The Exchanges

Q I was working through your curriculum and you pointed out that you found a way to express to somebody that they are in fear. I think it was your wife that kind of like iterated on how to give you a feedback that you're in fear where you didn't get defensive. It like got more fearful and angry. And can you talk a bit about that?

A Yeah. So we, we iterated, um, I at times feel anger and I act on that anger and I don't even realize I'm in anger. So I wanted her to let me know. And so she would say at first, she said, you're in anger. And that just made me feel accused and made me go into more anger. And then she said, are you in anger? And that felt passive aggressive or indirect. And that also made me go into more anger. And then finally she said, I perceive you to be in anger. So it's an I statement and it's simply what she's perceiving. There's no judgment. And that was able to punch through my anger. And then I, I woke up and went, oh, and then I stopped and just didn't act until I was able to shift out of anger.

AI assessment note: “And then finally she said, I perceive you to be in anger.”

Q Awesome. To give folks a sense of just how successful and big Snyk has gotten, one is just, what does Snyk do? We haven't even talked about that yet. And then two, just some stats about the scale of the company and the business at this point.

A The developer security company. We make it ridiculously easy for developers and their teams to improve their security posture while still moving fast. So Snyk can find and automatically fix vulnerabilities in code, Open source dependencies, containers, infrastructure and cloud configurations, and all underpinned by the best security intelligence data in the market with a laser focus on developer experiences, which is why we're, we're really different. It's also an amazingly fast growing business with some stellar PLG focused investors and board members from the likes of Ed Sim at Boldstart to Tamar Yahoshua, Slack's CPO. We were founded in 2015. Last valuation after our Series F was at 8.6 billion. We're securing the software of millions of developers now, well over 2000 paying customers, now around 1300 people, of which around 500 in R&D, with nearly 70 folks in our product org. And the people here just create this amazing culture, and all in all, it's just a really exciting place to be.

AI assessment note: “Last valuation after our Series F was at 8.6 billion. We're securing”

Q Anyway, enough about Jules. So to give listeners a little bit of context on yourself, can you just give us like a 55 second overview of all of the wonderful things that you've done in your career?

A Oh, we'll do real fast. So big highlight about me is I'm originally from Trinidad and Tobago, an island in the Caribbean, came to the U.S. for college, double E, got seduced by consulting, and did that for a couple of years, worked in oil and gas, electric power, heavy industries, love that stuff. But also like writing code on the weekends for fun. So I thought I should move into tech and I did. Worked at Intuit and helped develop their first iPhone app, which was, you know, a thing back in the day. Worked at a startup. Growth team at Facebook for four years, working on user acquisition, which was really fun. And I get kind of like strong, performative experience I had. Quick stint in biotech, and then worked on marketplace at Lyft. So rider pricing, real-time driver incentives. Matching writers with drivers. And then a lot of the operational tools that we use to manage our marketplace. And so that's a bit of my journey in maybe 45 seconds.

AI assessment note: “Worked at Intuit and helped develop their first iPhone app”

Q business to build on top of their marketplace and find some kind of recurring revenue component. And then in reverse, a lot of SaaS businesses look for how do we add a marketplace to what we're doing? I'm curious how often you find that this actually works out and what do you have to get right to add this other type of business model on top of something that's working?

A So broadly, I will say, I think it's easier for a marketplace to go SaaS than it is the other direction. And the reason for that is two things. One is it's a new capability to, to generate demand, which is fundamentally what a marketplace has to do. And it's a higher value activity. This is why like the, the effective commission of a marketplace, often, 1015, 20% is much higher than the effective commission of a SaaS business in the two to three percent range. So you're just doing Much more of the value chain in the marketplace. And second is the marketplace by definition starts with relationships on both sides, but the SaaS business does not have any relationships with the demand side customer. And so they have to acquire a whole new type of demand to make this work. It's not to say it can't work. There's actually like a classic kind of SaaS bootstrap to marketplace playbook. This is what OpenTable did. I think we actually see some new examples of companies doing this, like One in the health healthcare space is Solve. They built some interesting products for healthcare clinics that they're now bootstrapping into marketplace. And so I think it's possible, but I think it's very difficult. And then for a marketplace, the lens you should take is much less about how to drive more monetization, but just how do we create a much better experience for our customers? Because there's som…

AI assessment note: “I think it's easier for a marketplace to go SaaS than it is the other direction.”

Q if it's not enough where you can charge anything meaningful to run a business, it's just not gonna work. And so that's a really good way of framing it. Final question around marketplaces and broadly, and I'll let you go. You've spent a lot of time on marketplaces is seeing their evolution. You've worked on this maybe for the past decade. Where do you see the future of marketplaces going?

