20Product: Is the Design Phase Dead in a World of AI | Has Claude Code Crushed Anthropic Already | What Roles of a PM Are Less and More Important with AI | How the Best Product Leaders Tell Stories with Noam Lovinsky, CPO @ Superhuman

this is 20 product with me Harry stepings now 20 product is the monthy show where we sit down with the best product leaders to reveal their tips tactics and strategies to building great products and product teams in a world of AI and throw Stay to be joined by Norm Lovinsky CPO superhuman formerly Grammily prior to superhuman norm was a senior director of product management of Facebook and in his earlier years he was a CPO thumbtack and spent five years as a director of product management at Google where check this out. He was responsible for all of YouTube's applications, but before we dive into the show today, you know what's wild? It's 2026 and so many product teams are still flying blind buried in spreadsheets chasing feedback across 10 different tools trying to figure out what actually will move the needle. I've spoken to with hundreds of product leaders and the best teams all do one thing differently. 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Used by product teams at companies like Toast, Vimeo, Klavio, and many more, ReFord helps team ship more features that actually get used. Try ReFordge at ReFordge.com, Ford/Build, and use the code 20VC. That's 20VC for one month free of pro. You have now arrived at your destination. No, I'm so excited for this, dude. I've had so many good things. I was literally just making you incredibly uncomfortable beforehand. Normally with venture investors, you say that you got great references and they're like, "I'll stop it, tell me more." But you're like legit, like no, it's making me uncomfortable, which shows your humility. But thank you so much for joining me, Stated. Oh, it's my pleasure. Thank you for having me. Not at all, but I want to start with a little bit of a story, because I spoke to Glenn at Radfin before. And he said you came into Radfin when they had a couple of different product leaders. And you answered a question that he always remembers. The question you answered is, "What is a product leader?" And he said, "The description that you gave was very simple, but it was phenomenal." And so when I ask you, "What is a product leader and a great product leader, what is that description?" I mean, I think fundamentally a great product leader is a great storyteller, someone that is able to understand what the customers actually need, what problem that actually needs to be solved, and can form that into a story that is just well understood and well aligned, not only with the market and the customer, but that gets everyone internally to row in the same direction. There's all these interesting debates right now about roles collapsing and product and marketing and so on, and I just really don't see these things as separate. I see product and marketing, and it's the same thing. And so maybe that's where this comes from. I think that fundamentally a good product leader is just an excellent storyteller, and the best companies and the best brands are excellent storytellers. This is where we don't send schedules in advance because I just kind of lose interest in them in the minute you say anything, but our teams are like, "We spend hours doing this research, Harry, and then you just go, it broke." But you said storyteller, I get that, but the challenge when you're a horizontal product is different customers resonate with different stories. How do you think about being a great storyteller when you have such a broad customer base with a horizontal product? That's an excellent question, not to return some of the flattery to you, really shows a depth of understanding that you have that I don't think is always common amongst this crowd, so I appreciate that. I think that you go to different things, right? You go to what is the feeling that you're trying to create? What is the, after your features are delivered, after you solve each of the micro problems, what is the overall feeling that you're leaving the customer with? How do they feel supported? How do they feel more in the flow? Whatever you're going, whatever you're going after. I think a good example of that is like Instagram. It was Instagram about the features of the specific problems or was it more about catering to the feeling of the need for vanity. And that's essentially the product insight is that vanity is much bigger market than we realized it was as a latent demand that tapped into. That's the feeling that you're trying to address. What is a bad story that product leaders often tell, do you think? What do you see? I mean, maybe this is close to my heart right now, but I'm pretty tired of the like, this is going to make you more productive story, or this is going to make you like faster story. I think we like lean to things like time and productivity when we don't know what the value is, what the true value is. And so we're like, well, just let that's it. That's a catch all it will save you time. People want to save time. Let's see if like, you know, time, time spent will be the thing that resonates, you know, rather than kind of going a little bit deeper and understanding like what problem are you actually tapping into? Beyond the feeling of, you know, wanting to be quick, wanting to be in the flow, and that's an anxiety problem. A lot of people suggest that we're going to lose the design phase in a world where vibe coding and prototyping is so much quicker and real. Do you