Microsoft CPO: If you aren’t prototyping with AI, you’re doing it wrong | Aparna Chennapragada

26:22Most of us don't even program in C. Then higher and higher layers of abstraction. To me, they will be ways that you will tell the computer what to do. It will just be at a much higher level of abstraction, which is great. It democratizes. There'll be an order of magnitude more software operators. Like in Swiss, maybe we'll have souls. But that doesn't mean you don't understand computer science. It's a way of thinking and it's a mental model. I strongly disagree with the whole coding is dead. That's awesome. I love that. So is a software operator? What is that with that dance floor? Yeah. I just made it out quick.

27:02Yes. Okay. Cool. This idea of prototyping is being core to building these days. Is there anything you do within Microsoft to operationalize that and make that a thing everyone has to do? Is it just culturally do it or is it like you must show me a prototype before you show me? I think the future is here unevenly distributed. Even in Microsoft, I would say. But there is certainly a strong cultural momentum and shift and desire to say, hey, let's actually look at live demo's, live prototypes. And to even communicate the ideas. And to me, it's not always possible because obviously there are things that are deeply, if you're trying to change something in the bubbles at Excel, you probably don't.

27:49There's even enough depth in the product that, you know, what you need to do and you don't need to prototype that. But if you're especially thinking about new things and new products, new features, absolutely. Okay. Let's talk about product management. There's this fear that emerged as soon as all these AI coding tools came out of just like, PMs are dead. We don't need PMs. We could just build things ourselves with what are these people hanging around for? And what I found is it's actually the opposite that now that coding is easy. Now the question is more and more, what should we be building?

28:23Why should we be building it? Is this right? Is this the right solution than getting adoption for it? Which is what PMs are really good at. And so I feel like it's the opposite. Like, PMs are the most important role and they're, you know, it'll change, do. But let me get your take. But just what do you think the future of product management looks like?

28:44You look, I mean, if you're a TPS report, mostly process person and like a lot of companies do get confused about product management and process and project management, I think then you do have a question of like, hey, what is the value add here? Right? Especially if like AI can read and write like 50 ,000 meeting notes and, you know, attract things and send emails and so on. But I think what what I do think on the flip side is the taste making and kind of the editing function becomes really, really important, right? In a world where the supply of ideas, supply of prototypes becomes even more like an order of magnitude higher, you'd have to think about like, what is the editing function here?

29:34So that does mean that the bar is higher for you for product folks. But I there's an interesting side effect I am observing in startups that I'm advising companies and even within the companies that there's, there used to be more gatekeeping, I would say in terms of like, oh, this is, you know, we should ask the product leader what they think. And again, like there is a role for that editing function, but you have to earn it now. You just don't get it because of this title. But there's also just like unlock of latent really good ideas from smart engineers, smart user researchers, smart designers who can now who now have like this expert in their pocket, right?

30:16To kind of round out all the other things that they're not, they're not typically skilled at to bring for their ideas. And that's amazing, I think. And I think that expert, it's interesting. I'm working with an engineer and some stuff. And he uses chat GPT to even communicate to me in a more effective ways, like turn this pitch into something that will convince Lenny this is a good idea. By the way, that is actually one of my common use cases, which is the WWXD. I call it what would X do? Like I used to say, hey, what would the Sathya think about like this particular set of conversations or ideas that we're pitching and so on?

30:56This is the power of like, I think, deep reasoning plus relevant context, right? This engineer you're talking about has that context about you. And so it's kind of very interesting. If only everyone was as famous as Sathya and I had so much information out there, but I guess you can import all their emails or whatever tools exist to just like understand from the conversations you've had with that person. Yeah. And I think this is this goes back to actually what you were saying too, which is I think this idea of what is the, there's like a coil spring, there's an intelligence overhang that I just see across the board.

31:27And I think the part of product development has to almost rewire ourselves to I think Toby from Shopify calls it the reflexive AI usage. And that's not as easy. And I've been thinking about why, like I basically, I mean, I have a cheesy Chrome extension literally whenever I open a new tab, it just says, how can you use AI to do what you're going to do right now? Just like it's very cheesy, but it kind of helps to pause and think, oh, what am I trying to do here? But the reason I find it hard and when I talk even like people who are living and breathing in this space, they find it hard is that, you know, the updating of the priors is really hard.