A I actually wrote a blog post on this where we charted The commission that a marketplace charges and the year they were founded. And if you put those on the X and Y axis, there's this very clear up into the right trend. Like newer marketplaces are charging higher commissions and they're doing more work to justify those commissions. And so like broadly the evolution looks like kind of like marketplace one point O, which is all they're doing is aggregating demand. So that's like Zillow and home advisor. They're basically like lead gen and their commission rate is often pretty low. It's like five percent, maybe 10%. Then you have a managed marketplace like Airbnb or Etsy, which did something like really fundamental on top of that, which is generate trust. So they, that had supply, like you could probably tell me more about what Airbnb did in this space, but like they, they made it a safe transaction. And there's a lot of work it takes to make that transaction trustworthy and safe. And so they charge a higher commission as a result. There's then one click beyond that, which like for lack of a better term, you could call it like a heavily managed market. But now they're typically doing like some work in the value chain, which is distinct from just aggregating demand. So like, you know, DoorDash and Instacart own logistics. They took over logistics. And as a result, like DoorDash did …

AI assessment note: “newer marketplaces are charging higher commissions and they're doing more work to justify those commissions.”

Q Is there a better approach to that specific problem that you've found or is that too broad of a question?

A Kind of the first line of defense in any problem solving would be, how would you make it easier for somebody to do? And so in the personal finance world, Really the answer to most things is just default. So it worked for automatic enrollment for a one K. The reason we have retirement savings in America is because people are defaulted into saving from their paycheck. So that would be first line of defense. Obviously difficult for product teams to execute on takes a lot of back end infrastructure. So if we're just solving the personal financial management stuff, like a budgeting alternative, we'd actually go to making it not just logistically easier, but cognitively easier. So We call them rules of thumb. Like, instead of having to decide in the moment, do I do this thing, and you're weighing the pros and cons, you know, it's kind of typical econ, like, how much is this three dollars worth to me? You'd actually make a rule of thumb that says, do I do it or not? So instead of deciding do you take a Lyft, you know, when you're coming home from work, you'd have a rule of thumb that says, I don't take Lyft on the weekdays. I take it on the weekends. Very simple now to actually make this kind of decision. It's a heuristic. It's not going to be perfect, but it's going to help you reduce your spending in an easier way, at least in a way that you'd stay adherent to.

AI assessment note: “we'd actually go to making it not just logistically easier, but cognitively easier.”

Q Can you talk a bit about how you came to those To conclusions. I know you work really closely with the product team and there's this whole process you go through. How do you come up with these ideas? How many ideas did you test? Is there anything more you could share on that?

A Yeah, it's actually a pretty involved process. So first we did a literature review, which is basically saying like, look, we're not the first people to think about this. Let's talk to the experts and understand what has worked and what hasn't. So with that, actually one of the insights was that reminding people About their value of accuracy. So most people want to be accurate. Most people actually don't want to share this information. And so if you can remind people at the point of sharing, by the way, it doesn't work if you remind people before or after, like it's at the point of sharing that this is unverified information. Studies have shown that this could decrease share. So we took that piece. We also took this, you know, like the hot and cold state literature that says, if you actually don't want to get someone to do something, how do you intervene? So we did this literature review. We came up with a hypothesis and we had probably 30 different ways to implement this because the hypothesis is just a starting point. And then we put it into quantitative research. So we actually put five different versions of the pop-up in front of over a thousand users, which, you know, we got users from Prolific, which is a, a platform where you can easily test things. And we didn't measure, yeah, we didn't measure the idea of like, Do people like this? We measured a condition against anothe…

AI assessment note: “So first we did a literature review... we put five different versions of the pop-up”

Q team like this again somewhere, it was kind of R and D horizon three or two teams. Is there anything else you would do differently? Anything, any lessons you take away from this experience for maybe founders that are, or PMs working at larger companies that are like, Hey, we should have some like this. Is there anything else that you find is important for making something like this successful?