agree with that? No, you know, it's interesting. So many of these things that we're like talking about is if they're new things, I don't think they're very new. I think what's changing is that the toolset is accelerating, you know, things that have been happening for a long while. Like, I'm sure in all of your investments, like the best teams are one where like talent is collapsed in a small number of people, people where many different hats. The idea that like you are a designer, and therefore you stay in these lanes and you do these tasks and you don't do engineering work or you don't do product work, just like doesn't make sense. Like it doesn't work that way. And I get that as we scale, there's the idea that like everyone needs to specialize and kind of get deeper in their lane. I just, I just don't think that that's ever been true. And now the tools are making it even less true because to specialize and do well in these in these areas to be a unicorn that can do many things. You're not required to learn the syntax or the tooling or the tactics of doing any one of those jobs in the way that you have before. So is the design phase going away? No, like you still have to do that sort of thinking and there are many different tools for doing that sort of thinking. But as a designer today, like I had the the CPU of dualing on the show, he was fantastic. And they said about actually at chess and the integration or introduction of that from two designers and they vibed coded it in a couple of days. And then brought to life a working kind of prototype that everyone could play with. Is there any excuse for a designer to bring a design anymore when you could vibe code your idea into reality as efficiently in the same amount of time? So it, I mean, that's, that's as efficiently in the same amount of time. I don't know that where you are and kind of the design thinking stage necessarily leads to building a prototype is as efficient. I think if what you're asking is if you want people to empathize and understand your idea and feel your idea in the in the highest signal way, should you give them the highest fidelity approximation of that idea that you can as quickly as possible. That I would say yes, that is necessary as a designer, you know, you should be able to produce that prototype, produce that working product if you have the the time and the means when you're trying to get other people to empathize with your idea. But that doesn't mean that when you're starting your thinking process that maybe a whiteboard is actually like the best place to start or a blank sheet of paper or a Figma canvas that works in the dumb old way that they used to work. I just, I just think that the design thinking can still benefit from those different mediums, those different ways of doing the thinking because of the constraints that they apply because of the space that they create. I think that's different than saying, hey, if you're at the point where you want to like share your idea and get people to empathize with your idea as deeply as they possibly can. What's the best way to do it? Yeah, like have them use the thing and feel it in the highest fidelity approximation that you think it should be and so that might be a working working product or working prototype. But I don't think that means that all design thinking should start in a wide coding platform. What tools do you see use most often within the product teams today? Is it Casza? Is it Claude? Is it Cognition? What are you seeing internally? That's interesting or surprising? In terms of like the I coding, I mean, definitely Claude code is like the far and away and I think like just a lot of people make the transition from I want to start with something that is more as more familiar UX like cursor and then move to the terminal and there's there's a lot of freedom in moving to the terminal and almost like, you know, having layers of the abstraction even less visible. Now worrying about the files it's creating now worrying about inspecting the files like kind of gaining that confidence. I think that's that's what I'm seeing most and then, you know, the the next is starting with the kind of the more familiar applications for prototyping like lovable or or figma make, but the transition that I typically see is that you start with kind of like that lovable it's more familiar it's feels less scary you know it's like doesn't feel as much like coding. And you the move to something like like a cursor and eventually in the terminal what do we do in product development today that we won't do in three years time right specs for humans. I hope I hope most people aren't writing specs for humans any longer I think writing specs for agents is really helpful and smart and I think that also takes a different form and the way that we write them I think then also becomes different but yeah. How does the world change when you're writing specs for agents not humans and what needs to be altered. Some things are still helpful to be similar like you know who am I building for what problem am I trying to solve kind of like what like those fundamental things but when you're writing for a thing that's actually going to do the job. I think you just you you end up like creating different different types of details and kind of also even just structuring what you're writing differently you it's good to use examples build up like a context library of things that have worked in the past that you want to emulate things that haven't worked in the past that you want to avoid. All of these things that when you're