes you through how you’re actually going to make that switch. And also includes we’ve got a presentation and a guide on how to get the rest of your team on board, because the tough part about changing from timeline to Now-Next-Later isn’t convincing yourself.

It’s convincing your stakeholders. And so we can help with that.

Sean Murray [00:33:16] [unintelligible] Maps in a Cone of .”Uncertainty kind of format and the Now-Next-Later post really made me realize this is what I’m doing in a, you know, much more concise and transparent form.

Janna Bastow [00:33:28] Yeah, absolutely. And the Cone of Uncertainty was actually inspiration, one of the pieces that we fed into it as we were building that, that Now-Next-Later we were talking about initially as like a chart that maps out, you know, things to do and uncertainty on them. Which fell upon the Now-Next-Later as one of our iterations and it stuck.

Paul Gebel [00:33:45] But Janna, we’re big fans and really, really grateful for the time that you’ve taken to to spend time chatting with us and sharing your thoughts and insights with the world. We’ll look forward to seeing you again soon, but cheers for now.

Janna Bastow [00:33:57] Yeah, thank you so much for having me. This has been great.

Sean Murray [00:33:59] Cheers.

Paul Gebel [00:34:02] Well, that’s it for today. In line with our goals of transparency and listening, we really want to hear from you. Sean and I are committed to reading every piece of feedback that we get. So please leave a comment or a rating wherever you’re listening to this podcast. Not only does it help us continue to improve, but it also helps the show climb up the rankings so that we can help other listeners move, touch, and inspire the world just like you’re doing. Thanks, everyone. We’ll see you next episode.