A The criteria for moving researchers back into The, you know, their R and D team, whatever that happens to be for your organization. That can't be based on a calendar. It needs to be based on a replacement in seat who's actually doing the job and has picked up all of the skills necessary. And only then can the researcher move back. So make sure that you've got continuity of expertise and skillsets and domain familiarity before you move over. I feel like we've, we've, we've managed that pretty well today. As well, it's critical that the team who is taking over from the R&D shop feels like they have control over their own future. Uh, you can't Really delegate roadmap to an R&D team. The team who's responsible for maintaining the product, for building the product, who has the closest feedback loop with the end customer. They're the ones who really need to own and, and feel like, you know, they control the roadmap. And so making sure that you're not outsourcing innovation exclusively to an R&D team, but that is happening within the product team as they take ownership. Over the idea, and over, kind of, the use case and the customer. Last I would say here is really that engineering fundamentals in a lot of ways are the contracts that differentiate an R&D team from a operational product team. And bringing that fundamentals process into it is going to feel candidly a little bit unnatura…

AI assessment note: “The criteria for moving researchers back into The, you know, their R and D team”

Q How many companies have you worked with at this point, advised, and what are some examples, just like companies people would know?

A It's now been about, uh, I guess two years and three months since, you know, my last day at Grammarly in an, in an operating capacity. I probably worked with maybe 15 companies in the last, you know, two and a little bit of years. Obviously not all at once. Right. It's usually four to five at any given point in time. But some of the ones that I've been really, that I've really lucked out with in terms of, I mean, in terms of getting aligned with, you know, companies like Canva, uh, Airtable, hims and hers in the personal care space. There is otter.ai. Who else? Flow help. Uh, you know, the, the world's most downloaded period tracker.

AI assessment note: “I probably worked with maybe 15 companies... companies like Canva, uh, Airtable”

Q a ton of about yourself and your kind of background where you grew up, where you're, where you're born and things like that. So I'd love to Learn a little bit more about the human that is Shreyas. And so maybe you start there. Like, where were you born? Where'd you grow up? What'd your parents do for work? Or what did you want to be when you grew up?

A So I was born in Mumbai, Bombay, India, and I lived there for the first 21 years of my life. I actually did not really even get to see many parts of India while I grew up in India, and basically just was in Mumbai the whole time. And then I moved here to the United States for graduate studies at age 21. My parents, my father was a businessman. And so he started his own business. He manufactured spices and marketed them. So growing up, I saw him work on packaging and pricing. And I used to, when he was short on staff, I used to be packaging the spices into the little box. Or creating some marketing material for him, not the creative part, but the grunt work. So I kind of grew up in that environment where the lines between what was my dad's business and our personal lives were very blurred. My mother, you know, just growing up was a homemaker. And so my dad was largely kind of just busy and all consumed in his business. And I ended up spending a lot of time growing up with my mother. And so both of them have had a pretty significant influence in different ways, but both significant influence on who I am. What I wanted to be when I grew up, I changed that a lot. When I was very young, uh, one of my uncle is a doctor, so I kind of saw him and I was like, oh, maybe I should be a doctor. And at some point later, I changed that. In high school, I took French and I ended up being reall…

AI assessment note: “I was born in Mumbai, Bombay, India, and I lived there for the first 21 years”

Q Awesome. I will check that out. What's a favorite podcast or even newsletter on marketing?

A I love Nick Sharma's weekly newsletter. He's a growth marketer. He started his career, I think at Hintwater. So he does a lot of like CPG, um, type DTC. Uh, he has a great marketing newsletter that comes out every Sunday night, um, on podcasts. I love how I built this. I know that's already really popular, but I love that one. It's not really marketing, but just like general business. The first round podcast in depth is pretty great. Lenny's podcast I've been listening to is awesome. And then my friend, um, Jasmine from the Concept Bureau has a marketing podcast called Unseen Unknown. And it's kind of about like culture and, and branding and how these things, society and trends, it's not like straight marketing. It's kind of more of like the culture and sociology that informs marketing.

AI assessment note: “I love Nick Sharma's weekly newsletter. He's a growth marketer.”

Q I want to spend a lot of time talking about what you learned driving growth with these companies, but one quick question. So Gojek's kind of the super app where you do a lot of stuff in one app. Do you have any insights into why a super app hasn't emerged in the US?

A Yeah, I think the sentimentality of a conglomerate is very different in Southeast Asia. So we've grown up with, you know, a specific conglomerate owning, not just the mall that you go to, but also the apartment building that you live in and the school that you go to. And so they're very well integrated and there's a sense of trust in a conglomerate. Whereas in America, we already kind of shy away from like, does Google know too much about me? There's also, I think the second aspect of it, which is that in Asia, we've kind of leapfrogged to the computer era. So everyone has a phone, but you may not even have a computer in the entire household. And so when your phone is full, are you gonna delete a photo of your kid or are you gonna delete this app? You're probably gonna delete the app. So for anyone to really survive, it has to be part of this super app concept.