writing to a human you just assume that they have that task of knowledge that you know since you've been working on these things together they like they they understand that that you don't feel like you need to embed as much of like the context engineering effectively into the spec that when you're going to have something that is actually bootstrapping and coding you know kind of based on that on spec and that and that plan file and a very direct and fundamental way I think it changes what what you put in there. I also think it should change how you write it you should use the thing that's going to code it to help you write it because it's going to end up creating a version of that output that is more compatible with what it understands to do the work. I have so many questions i'm so enjoying this if we're writing specs for agents okay are we going to see like a normalization of products like a kind of plateauing of creativity because the wonderful thing about writing specs for a human is that human brings in. The experience they had from growing up in a kibbutz in Israel where they think about whatever in a really different and cool way that influences how they think about collaboration features and they bring that really cool anomalous experience to the product process and you lose that hallucinatory element when writing it's back for an agent that executes it do we see that. I would say we will see a little bit of both i actually think that this will lead to creativity and and certainly like taste standing out more than ever because i think you're going to have this like flattening where you are going to have a lot of things that just like oh you know here we go it's this the same dialogue it's the same flow like this this is what works these things have learned that this is what works and this is what they're putting out. But that actually I think gives more room for the standouts to shine for the things that kind of have that taste and creativity to shine and fundamentally that's still like the human the human job is to figure that out so I get that maybe the analogy that to the describe that flattening just to go back to Instagram it's or like what Instagram did to did to photos right we went through this period of like every photo looks amazing it's filtered it's it's touched. Up like look at my amazing shiny life like it was sort of like this creative flattening of what like makes a good photo and then you know slowly organically over time what emerged is that the things that that people you know thought were more interesting or or more compelling was the things that like looked a little bit messy or like a little bit or organic or you kind of like the trend of what was like in fashion changed after that kind of flattening period happened. I think we'll see something similar with you know applications can I see the joys of doing what I do is I I get to ask really smart people for their wisdom to help me in my other job which is also far more lucrative I have to admit the media which is obviously using other people's money but a great lesson kids OPM other people's money you see as this brilliant wisdom that we give on the show vibe coding I'm just stuck with it as a market do you think it will be an enduring market to offer non technical functions. The ability to spin up development sites you name it faster will your loveables wrap its base 44s being every sales marketing team or is it a moment in time hype cycle I think the idea that everyone can build is not a moment in time hype cycle like we've we've seen it time and time again like you can democratize you know the act of creation. Many more people want and can create than we believe more than we currently observe and then that kind of expand so I don't think that that is going anywhere where the like value capture will be in in that stack I think is a different question you know is it in the kind of the deployment hosting in distribution of the thing is it in and will you be paying for the tool. I think that that is a different question but I think fundamentally will happen is that these vibe coding tools will continue to march up the stack and they're not building an ID they're building a service a thinking service that does things for you. My friend which ones easier to do is it easier for Claude and cursor to go down the stack and eat the consumer and what is it easier for the consumer and loveables base 44s rat place to go up the intellectual stack and eat the developer and I think that the hardest thing right now is figuring out the user experience that is going to scale to the largest number average average. I think that we're already very much at the point where we have this kind of capability overhang that people talk about right where like what these models can do and what people actually can do with them there's there's a big gap there. So I think that the question of is it easier for Claude code to figure out the right user experience or is it easier for someone that is working more actively in the kind of that UX application layer like a like a like a man or or or like a like a lovable to figure out the user experience unlock. I guess I would I would probably bet on people working at that UX application layer already but I think that the the foundational labs are doing that as well and are trying to learn at that at that level as well. How much would you say of net new code created today within superhuman entities all the different products you have is written by AI versus by engineers. I think we're we're basically at the point where we're