Ex-Twitter CEO's $2B bet on search for AI agents | Parag Agrawal (Founder of Parallel)

And today, he's the founder of Parallel, a multi-billion dollar company backed by Kleiner Perkins and Sequoia. In this conversation, we talk about what drove him to excel in every aspect of his career, his mental models, his operating principles, and the internet of agents he's building for. Knuckle Up. Parag, welcome to the show. Thanks for having me. So, you know, before Twitter, before Parallel, you know, Physics Olympiad, Gold at 17 years of age, top of the CS class at IIT Bombay, Stanford PhD. So you really excelled in every aspect of your career. What were you as a kid? Like, were you always very ambitious and competitive?

I don't think people would have described me as ambitious. People would perhaps early on during middle school, high school would have described me as ambitious. Happy-go-lucky. I think I was competitive towards high school, but I was competitive because I was with a group of friends who were all exceptional. And it's probably driven by curiosity and just wanting to be... Because we found it fun. We found it fun to do math. We found it fun to do physics. And that's sort of what led me to a peer group. And a peer group. I think I give a lot of... I attribute a lot to the people I was around.

Were you looking up to something in those growing up years? Was there Narayan Murthy or somebody like that? Or in the US, somebody that you looked up to? No, no, there wasn't like a...

I've won even back then and even till this date, like I am not the kind of person that like looks up at like role models or idols. Like that's just not my way of visualizing myself or the future. I think it was like much more... Day to day, which is like, oh, we want to go do this, or this problem sounds hard, or I'm with a bunch of friends where we're talking to each other about problems we're solving. You end up in this, getting into IIT, has this entrance exam that is talked about, which requires real amounts of hard work. Turns out, but if you are someone who actually enjoys learning and it's surrounded by many such people who also happen code to be able to do it with perhaps less pain than other people.

And then when you landed in America in 2005, You went to Stanford for your PhD straight away and your plan was to be an academy, right? Plan is probably an overstated word.

I think the journey I was on, like after Physics Olympiad, I went to IIT, started doing computer science, hadn't really done computers before then, right? So I went from math and physics to computers, mostly because the smartest kids went to do computer science at the best institutions. So I was lucky enough to get in, got to be there. As a computer scientist, I was like more of a math person. So I did a fair amount of research during undergrad. So I really... Enjoyed solving hard research problems and I came to Stanford in part because one I wanted to just like it seemed like PhD was the path for me at the time to me because my world wasn't broad enough to fully contemplate every other path.

But I also knew that I didn't want to do the same kind of research I had done during undergrad. So I chose Stanford because it would be a fresh, clean start relative to other institutions I could have gone to where I would continue the same research which I was already doing. At Stanford, it's like, okay, we don't care who you are. Show up and figure, you have the first year to figure out what research you're going to do. And I change fields. My journey is to get more and more applied every step of the way, perhaps a little bit impatient every step of the way. Like during undergrad, I was fine doing like just writing proofs, right?

I wanted to start building things and that started for me during my PhD. And then what made the switch to Twitter happen? Because that feels like a departure from solving math problems to becoming a junior engineer at Twitter.

Yeah, so I think early on in my PhD, I realized that I didn't want to be an academic. But I still enjoyed research. So then my next mental model became to do research but within industry. At the time, there were all of these labs like Microsoft Research, Google Research, Yahoo Research. And so I thought like, okay, maybe you can have it all, right? Maybe you can keep doing research, but also have an impact and do real things. And so through the PhD, through a bulk of the PhD, I thought that is where I wanted to be. But towards the end, I got even more disillusioned with the sort of straddling the boundary of academia where I think like I got disillusioned by the peer feedback loop of other academics judge your work, your output is a published paper of sorts.

Usually it is judged by others who are also not entirely living in the real world, right? And so it felt like a slow feedback loop. It felt like a low signal feedback loop. And I was getting impatient to do things which felt more real and tangible. And so after doing like a lot of summer jobs at every industrial research lab, I gradually came to the realization like you should just like go build stuff. And then So it was a pretty last minute thing. I think even like six months before ending up at Twitter, I would have said that I'm more likely to do research industry than a software engineering job.

And I ended up at Twitter mostly because I was obsessed with the product, right? Like it felt early, but I was like, I was on it. Were you a tweeter also?

Were you a consumer or you were actively tweeting? I was very active. I think working at Twitter made me tweet less over time. But yeah, I was a producer-consumer, heavy-duty person. Prior to starting to work there. And that was a phenomenal run, right?