32:06Like the models couldn't do some things one year ago. Like, I mean, image generation was full of spellings or like reasoning, you just couldn't like, you know, have deeper and smarter answers. You couldn't do data analysis. So like my impression of it from change and trying it a few months ago, that prior needs to be updated and it's hard to do that, right? And you have to kind of do something almost counterintuitive and against the grain to say, no, no, like ignore what you learned about like what this can or cannot do. Like the baby just grew up to be a 15 year old in a month. I think that last point is so important that we've tried these tools over the years and it many like so far, it hasn't been amazing and then all of a sudden it is and you kind of don't know that and you've given up almost and things change.

32:52I think that's actually if you're a product builder listening to it, that's a really interesting arbitrage thing for you. Like if you can kind of cut against the grain and say, no, I won't have that scar tissue and I'm like, you know, this didn't work a few months ago and keep setting high expectations and like demand more of the AI today, I think you can unlock more. There's a lot of alpha in doing that. That's right. Today's episode is brought to you by Coda. I personally use Coda every single day to manage my podcast and also to manage my community. So I put the questions that I plan to ask every guest that's coming on the podcast.

33:31So I put my community resources. That's how I manage my workflows. Here's how Coda can help you. Imagine starting a project that work and your vision is clear. You know exactly who's doing what and where to find the data that you need to do your part. In fact, you don't have to waste time searching for anything because everything your team needs from project trackers and OKRs to documents and spreadsheets lives in one tab all in Coda. With Coda's collaborative all in one workspace, you get the flexibility of docs, the structure of spreadsheets, the power of applications, and the intelligence of AI, all in one easy to organize tab.

34:06Like I mentioned earlier, I use Coda every single day and more than 50 ,000 teams trust Coda to keep them more aligned and focused. If your startup team looking to increase alignment and agility, Coda can help you move from planning to execution in record time. To try it for yourself, go to coda .io slashlanny today and get six months free of the team plan for startups. That's coda .io slashlanny to get started for free and get six months of the team plan. Coda .io slashlanny. I'm going to come back to this cheesy plug and say more about this. So this is a plug in that just lets you put a custom message on every new tab and it just you have it say, how can you use AI to do this?

34:45Yeah, it's as cheesy as that. And it's interesting because it works in the last few weeks alone. I've been doing this like experiment to say, hey, how much more AI pill can I get? Like both at work and in a person life to say, you know, when I'm trying to do anything manual, like, should I be demanding the AI to do this? That's so cool. Do you know the name of this Chrome extension by any chance? Otherwise, no, I built it. You built a Chrome extension. That's so cool. Okay. Did you use AI to build it? Of course. Wow. Which tool did you use to do that? Some kind of Microsoft tool? I imagine. Yes.

35:25Yeah. No, actually, it was just like, I mean, I live in GitHub and GitHub. Copilot. So just like, was like, okay, let's go build this Chrome extension. Yeah. Are you releasing this for the general public? No, I mean, this, that stuff on that's amazing thing. It took me like 10 minutes to do this. Okay. Let's link to it. Let's get it out there. Open source is thing. Okay. You mentioned Satya. I have a question about this. So you're one of the very few people that have worked very closely with both Satya and Sundar at Google. Let me ask you this. How do their leadership styles differ? And is there just like a fun story you could share by each of them?

36:02Yeah. I do feel, I do feel lucky to have, you know, kind of have a been going to these two amazing leaders of this generation. I would say, I mean, again, no surprise. They're as you'd expect from CEOs of multi -tillion dollar market tech companies. They are 99 .99 percentile in like almost every dimension you'd think of right in the leg empathy leadership, you know, be product strategy. They are of course, flavors of differences. I was at the technical advisor for Sundar with the first at Google and set up kind of the office of the CEO there. And they're again, a matter of like time and context because there's a lot more consumer oriented focus there.

36:46So what I did find, so the great added is being really calm and measured and thoughtful in terms of, you know, taking making sure that things are dealing with the complex ecosystems. And if you think about the phone ecosystem or even like the search and publisher and advertiser ecosystem, it's a very complex ecosystem. He was a master at that. He's a master at that. And I think on Satya, I find it amazing the appetite he has for learning and fine tuning his mental models. And just like the zoom levels that he can operate at, the macro, the strategy, what's the game, but also the micro. Hey, why are we don't like here's like a specific insight that I saw on Twitter.