approaching about half that's that's there I think that it can go much further than that. What do you what do you think it is in 24 months in 24 months I I hope it's like 90% when it's 90% what do we do do you have less engineers do you just create way more products how does that change when 40% more is taken. I think it's it's absolutely the latter that we build though we build more things I just this idea I don't I have never worked at a single company that doesn't have an infinite roadmap that doesn't have like a we're done here like we only need this many people or or done or done here. I absolutely think we're going to go through a phase and we're going through a phase where the number of people we need and what a good ratio on a product team looks like and all of that is is going through like a fundamental shift and that's going to that. That causes obviously some disruption that doesn't always feel great but then I think once that kind of normalizes and we have a better understanding of that our desire to do more is not going to go anywhere and then we're going to like continue to scale but basically you know divide up the work in a different way. Can I ask you said about the ratio on product teams changing what do you think it's changing from and to and how would you discuss that. I mean I think that you know up until like a couple of years ago you probably like what is it was a kind of a decent product team look like if you were starting like a zero to one team you know maybe you say it's like depending on on the problem you know five ten engineers at the limit you know it's kind of like one PM one designer right I think now you're you're much more looking at you know it's like maybe one PM one designer two engineers has kind of like you know what what you need and then also who is doing what is is also very very different right like everyone is in the code everyone is building the thing and you just have a small number of people that have their hands on a much wider part of the the product pipeline and I think that leads to to better products totally get you. So we have smaller teams everyone still being the code when we get a little bit further along how is testing and deployment changed in a world of AI or is this fundamentally remain the same. Well I mean I think that I think that for one like that they I can can do a lot of the the testing certainly the you know the first run catching all the the obvious things I mean even for on call like incidents like when they kind of bad things happen I think that I can do a lot of the triage a lot of the the first run investigations so that by the time it gets to an on call engineer it's like here's what I think is going on here's I think the three options are hard to fix this like which one of these paths do I'm going to take go. I think over time as you build up that that context and that and that memory then you know it's going to ask you like less and less so I think the whole stack is is is going to be automated in the same way. How much faster does AI make your teams are you able to ship twice as much three times much for I know it's hard to quantify but like just to help someone who doesn't live in product. I think that that maybe there for our teams like the fundamental thing that I can get shrunk is the exploration phase and the rate of integration through the exploration phase how quickly you can kind of get to this is the thing we actually need to build. And we've you know we've learned that we've we've tested that we've iterated through that exploration phase that's shrunk quite significantly. I don't know how to like put like a it's 2x it's 3x on that but I do think that in the limit that speeds you up quite dramatically because usually what does it really mean the exploration phase is shrunk like. I think that the phase the phase of going through we've observed this this problem how do we build a solution for this problem. Okay let's try to like you know iterate through what a solution might be let's go and like kind of test that with some of our customers oh that's not the right one let's iterate and try this other one. How much of that you can shrink how many of those you can do in parallel who can do that kind of full full pipeline of that exploration how many different people you need to do that. And so basically it just it increases the rate of learning like quite dramatically which then kind of you know shrinks the the whole kind of prog development life cycle. And I think if the business is fundamentally learning much more quickly than you know the whole thing has like a massive acceleration. There's also obviously the I think when we think about this we like quickly go to like I used to type all these things with my hands and now like I can you know this thing just types them for me yes there's that's that sort of speed up as well obviously and that stays you like quite a bit of time. But then again I feel like you you just end up doing more also of other things you're you're reviewing code more right and then we need to like make that process more scalable you're then just kind of doing more things and in parallel. And so anyways I think that the shrinking of the exploration and the rate of learning is at least right now for us one of the biggest accelerators when we think about how it makes more efficiency and more productivity gains within engineers. If an engineer say has paid 250 grand a year I'm just making up numbers and it makes them 30% more efficient or better or whatever does so it makes sense to pay 75 grand per engineer