AI assessment note: “Whereas in America, we already kind of shy away from like, does Google know”

Q many companies and so many startups, so many products, everyone's launching the speed at which companies and products are shipped is like thousand xing. How do you think about durability and moats when you look at a startup? Because a lot of founders get that question. Everyone's getting that question. How am I not a rapper? What are, what are signs that tell you this might be a durable thing?

A Well, I think there's two important ideas. One is something that, um, Jesse from Decagon said, which I love, and that is that moats are most often discovered, not designed. I think it's really easy. I've done this as a founder to get in your own head about like, Hey, I need a business plan that survives scrutiny from MBAs and VCs. I've got to have some really sophisticated, you know, idea of what my moat will be. And for that team, they just started shipping and it developed over time. Another great example of this is cursor. You know, they were criticized a lot for not having a moat, but it turned out that initially being a high NPS DAU product was really good. And over time they captured all the reasoning traces. They train their own models, the composer one, two models, and you know, so on and so forth. We know how that story plays out. So moats can be discovered. They don't have to be designed is one. And then I think the other is that we seem to have forgotten that the classic moats, none of the classic moats are based on how hard it is to make the software. You know, like we're not building self-driving cars. Most of us aren't. So it's network effects, it's scale advantages, it's brand effects, proprietary sort of data or what was historically called a cornered resource. Every moat from five years ago generally is still a good moat. We just need founders that have ambitio…

AI assessment note: “moats are most often discovered, not designed”

Q knowledge work mode. It's actually codex doing all that work, but people may not know what codex is. Maybe not. They may be afraid of it. Is there anything in that work mode? That's not just codex. Cause that's actually really interesting. Is it like, is there like additional harness tweaks to make it feel a little different or is it just the same thing with a little different UI?

A It's, it's really at the UI level. Um, so work mode and codex mode, if you go to codex and ask it to generate a amazing financial model to price your product or something like that, or like, tell me, predict my revenue for the next six months or something like that, codex will do as good a job as work mode. It's like really about, whilst it's doing so, what kind of UI do you want to see in the chain of thought? What kind of technical detail do you want exposed to you? The, it's like incredible, it's similarly powerful. And so codex users aren't missing out on anything. by not switching modes. In fact, we do not want them to stay in Codex and do all the stuff you want to do in Codex. And we will show you the appropriate UI based on the things you asked for. Truly, our North Star is to merge all these things so that users don't have to make any of these decisions. The separation is really more about how can we meet people where they are as much as possible in terms of the products that they use, in terms of their familiarity with concepts, and make sure that We are enabling everyone to take advantage of working with agents, which has transformed entirely the way every single developer works. We should do the same thing with knowledge work.

AI assessment note: “It's, it's really at the UI level.”

Q Start work, meaning implementing, rolling out people onboarding. Got it. Got it. Got it. Okay. Amazing. Okay. So that's step 11, papering prep, setting timeline for procurement, kind of getting on board with like, what is it gonna take to sign by the state? Here's a little gift you'll get if you do it by the state free month or whatever. Okay. Uh, step 12, papering review.

A Yes. The best thing you can do is they're gonna send you back red lines. No question. If the red lines are extensive, Okay. Go ahead and accept the things that are easy. The red lines are extensive. See if you can get legal on a call live and just talk through them. That will accelerate your sales cycle versus a bunch of back and forth, a bunch of back and forth, get them on a call. Be like, Hey, everything. We're 80% of the way there. I have a few questions based off of your red line. Can we jump on a live call and just go through them? Focus on the things that are going to impact the business and pushing on those. Let the other stuff go. If it's not super important, obviously have a lawyer, look at it from your side. You're dealing with a commercial lawyer, commercial legal team, have a lawyer. Look at their red lines.

AI assessment note: “The best thing you can do is they're gonna send you back red lines.”

Q What's like, uh, what's, what's like a context where you had said to someone, Hey, we go play the accordion or we're playing the accordion. Like, like what are they usually doing wrong?