37:28And like you can count on the fact that he's ahead of pretty much everybody else in terms of spotting those early things too. So it's just been like, like, you know, learning from the fire holes as they put it. What a cool opportunity to work with two incredible folks. Okay, let's go in a in a whole different direction. Let me just ask you this question that I've been asking people more and more. What's the most counter intuitive lesson that you've learned about building products that goes against common startup wisdom, common product building wisdom? I don't know if it's a, I mean, as common as it should be.

38:00And it's like a counter intuitive thing. But I've repeatedly learned that when you're doing something new, zero to one, the temptation is to kind of think about, you know, it's like that South Park episode. Step one, think about the problem. Step two, step three, underpants is step one. Exactly. Right. So I do feel like there's a temptation to rush and say to go to scale before solve. So I've always said to my teams, solve before scale. Right. So what that does mean is there's a different posture and different mode when you're trying to solve a problem versus scaling something that's either post product market trade or even at least like in the roughly in the ballpark.

38:48So to give you a couple of examples, right. I think when we, when you look at the solve stage, there are wide lurches. You got to be very comfortable with the fact that you're, they want thinking about, hey, a plant detection tool. And then day 15, you're like, oh, actually, the tech is really good for translating, you know, foreign language. By the way, this is not hypothetical. This is what we kind of like looked at in Google lens back back then and said, okay, like where? What is the intersection and so on? So from the outside, it looks like chaos. But actually in the, and you should be very comfortable.

39:22Not only tolerant. I think you should be like, should have an appetite for that because the last thing you want is prematurely like, you know, fix on one local hill and then you're climbing that and startups and entire product areas and companies, big companies make that mistake. And three years later, you're like, oh, how do I get off this hill? So I'd say that's one big, competitive thing. Like when you're trying to think about what mode you're in, are you in the solve mode? Are you in the scale mode? One example is kind of making sure that you're comfortable with the chaos. I think the other lesson I've learned is the danger of metrics.

39:57Right. And I think again, if you have booked on, you know, rule search or if you're worked on, you know, like, after products, you'd really have like a very fine grain sense of what are the metrics for this product? Yeah, the input metrics are going to have a whole she ban. But when you're looking at something zero to one, if you decide on a metric to prematurely, that's false precision, first of all, right? Like you kind of, I mean, CTR, when you have like 1000 people, it doesn't mean anything, you know, retention also may not mean anything. So really being very wary of like this big guy, big girl of grown up metrics as I call it, right?

40:38You are looking for more qualitative, the sound of click. And what is your, as the other kind of the handler uses, what is your set timer and play music? Right. So if you look at like Alexa and like Siri and Google Assistant and all these things, they had a very promising broad interface. You could say anything, but I think there was one or two things that it was really good at, right? Like you could set a timer, you could play music and you could play trivia. And so you got to mail those things before you say, oh, yeah, here, you can do anything with it, which is not a good recipe. That's exactly what I used to my Google for.

41:16So basic, I don't do the trivia thing now. Maybe I got to give a shout out. Got to cry that. Yeah. There's something along these lines that I've also seen you talk about, which is how to go zero to one with something, just kind of a little framework for helping you know, if this is the right time for this idea. How do you think about that? Yeah. And when we, when you think about the solve mode, and this is again, like sticking with my whole, you know, living in one year in the future, I, I gravitate towards the zero to one in solve mode products, completely thinking about new category of products.

41:47And what I found in both the hardware, I would say, is that you do want to look for at least two out of these three factors, inflection points here. If you want to make a really good product. Number one, is there a shift, is a step function in the tech, right? That's somewhat obvious. I would say like, you know, deep learning was one for Google lens back then speech recognition was a step function for like conversational search. I would say for Robinhood, you know, the generational shift was very clearly and the fact that phones were a primary means for, you know, you could actually have an app, or global app for finance that you could use.

42:25So look for that inflection, right? What is the tech inflection? And right now, of course, like an alimson reasoning models are that step function. But that's not enough. I would say the second factor that we should look for is, what is the consumer behavior shift? Right? So to give you an example, when we started working on Google lens, what we said is look, people were taking mostly pictures for sharing, right? Selfies and sunsets and so on. And suddenly when storage became free and mostly free and everybody had phones everywhere, all all all the time, you took pictures of everything, right?