per year. You know it's interesting I just don't think that that's how things work fundamentally I think what happens is engineers just get to spend more time on other parts of the prog development process. And so they they get to flex their their producty skills more or they get to flex their data analysis skills more. And so the most valuable people will continue to be the people that can wear many hats that you know have a more like kind of fulsome skill set that they can express which was before was just harder to express because of one where time had to go but to also the time that you're tooling required of you to kind of be able to express those skills. No I'm a VC. Okay we we very simple we're cooperating we think in dollars and great British pounds in the UK if we are going to make money from AI. We need to fundamentally see the transition from software spend to human labor spend in a way like I mentioned 30% of time great will pay 30% of salary because otherwise we're still paying the per seat 25 bucks a month. And then the time doesn't expand can you help me understand are we going to see the expansion of time with the movement of that software spend to human labor spend or are we all getting way too high on our own supply. And we're going to stay in a software spend world. I mean I I guess like Tam expansion that I see is that the number of problems the number of things that you're able to solve with software and do for do for people is just is just going to expand. And so yes will you be able to have smaller teams like kind of more more productive doing more will that change kind of like the the hot packs accounting fundamentals that are like yes but I I think them like what happens is that you expand through just providing more service. Solving more problems and does that lead to like basically fewer bigger firms. I know perhaps like maybe there are too many providers and what you actually need is fewer providers that just do more and cover much more much more of the stack. And do you have to be a platform to say when we look at a super human with all the entities that you have your code is your super human to ground. And when we look at like a notion I know notion of see a capacitor. So forgive me for bringing in a capacitor. But it's like you know that they obviously have calendar integrated now. I think they're starting to cool recordings. They obviously have their cool kind of knowledge management system. I think when you look at like an author or a fireflies. They're aware of the need to move from product to platform is product no longer enough in a world where you need to be platform. It depends how you define platform like I I think you know there's there's one definition of platform which is basically other people can build businesses on top of your your product. I think that maybe that's not real that definition is not required for everyone. I think that your customers are going to build on top of your product is a requirement for everyone that is that is that is serious because customers needs are always nuanced. I mean, I think we're very quickly moving to a world where you're just going to have a lot more bespoke software. And so you have to you have to have a platform approach that and how your customers can can build on and extend your platform your products in order to kind of meet their need. What changes then for product leaders in the world when you exist in a world where customers need to build nuanced personalized customized features elements to your product. I think you just think of things pretty differently in the impact of things pretty differently when you know you have other people developing on your platform right like how you roll out change how you think about backwards compatibility. How you even kind of run experiments and kind of measure measure your your experiments in terms of you know who's doing what with your with your product and kind of what you're making better what you're what you're breaking. Like one of my favorite examples of that and this is more from like YouTube is a platform in the definition that other people can build their business on top of YouTube. And when we would kind of experiment and you know just observe things in terms of watch time it's like hey watch time is this is a big win and then we roll it out and we'd have like the community like you know enraged. And why is that is just like what it's not it's not equally distributed and so you have to you have to look at you know by kind of cohorts of publishers and creators like whose business is not my hurting whose business am I helping and how do I kind of try to you know normalize that across the base. I think you just you you have to observe things differently. Can I see a bit of a weird one but everyone is so excited high on their own supply but how we're able to build more faster is around the thing that you are nervous or worried about in the way that AI is changing how we build product. Maybe maybe I'm just giving us too much credit I would like to think that in areas of like you know security sensitive data. That we're all still adding the observability and the controls such that there is kind of like the right human in the loop for those sorts of decisions. I suppose that we'll go through like kind of some bad phases where people are using these things irresponsibly and you know we have data leakage we have you know prompt injection short sort of hacking and so on. But I think that's just like a part of the learning curve that we're going to go through I don't think that's like