A It tends to be that you're shipping something with in a very local sense without necessarily understanding, uh, impact. So, uh, an example right now is, you know, the core of most marketplaces is listings, right? Like if you try and think about amazon.com without listings, there's basically nothing there. It's a bunch of, you know, it's a left rail or right rail and some videos. Um, in video commerce and live commerce, whatnot, you don't really historically need listings. If I want to sell you a pair of AirPods, I could literally hold them up to screen and show you them and describe them and say, they're AirPods. I'm going to start them at a dollar. And as a buyer, you now have all the information you need in order to kind of like make a purchase decision, which is great. And so you may not have to invest in making listings the way that someone else does. And that's probably net good for a seller because It takes like three and a half minutes to make a listing. Uh, and it takes zero minutes to describe a thing and hold it up. Uh, but you then zoom out and say, oh shit, new buyers are going to come to live commerce and expect search to function. If I don't know what you're selling until after you've sold it, there's no possible way that I can put somebody in the right stream for ear pods because they didn't, we didn't know you have them and I therefore can't direct people to it.…

AI assessment note: “It tends to be that you're shipping something with in a very local sense”

Q to describe it kind of more broadly. It's not going to be an exact match. So this is a really interesting change in the way product happens and will happen is evals. Writing evals versus PRDs is, is a big part of this. Do you guys still do PRDs? Is there still like a one pager describing a problem or is it replay? Okay. Now you're shaking your head. Yes.

A We, we, we are, we do. I think Um, when there's a very defined problem, I think things like evals might be almost a shorthand. I think there's other cases where PRDs are really valuable. Um, PRDs are great vehicles for getting a very large group of people aligned on a set of sources of truth about experience and set of goals. So when we do have a model, we actually, for every model, we do have a PRD. Less necessarily for our researchers, but more for our growing product surfaces, for our engineering teams, for our, um, stakeholders like legal and safety and others as just a source of truth of putting together what we're aiming to achieve so that a big group of people can row in the same direction. The other place where I do think PRDs are valuable are on the more ambiguous Problems and opportunities, right? So we, if we haven't shipped a thing like computer use, we don't necessarily have a set of like user specific pain points always. And I think there's value in the product vision portions of a PRD to explore What could, even if a technology is not yet ready to work for everyone, how do you get it to work well for some group? So you can explore the value. You can actually bring something that is, uh, coherent to a user group. So we do have PRDs. Um, I think the application's a little different now.

AI assessment note: “We, we, we are, we do... for every model, we do have a PRD.”

Q So let's actually look at that data of just how this sort of classification connects to just optimism burnout, things like that. Uh, because this is, and we're gonna come back to just like, what exactly is that divide? Just the question to ask that tells you which side you're on, but let's look at this first.

A Yeah. So we'll dive into some of these things in a little more depth later on, but just to put it all together, what you're looking at here is the AI identity stance, and then a breakdown by your AI identity around career optimism, burnout, layoff worry, And an interesting one for me, and we'll talk about this further. Would you recommend your role to someone coming into the industry now? And what you can see is that as you move from the people who feel amplified to the people who feel diminished, career optimism goes down significantly. Burnout or reports of burnout go up significantly. Layoff worry. Also rises significantly. And perhaps the most significant finding of them all is that people would not recommend junior people, early career people entering into the tech workforce at this moment, given what's happening with AI. And you're seeing these very linear, clear and organized effects. Which just demonstrates to you the impact that AI is having on all of these different variables.

AI assessment note: “career optimism goes down significantly. Burnout or reports of burnout go up significantly.”

Q Yeah. Is there an example that comes to mind when, cause yeah, what's like in, what's a, what's a company or two that started very unambitious?

A I love the story of bolt.new that really blew up last year. I loved it so much. I cold mailed the founder cause I was just so impressed with, yeah. And you know, they, They toiled in obscurity on something that they were into, and then they open sourced it. I think they were barely able to keep going with commercial development. And then they had this realization one day of, wait a second, if we take these, uh, web stacks, this virtual machine that we've been making Work on the web, but we actually add that to an AI coding co-pilot. We now have something that's better than what anybody else has. And, and I, I think that was just a great story that he, they were passionate about one thing and you know, and they stuck with it.

AI assessment note: “I love the story of bolt.new that really blew up last year.”

Q at the end they were like, oh, and this iPhone thing launched and they're like, no, this is dumb. It's like no keyboard. And it's not serious. Can't do anything with it. I've always wondered just being on the other side of this, being within Apple building the iPhone, uh, how much did you guys actually doubt that? Okay. Maybe they have something. Maybe we need to add a keyboard.