43:03And then you had like enough of pictures or you use the camera as the keyboard for you for your world, right? For the real world. And so how do you kind of then say, oh, this consumer shift is big. And so therefore, kind of like as it, as you go on of magnitude more photos, then you want more to come out of them and you can apply AI to that. And I'd say the third inflection point, particularly I would say enterprise, but also in consumer is the business model shift, right? How do you, is there an inflection point, natural inflection point in the business model? So any great products, if you think about like, you know, all the way from search, again, like the the second price option and the fact that you had like, you know, CPCs, same thing with SaaS and the fact that you could actually charge or monetize enterprise products in a different way.

43:53And with AI, of course, like the monetization is a whole different like, I mean, you know, we've just barely sketched the surface of whether you do seat monetization usage, like on tap. And then of course, outcome based stuff, outcome based monetization, hey, have you solved the problem for me? And then I will pay you some fees. So all three, like to me are, you know, kind of like great, but at least two out of three for a good product. So this essentially when investors look at startups, they're always asking why now, why is this the time to start this thing? And so you're advice here is you should, there's three ways to look at it and you should two or two of these three should be true.

44:33There should be a shift in technology, some new technology that has enabled this now recently. There's a shift in consumer behavior. And then there's maybe a new sort of, or you've invented a new business model, like any way into monetize something that it gives you an advantage over folks trying to do it today. Awesome. And you didn't mention Robinhood, I think in that example, that was another good example of yeah, yeah, I mean talk about the business model of kind of again, like, not having a zero, you know, zero fees, right? And again, like the combination of all of these things is what can unlock it.

45:07Not you can't just say, oh, we'll just have a much, much more better intuitive interface and hope that, you know, people switch to it. Okay, so speaking of zero to one product, so I'm going to take us to a occasional segment on this podcast that I call hot seat corner. And I have a question for you that is on my mind and it's come up on a couple recent podcasts actually. So there's these companies like cursor, V zero, lovable, bolt replete that are like the fastest growing companies history. I just saw that cursor hit 300 million ARR in two years. Interestingly, you guys were very well positioned to do really well in this space, this AI coding tool space, you guys said co -pilot, the first tool in the world at this stuff.

45:49So ahead of everyone, you build VS code, which is all these companies that are working to build on. You have incredible AI infrastructure, incredible AI talent. So this could have been your market. What happened? What happened apart now? You know, it's interesting. The framing, so I'm a better user of GitHub co -pilot. And I would say, look, if you unpack, I think the thing, the beauty of this is that code generation is become an amazing tool that LLM's have unlocked. So it is not so. It is actually really good excitement and action that now code generation has just opened up all of these things that we've talked about the whole idea of like prototyping.

46:29Go go from idea to Marx and idea to kind of a clickable prototype in like in a few minutes. Those are the kinds of things that of course we should expect code generation to enable. The way I think about how we are positioned and like what we do with GitHub is, so it's a system not just a product or a set of features. If I think about GitHub, it's for folks who are who have their rep, rep, rep, rep, rep, rep, rep, rep, rep, rep, rep, and you have kind of, of course, you have the assistance in terms of autocomplete and you can chat. But now we have the agent board. It's one of the fastest kind of loops that we are seeing.

47:07Really strong positive feedback. So in some sense, when you have a system, what you are looking for in terms of building and designing, it is not just a single product that can go grow, but it's the, what is the repository? What is your context? What are the set of features that grow from your expertise? If you are a really expert coder, you want kind of like the assistance, this product needs to scale for that. If you are a wipe coder, you should still be able to do that and so on. So that I think is the way that GitHub is positioned to build on and like growing honestly, really well. That's so interesting.

47:47So like the core of this is everyone ends up in GitHub anyway, no matter what tool they use and that's kind of the, yeah, and I think the idea again is that code generation is a tool. We'll unlock a lot more products. I mean, they're not all competitors to the fact of they're not all kind of doing the same job. I think when you're at the end of the day, like you're building code for companies to run on, you need to have a system, you need to have kind of the ability and entire Swiss Army toolkit, right? Not just the other complete, not just a chat, not just like a software agent that runs and you kind of like handhold.

48:26You need all of this to work together and that's what the GitHub product is going after. All roads lead to GitHub. On the flip side of this question, there have been probably 5 ,000 startups that have tried to disrupt Excel and you guys just keep waiting. So something mayor is working really well. That is so interesting. You say that. So when I came to Microsoft and I'm an Excel fan, so I actually had a conversation with one of the OG Excel product folks. I was like, man, what is it about this product? He said a couple of things that were really interesting for me that just stuck with me. One is, he said, hey, Excel is a proof that non -corders also have to program.