something fundamental that's going to make software worse in the in the limit code quality is also not one that I think I worry about too much in the limit. I'm more worried about whether we actually use these tools to make our lives and our work lives actually easier and better or whether we're on a trajectory that I feel like we've been on which is I'm not sure that a lot of the you know tools that we use for work in a lot of the ways that that we work have actually made us better. Certainly can work a lot more and and all the time which is you know I think has benefits and and also to for some folks some some downsides but like I'm as an example like I used to really love a slack when I was in my you know startup phase and near 10 people in the room and it was like one of the best products that I had ever seen. I have to say in my role now I'm not sure that slack actually makes me better at what I do and makes my day better and more effective and I do worry that some of these things that we're building could kind of go towards that that trend rather than actually helping us do things better and taking things off of our plate and kind of from moving some of the work. I think one thing that we're going to see in 2026 that no one's talking about is 24/7 inference that everyone is going to have inference running all the time not just on input into chat GPT but consistently for the majority of people especially in knowledge worker jobs. You will have that you agree with that and does that factor in how you think bubble in product. I think that's a that's a very good observation and whether it happens widely in knowledge work by 2026 I think is you know I'll take a bet with you on that certainly for coding I think in a lot of places we're already there right. I mean you have like the Ralph Wiggum stuff that that popped up over over the holiday and now people are running in friends 24/7 for their for their coding tasks for the sort of knowledge work that the majority of us do on on a day to day will we be there by the end of 2026 I might disagree with you on timing but I think that the inside is correct why would you I'm so love to be proved wrong and I'm wrong most the time is eventually faster why would you disagree on timing because I think we're still at the stage where fundamentally like we don't have the right UX we many people are still at the stage of I'm not sure what to do with this thing other than like kind of search in chat I still think that a lot of how people use these things. It doesn't feel like they actually make them better or that the output is better than kind of what they've done on their own I think in in most cases that's not actually a problem with the model or problem with the technology I think it's it's often a problem with the user experience and what I mean by that is how do you add this sufficient context how do you you know kind of prompt this thing correctly like what should you use it for how should you change your workflow to adapt to it I think we're still at that stage for you know a lot of the work that we do. Do you think I will do more to harm or to help wealth inequality. Oh man I think we're going to definitely go through a painful period wealth inequality in the US is something that I really am concerned concerned about because it's higher than it's ever been higher than the gilded age and that has a lot of very potentially dangerous ramifications. Don't think the answer though is to curtail things like AI I do still fall on the side of I think I'll ultimately creates a lot more abundance that it's not a zero some game and that it is an example of a technology that's going to lift lift all boats just I don't think that the path from here there is going to be you know as smooth as we might like. The other prediction of mine for 2020 is I think we can see that the demonization of tack and tack leaders like never before as you see the first real instantiation of job losses and job displacement in large parts of the economy like in low level law in customer support but keeping. Yeah I think that that one I won't I won't take a bet against you for this year I think I think that is that is will more likely to see that I want to do a quick far around so I say short statement you give me your immediate thoughts. What have you changed your mind on most in the last 12 months how close we are to what my kind of my version of AGI would be and I think specifically with opus 45 like that has changed quite significantly for me I think what cloud code can do is just incredible for coding or knowledge work I think it's made a huge leap with opus 45 I think we've crossed some. Like invisible capability line and now like kind of that what it can do in the outputs that it can produce you know for code and otherwise we just haven't found a way to package the right UX around it for most people in my view. You can have anthropic at 360 or open AI at 500 which one would you rather buy I'm a buyer of ontropic at this point. What's your biggest prediction for 2026 like I said about inference or the demonization of tat leaders what would yours be. I think we're going to crack the like continuous learning self improving these things you know can just be set on a task and given the context and build the memory and and are just going to get better on their own for you know the majority of tasks that you put in front of them. That's likely already been cracked and we're just dealing with like the implications of that and how do you roll that out safely and so on. What was your biggest takeaway from matter