A It was the most heated. Conversation, and it dragged out the longest. There was one, one way of looking at the Blackberry, which was, that is the market we want to go after, and we want to win. And then there's the other side, the flip side of that argument, which is, Only one percent or two percent of mobile phone users at the time had a Blackberry, knew what a Blackberry was. So what about the other 98% of the people? What would they want? What would they need? Why are we going to go after winning this, this very loyal and, and, and, you know, um, incredibly passionate user base and try to pull them away from something. And so there was this Basically head to head competition between a display keyboard or a virtual keyboard and a physical keyboard. I had been doing virtual keyboards for a while since general magic and then in the nineties, and I knew what handwriting was and, and keyboards were like on these touch screens. And, but I was only doing it on a, um, and I was writing software and calibrating them, making, trying to make them work with a single touch, uh, display. Resistive or what have you. And so I knew what the limitations were of those kinds of things. So I was like, this is really going to be difficult. And we hadn't, you know, multi-touch was just, you know, was on a big ping pong table and like, it hadn't been scaled down. So it wasn't like something in a co…

AI assessment note: “It was the most heated. Conversation, and it dragged out the longest.”

Q like is growing. It feels like if you've seen these surveys, AI is like less popular than ice. People are trying to stop data centers from being built. I think Eric Schmidt just did a commencement speech and people were booing him every time he mentioned AI. Just like, where do you think, what do you think is going on? Where do you think this, how this goes over time?

A It's interesting, and it's a big sort of fuzzy mess of different stuff, I think. There is like tangible, like my electricity bill went up, which applies actually in a very small number of places, objectively, but it did, and this is a question. The water thing is weird because it's just like completely fake. Um, and I should call, explain what I mean here. Um, data centers use water for cooling. It's mostly closed loop, but the number of data centers relative to the total amount of water use in the USA is tiny. I actually went and dug into this at the Livermore lab. Did a study at the end of 2024 where they estimated US data center water consumption, and it came out at about 0.017% of US water consumption. Now, obviously if you live in a small town and you've got one well, and like they capped the well and gave all the water to the data center, then you're really pissed off. But like, that's like, that's a planning problem. That's not a data center problem. You know, in generality, yes, this is, you know, data centers of what, like five percent of U.S. energy and might grow one percent a year for the next five years, one percentage point a year, but the water stuff is just nonsense. And then you get into more tangible, like, well, what is happening with this? Is it taking jobs away? Where you can watch a bunch of three-hour podcasts of economists talking to each other, and the …

AI assessment note: “it's a big sort of fuzzy mess of different stuff, I think.”

Q Okay. Uh, on the goals, what are kind of like buckets of goals? So cost is when you shared, like, we need this under 300 dollars. What are some other like buckets of types of goals people should be thinking about?

A So in VR, uh, display resolution or arc minutes, um, like how many pixels per degree do you want is actually one of the key metrics. So you need to understand what your key metrics are and why is that key? Well, that's your visual field. So you think about retina displays on, on MacBooks. Um, they figured out the KPI of what the human eye could see, probably overshot it a little bit and built that. And then do you really need to Keep as much engineering pressure up on the resolution of a display after that. Maybe not. So VR is not there yet. Not, not even close. So not in mass produced VR. We don't have retina displays yet. So that is one aspect of pushing that up is one example. I think on a computer, obviously you're talking about clock speed. You're talking about, um, how many parallel processes you can run. You're talking about weight. Um, you're talking about price. Um, And you're talking about features. So when we did the MacBook Air, it became very clear because we were machining it, that there are certain features like, uh, ambient light sensor that we just didn't make sense anymore. And so being willing to just jettison them, uh, uh, for, for what we were going for, which was weight and size. Um, so if you have those overarching goals, you can actually make decisions, engineering decisions pretty quickly. And this is actually something that I think Elon I've heard does…

AI assessment note: “display resolution or arc minutes... You're talking about weight. Um, you're talking about price.”

Q So let's say, let's say Matic is an example. Like how many components are there that they all have to assemble and not have one not available?

A I'm doing the math in my head. They probably have between 50 and a 150 parts. It's possible that they have more. I haven't seen their CAD, so I don't know what it's like inside their device, but they do have a lot of things going on, right? They have the wheels of the device that are obviously moving around, then they have a vacuum, but they also have a mop. And obviously they have a vacuum bag. They have the, uh, the reservoir that, uh, the liquid has to go in for the mop. They have a, uh, system, which I think is SLAM based, which can see your room and, uh, make a map of it and identify which surface is which. And that I believe stays on the device. So it doesn't go up to the cloud, um, which is also kind of what we did in VR as well, which I think is a good practice for a good privacy practice. And then they of course have wireless modules that connect up Uh, so you can, so you can communicate with your device. They're gonna have a SOC, um, silicon. They're gonna have RAM. Um, they're gonna have PCBs. Um, and if you take everything off of those things, like all the little caps off the PCBs and everything, then you're in the thousands of parts easily. So it depends on how you count, but this is not a simple device.

AI assessment note: “They probably have between 50 and a 150 parts.”