49:09Programming is really powerful and it's the tool that gives all of the non -corders a really powerful programming ability. And I thought that was just like really striking. And then the second thing that I found out super cool, I don't know if you know this, but I didn't know at least before two years ago that there are these amazing Excel championships, like World Excent Championships, where you see folks who can do just magic. And to me, I think the insight here is also that some tools are harder to learn, perhaps in the beginning, this friction in terms of learning, but great to use. So it's a very good case of, hey, the learning curve initially, the one time learning curve might be tricky, but it is because there's so much power and depth in the tool.

50:02That's so interesting. And I never thought of Excel as a programming language, but it makes sense. And I feel like once you get used to it, and this is just the way things work, you're kind of stuck there and everything else has to basically copy them on, which is hard to be as good. Yeah, and I think the depth and the attention that the team is given, and again, that's the compounding effect over decades of working on like deep, deep signal, right, from people who live, who depend on it day in and day out. Yeah. Okay, to kind of start to close out our conversation, I want to ask this question around your career.

50:35I find that most people have a, like one moment in their career that changes the trajectory of their career. It could be like a manager they had, it could be a project they worked on, it could be just a job they landed. What would you say is the most pivotal moment in your career that eventually led you to becoming chief product officer, Microsoft? Actually, there is one moment where it was a turning point for me. I was in Google search. I was working on this idea that I thought should just work and it didn't. Like I said, hey, these phones are becoming a thing, personalization has to be important.

51:13So I probably banged my head against the wall for a year or so trying to make personalization work. And it turns out when you have a query that you put into Google search, like the personalization didn't matter as much. And so we disbanded the team. But then I think I started working on this product called Google now, which was a twist on that, which said, hey, actually on the phone, we should be able to push content. It's not about like searching with personalization. For example, if you have a flight coming up, we should be able to say, connect the docs and say, you should leave now for the, given the traffic and where you need to go and so on.

51:54Or if you're deeply interested in an upstandup comedy with Deadpan artist, you should check out Mi Checkbook. These are kind of like these really moments that the smartphone should be smarter. So I let that product through the initial zero to one phase. And that was a pivotal moment. It made me realize two things. One, I really love seeing around the corner and kind of seeing where things go and building the product rise to the occasion, way more than the scaling and sustaining products. Second, it's harsh, but being early is the same as being wrong. This is pre -LLM, pre -D planning, a lot of the really amazing ideas and terms of next token predictor, etc.

52:39We've been thinking of it, but didn't have the horsepower to go. The interface was great. The intelligence wasn't there. And I'd say the third thing that struck with me is I got to work with some really smart, like they talk about talent density now, right? I think really smart people gone on to do amazing things. And so kind of like it gave me a taste of what a small group of people can do. It's such a great story because it didn't work out right in the end, like Google now kind of went away, right? And by the way, I super remember that product. It was very cool. I remember looking at it was very delightful and happy.

53:12And so I also have this segment on the podcast, I'll failure a corner. People share a story of failure and how that helped them. And I love this is a combination of those two. Yeah, I mean, I'm not going to lie. I think it was it was it's painful when you do that because you see the vision of what can be and what is and sometimes it's hard limitations. Sometimes it takes like, you know, in this case, it takes five years or 10 years to kind of like really unlock the intelligence. But sometimes it's it's one or two key clicks, clicks stops away from the product being great. And part of figuring out is knowing when you're in what situation?

53:50How long was that period from from starting on it? So it was just like move it on. And it's not worth it. Yeah, I would say in that case, one of the good things is again, like the the it led the foundation of it was one of the foundations of the Google assistant. And of course, as the LLM's, you know, step function happened now with Gemini, it kind of like works out. And I think it's the same thing across the board, which is sometimes you want to kind of figure out the invariance that do work, right? That can then that then go on to the next version of the product. And other times you just have to start over.

54:23It was a Google now the first agent before agents sort of feels like I was certainly the idea. Yeah. You know, inter, but it is fascinating to me that the interface that there we had the opposite problem like whether you think about all the voice assistance, right? The interface is like we overshot and the intelligence wasn't there. Today, I feel like there's an opposite problem. I think these these things have amazing intelligence and the interface we have largely is like the AOL, AOL, DialogModum chat, what? We've covered a lot of ground. Is there anything that you wanted to chat about or leave listeners with maybe a last nugget of wisdom before we get to a very exciting lightning round?