we haven't discussed it but that is an amazing place what was your biggest takeaway. I think I think this is like specific to like the part of meta that I was in and to be fair I didn't get to experience kind of like mainline meta I was an incubator team that was explicitly you know shielded. From the rest of the organization for for good reason and that's that's because. I think doing zero to one product development it I don't think this is an uncommon learning by just seeing it so viscerally and understanding all the reasons as to why it is I think doing zero to one product development at scale is just really really hard. And I think that that place has many many strengths but like lots of companies at that scale that's just a fundamentally hard thing to do. When you look back at your leaders over the years as we said from YouTube to Google to matter to thumbtack you can't choose to share by the way which was the best leader you worked under a more. So like I got to piss all the other ones off. Because you're not saying one was bad you're just choosing one it's like when you have six kids you can say the favorite because there's so many that five you know it's not like there's the least favorite. Yeah this this goes this goes back to you know what I said about like what I think is like a good product leader and I do think that the best leader in the company that that I have ever experienced is is Glenn Kelman because of not only his ability to empathize and understand the market but how well he can communicate. And describe what we should do and why it matters his ability to relate and get people to want to just run through walls for even seemingly meaningless things. I just think he's he's in a class in a class of his own if I look back to plumb tree which was basically like corporate portals like you know my Yahoo for the enterprise like we felt we were on like a Messianic mission why like we were building corporate portals and Glenn was able to relate it in that in that way in a very meaningful way and I think that he would be on the top of my list. First joined up with your share first day of Grammily what do you know now that you wish you could tell yourself then. I think I didn't push for product expansion nearly as aggressively or fast enough I had the hunch and we sort of had the conversations of you know we must own a surface like fundamentally if we want to be like a creative product you have to you know have a destination that is meaningful to people in some way it was sort of like a side chat and like you know every time I was like no no that's a that's a big that's a big risk and anyway lots of good lots of good reasons and I think we got there and now we are undergoing like quite a tremendous like product expansion but I wish I had pushed harder and that we've got there a year sooner. Final one what are you most excited for when you look forward to the next 12 to 24 months. Personally I am most excited to build with AI and how I think it's going to change even my job how will it most significantly change your job most significantly. I think that the people and I think my roles typically have a hard time finding time to build to make and that's like fundamentally why I got into this career in general as I like to make things and you know as you progress you just you do that less and less which I think is a real shame and I think that it's going to give me the opportunity because of the amount of time and energy it takes now the amount of space I can I need to carve out in my day in my in my weekend I think I'm going to get to build a lot more than I have in a long time where before it would have been like well I got that week a quarter where we ran that sprint and I got to you know actually be a designer again or be a PM PM again. I'm very hopeful maybe maybe I'm projecting I really want more of that time in my week to week and then I hope through that to also help change how our teams work and kind of like our rhythms and our are expected like you know roles and accountability rhythms such that more of our PMs and more of our designers and teams can can work that way because I don't think the the biggest thing that's in their way now is is the tooling or the desire or the knowledge I think it's actually more the change management around just how we work and like what should the week look like and you know who's responsible for what's and you know what do we use meetings for and what you know like all of those things I think really need to change in order to create the space and the permission for people to just do a very different thing in the majority of their day. No you figured this wasn't the traditional interview from how freewheeling I am I've so enjoyed this discussion you've been fantastic so thank you so much for doing it man. My pleasure. Thank you so much for having me. I really appreciate it. But before we leave you today you know what's wild it's 2026 and so many product teams are still flying blind buried in spreadsheets chasing feedback across 10 different tools trying to figure out what actually will move the needle I've spoken to with hundreds of product leaders and the best teams all do one thing differently they build a system to capture ideas validate them with real data and focus their roadmap on the right things. That's why product teams at Canva Deliveroo toast the castle on used your product discovery it pulls ideas and feedback into one place with built in tools to prioritize what will actually have the biggest impact. 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