Q or we'll link to it in the show notes. It's so powerful. Final question. Somebody that, uh, that knows you well shared this really interesting tidbit about you that you hired a PhD to tutor you on the, on the staples of ancient Greece and Rome and just get really nerdy about this stuff. What's going on there? What drives you to go so deep on these sorts of things?

A This is like very niche nerd, nerd territory, but I found this, um, list That the poet Joseph Brodsky Brodsky wrote, which is a list of English, uh, or a list of things you should have read in order to have an intelligent conversation in English. And it is like an affected list. Like it's, you know, it's intense. It's like the Old Testament, Gilgamesh, and then all the way down through. But what I found is it's a pretty good, um, distillation of what we used to call the Western canon. And that actually I learned a lot in, in my public school education and in college, but I never really learned from what you would consider the Western canon. Um, and so this is kind of, um, in addition to that, there's some, some more newer, newer, um, Books on the list. I find it just fascinating to have something to work off of. And what I found is as I got into specifically the tragedies, the Greek tragedies, I just didn't have enough context to learn what I wanted to learn and just reading them. I didn't have enough uptake. So I found an incredible, um, uh, postdoc who's was willing to tutor me and I just get to ask him all these questions. He's an encyclopedia. He knows everything. I could ask him what was happening in Turkey at the time of this Greek You know, this tragedy that we're reading, and like, what was happening in Athens, and like, what this, you know, tragedian might be respondin…

AI assessment note: “as I got into specifically the tragedies, the Greek tragedies, I just didn't have enough context”

Q up with. What I think about as I think about this is there's a video that you, uh, pinned to your Twitter profile that we'll link to, which I think is Dita Roms. Is that who that, who the person is? Okay. He's walking around. He's just criticizing all these designed chairs. Uh, talk about what that video is trying to, why you pin that to your, to your profile.

A Uh, there's many reasons. One is, uh, um, I think maybe the only thing that I have In common with this very accomplished person is that we're both German, and so sometimes I joke that I also aspire to disapprovingly just point at things with my walking stick and say, this isn't good enough, this isn't good enough. The reason why is because I think if you speak German, this is one of the funniest clips that I've ever, I just die laughing every single time. I'm actually curious how you think about how it ties to Malleable software, because the main reason why I use that as a clip of reference is I'm very much in the camp of design should be first useful and then beautiful. And I think a lot of the pieces there are predominantly things that you put in a museum for display. And if you try to sit on them, you'd be like, what is this nonsense?

AI assessment note: “the main reason why I use that as a clip of reference is”

Q Whoa. No. Okay. I'm afraid. I used to watch it, and I'm more afraid to watch it now. Okay. Uh, favorite product you've recently discovered that you really love? I know you put together a list of beautiful products that, that people buy. Uh, what's something recent?

A Well, that list that I put together was for products that I think people should buy, I think, or that I thought, I actually did the taste emulation. I'm like, oh, I think a lot of people are going to find this useful. Uh, I have weird ones now for you, which is. Yes. Uh, okay. So there's not a, you can just, it's a product. It's great. It's ghosty. Terminal emulator. Like most people use terrible terminals. Don't do that to yourself. Just use ghosty. Huge fan of the work that, uh, Mitchell is doing. Uh, and then there is a new one for the phone called Moshi. M O S H I. That one's not free, but it looks very well done. I'm like currently exploring it. I mostly code on the phone now. Um, cause I don't have a real job. Uh, There is an open source keyboard called, uh, I don't even know how to say it, Corne, C-O-R-N-E, which is a split keyboard. It looks very weird. The reason I like that one is I'm trying to claw back as much agency in my compute life as possible. This one is very open source. If you really wanted to, you could, like, download all the schematics, send them off to China, and you have the PCB back, and, like, you can just build it from scratch. Um, and then This one's silly, but I like tools. I like physical tools. Civivi pocket knife, which is pretty high quality, maybe more expensive than what most people would spend on a pocket knife, but I think a good pocket kni…

AI assessment note: “It's ghosty. Terminal emulator. Like most people use terrible terminals.”

Q say. And then maybe threads, which I think is cheating because it just sits on top of Instagram. Basically nothing else has worked other than Snapchat, 15 years ago. And in spite of everyone, just like everyone innately just wants to build a consumer product, social app. It's just like where everyone first goes. Everybody fails. Nothing works. Why is it so hard? What do you think people don't get?