55:06I think I would say one thing that I'm really excited about is this idea of figuring out how we as people and agents collaborate together, right? I think there is like some great set of products and experiences to be reimagined. That's my other Roman Empire, which is how do we actually have this co -working space where you know, you have kind of like the the humans and agents and how do you actually kind of have an output that's much, much more significant than what anyone of us or any few of us can produce? Well, I need to hear more about this. What do you when do you imagine a co -working space of humans and agents?

55:44What does this look like? Is this like Microsoft Teams or is this like a physical place with little robots? Oh, I had a thought of the physical place, but I am thinking I am thinking a lot about kind of you know, right now all of these experiences are very civil player, right? And I do think there's an opportunity to think about how do we again, I'm living one year in the future, how do we actually have like you know, collaborate with each other, but with also with agents and really figure out, for example, what tasks can be delegate, what can be kind of like inspect, how do we actually have information that flows between people, that agents can mediate and so on?

56:23All right, I'm curious to see what you guys got cooking. With that, we've reached our very exciting lightning round. Are you ready? Let's do it. Let's do it. First question, what are two or three books that you find yourself recommending most to other people? Oh, I have recency buys, but I've been reading this book called The Brief History of Intelligence, Phenomenal Book and you know, like lots of lots of underlining for me. And I think it kind of the premises to it looks at the evolution of intelligence like human intelligence and kind of the brain development and I've kind of connects that to what we're what we're seeing with the eye.

57:01Do you ever favorite recent movie or TV show that you really enjoyed? Hacks. I've been watching this. It's about a woman who who's just like a great stand -up comedian of I think it's set in kind of like the the fact that she grew up I think in the 70s and 80s and kind of like really tried to break through in an industry that hasn't traditionally been like very friendly to women. So really fun and quirky. Do you have a favorite product that you recently discovered that you really love could be an app could be some physical? I do use a lot of Microsoft products GitHub, Copilot being one of them, but I think the one that I maybe I'll pick is Grenola.

57:44I think it's the name of the app. I found it really useful. I just gave it a spin the other day and I'm like, oh, this is really useful in terms of being able to you know again like without being intrusive just just capture the thoughts, notes and structure it put some it felt like one of those things where yep the components of a few things like we were talking about right like the transcription real -time transcription tech has gotten really good voice recognition is great and then enough of the LLM magic on top of it to kind of make it structure and contextual. I am a huge fan of Grenola. I'll give a quick picture if you become an annual subscriber of my newsletter you get a year free of Grenola for your entire company.

58:28Did not know that. Okay. So and then just check that out Lenny's newsletter .com and you click the word bundle and you'll see how to do that. Very cool. Two more questions. Do you have a favorite life motto that you often come back to when you're dealing with something maybe share with folks they find useful as well in work or in life? I have one. In fact actually this is my email signature for I don't know for the last 20 years or so says the best way to predict the future is to invent it. I think it's a quote by Alan Kay. I find it useful for two things. One is no one knows anything like when you think about like all the folks or kind of think about hey this is this is exactly how everything is going to look and this is exactly the sequence and so on.

59:11I think there is no substitute to experientially like building it and and I think the second part is you know like if you think there's something that is that should exist go build it. I love that. Final question we've talked about stand -up comedy a bit. Is there a is there like a favorite under the radar stand -up comedian they think people should go check out? Oh there's a there's a couple of them. So one I think there's a there's an Indian American or I think I think a British Indian stand -up comedian her name is Sindhu V super smart like you know mom comedy and I think the other one that he this is definitely not under the radar but like I've just like love his stick is Nate Margazzi he's just so good.

59:59A perna this was amazing two final questions working folks find you online if they want to reach out maybe and follow up on anything you shared and how can listeners be useful to you? You can find me on LinkedIn and Twitter. A perna CD is the handle. I do post stuff a lot more on LinkedIn these days so you know would love would love to hear thoughts comments conversations there. I'd say one thing that would be super interesting is if any of the stuff spark conversations particularly around like kind of you know this what do what can a small team with a lot of AI tools do or new products that folks are really excited about saying that they should exist keep me up.

1:00:42Amazing perna thank you so much for being here thank you bye everyone thank you so much for listening if you found this valuable you can subscribe to the show on Apple podcasts Spotify or your favorite podcast app also please consider giving us a rating or leaving a review as that really helps other listeners find the podcast you can find all past episodes or learn more about the show at Lenny's podcast .com see you in the next episode