A Well, I think it's really interesting, you know, in terms of the examples that you just shared, right, of, of TikTok and, and threads, because you, you just shared two examples of people who figured out distribution. And I think that that's actually one of the hardest things to figure out in consumer technology today. We were so fortunate when we created Snapchat, the mobile phone, you know, and the app store were just getting started. So people were downloading lots of new apps all the time. They were really excited about trying new. Uh, services, you know, Instagram, I think it started a year before Snapchat or something like that. So there was a real appetite to try new apps and new services. And that's not the case today. It's a lot harder to get distribution for new ideas and new services. People aren't downloading as many apps now as they used to. And both TikTok and threads figured out distribution, which is why I think there are more recent examples of success. TikTok did it with money, uh, which I actually thought was really innovative. Uh, they spend billions of dollars subsidizing both sides of their video marketplace, right? Acquiring customers to watch videos and then paying creators to make videos. And so they were able to bootstrap, uh, you know, the, their ecosystem. And I think with threads, obviously they were able to leverage the amazing distribution, uh, tha…

AI assessment note: “I think that that's actually one of the hardest things to figure out in consumer technology today”

Q revenue, something like that. One of the very few social networks that lasts, that is durable with like a very, uh, valuable, interesting audience. On the flip side, the stock hasn't been killing it. There's like these investors coming at you trying to tell you to change all these things. Uh, I guess just thoughts, reflections, and what do you think people are, are missing about where this might go?

A Well, that's really one of the reasons why I call this year, uh, a crucible moment. I mean, the, the company's almost at the scale of entering the fortune 500, which is really exciting. It's almost at a billion, uh, monthly active users. Uh, it's about to launch specs after, you know, 12 years of investment, uh, in this future computing platform, you know, but at the same time, it's, it's still not net income profitable, for example. Uh, because we've been investing so heavily, uh, in the future and making, making the choice, uh, to do that. And so I think this is the year that we have to prove that Snapchat, you know, can be a really strong, profitable business that it continues, uh, you know, to grow and both in terms of the reach of our audience and, and their engagement, uh, you know, with, with new products, whether it's, you know, topic chats or spotlight, or, you know, we've, I think we've got two hundred million people playing games every month on Snapchat now. So gaming is becoming, A big part of, of, um, you know, the engagement driver, you know, engagement drivers on Snapchat. And the reason why that's so important is that it's going to be very hard for us to win long-term in specs without a really solid foundation. Um, and so I think we need to demonstrate that, you know, after a couple of years of rebuilding our ad platform, rebuilding our go-to-market efforts can …

AI assessment note: “that's really one of the reasons why I call this year, uh, a crucible moment.”

Q Okay. What are two or three books that you find yourself recommending most to other people?

A Well, you know what I just finished was The First 50 Years of Apple, uh, by David Pogue. I thought it was great. I would recommend the first half, uh, because, you know, he interviews, like, a 150 early Apple team members, and the stories are just great, and there's a lot of learnings in there. Um, so I really enjoyed, I really enjoyed that. I think, uh, what else have I read recently? Uh, there's a, a great book, maybe relevant for this particular moment, called The End of the World is Just the Beginning. Um, which actually touches a lot on the vulnerability of global shipping. Like the global economy is built on global shipping. Um, and it sort of predicts a world where the U.S. is going to have a much harder time securing the global waterways. Uh, and what does that mean for, uh, the way that we build things and organize ourselves as a society?

AI assessment note: “The First 50 Years of Apple... called The End of the World is Just the Beginning”

Q his phone. Just like, I don't even know what the number is anymore. I think people don't give you enough credit for the success that Claude Code has had and co-work and all the things you all are building. Help us understand your role on the team, how you work with Boris, how you split responsibilities, just like what does the PMRO look like on, on the Claude Code team?

A I feel very lucky to work with Boris. He's been an amazing thought partner. He's our tech lead. He's very much the product visionary. And he is great at setting like, this is what the product needs to be. In like three months, six months from now. This is like what the AGI-pilled version of the product is. And a lot of my role is figuring out, okay, what is the path from where we are today to like that vision three to six months from now. And I, I spend more of my time on the cross-functional. So making sure that our marketing team, sales team, finance, capacity, et cetera, are like bought in on the plan and that we're all rowing the same direction and that Once the feature is ready, that there aren't any blockers to shipping it. I think in many ways it works well because we kind of like mind meld, but it is actually like remarkably blurry of a line. Like, I think we're like, 80% mind meld, and then there's like this 20% of things that like, maybe I care a lot more about than Boris, so like I'll drive those, and then like 20% where he cares a lot more than me, and he just like drives those.

AI assessment note: “a lot of my role is figuring out, okay, what is the path”