Like you went from a junior engineer to their first distinguished engineer to the CTO to CEO, if I'm correct. And Twitter also went through a few eras at that time. It started when you joined, it was still, it was a hit company, but still small. Then it became the public town square of the world. How were those early days at Twitter? And how did it evolve in the various CEO journeys before you ended up taking over?

Yeah, so I started as like a junior software engineer. I went there to work for sort of the new ads team. So Twitter was already at the time a product that was starting to work. The biggest problem on the product was bringing in Making it reliable, bringing in enough machines so that it would scale and you wouldn't see the fail well. But on the other side, as the product was scaling, there needed to ultimately be a monetization story. And people started bringing in like a small team to go build that. And that team essentially worked a little bit separate from the rest of the company to an extent.

And I was a part of this early smallish team, which we were really fortunate, like the people who hired me there, like they're now at Parallel. So some people from those teams from that day are now at Parallel. I think it was like a, it felt like a small elite team on a zero to one journey. And so it's not just like working at Twitter, it's working on a, That problem, which was fast moving, that team grew like you would think a rapidly scaling startup grows, right? Like from 10 odd people to hundreds of people in like a year and a half, from running a system on like four computers to 4,000 computers in a year and a half to take revenue from almost nothing to like a couple billion in like two, three years. So...

That journey was particularly rewarding that early couple of years because you get to figure out like, I didn't know how to hire people, right? Like, but I did so many interviews.

Yes, actually, one of the questions I had for you was, who taught you to go from an IC to be a leader, hiring, culture? We'll go into a lot of your operating principles later, but how were those years of learning? Were you bumping into a lot of mistakes and then just learning by yourself? Was there an influence on you?

Of course, right? Like, I think everyone around you influences you. Every problem that you have to solve influences you. I remember, like, it was early enough at Twitter that Twitter was not too organized. So, for example, one of the things I distinctly remember was, like, we needed to hire great people. One fine day, Aish, and, like, in 20, was this 11 or 12? One of those, 11 or 12. Towards the end of the year, I was relatively new. I was, like, the most junior person around. And I had this weird idea that like we should go hire undergrads graduating college in IITs. And there's just like no precedent for it at Twitter.

Twitter used to do like, Twitter had a university recruiting team that went to four universities in the US or something at the time, right? And so I like, I want to go do that, right? And We didn't have a track record of doing video interviews at the time, which today feels weird, but at the time was just true, right? We didn't have too many ways of doing immigrations for people or we didn't have too much precedent of that. But like I literally showed up there and in like six hours of interviews with a bunch of people, hired a bunch, many of whom became really influential engineers over time. But it was pure people Showing initiative and people just going with it to letting you do things that you thought solved the problem of the day which was hiring amazing people ASAP who were extremely talented.

And so in the process though for hiring those, I don't know, we hired maybe five or six people which was like hiring five people in a day. For a small team was a big deal and five amazing people in a day. But we learned how to do video interviews. I was like the recruiting coordinator. I had printed offer letters for everyone because we didn't know who we would hire. And there was some rule that you had to give the offers that same day. But you could do things, right? You could just go, look at a problem and be like, I think this is what I want to do. And you'd be like, let's go. And so that environment...

Is the one that I think you learn in. I think people think that you learn by only making mistakes. I don't think that's true. People think that you learn by only imitating others. I think that's not true. Of course, you have to learn from those things, right? Like you can't repeat every mistake, but you also can't entirely imitate others. But I think if you're given... If you decide to solve something a certain way, it is often more possible than you believe if you just keep following through on it. If you decide to do things, you can make them work.

Yeah. But clearly, you know, that environment was there for everyone to do things. So clearly you still rose through the ranks. When we were talking earlier, you'd mentioned like you were just, you're used to this idea of attacking the problems that you think are hard. What's the reason you were able to rise to the first distinguished engineer, the CTO, the CEO?

No, I think one prerequisite, as I've been saying, in many environments, no matter what you do, that is not a possibility. Right. And so I think in some sense, Twitter of that era was special in that it was a possibility. Number two, I think I got lucky to an extent. Like you need luck for journeys like this always. The thing I, if I look back at like what I did right and like the common element there, I think it was two things. One, I think I always like to be with and around Really capable people who push me to do more and push.

Collectively, you raise your ambition as well as capability simultaneously. Like who are those people with whom that happens? And I don't think I would have described it that way back then. But to me, it's like a feeling that you look for in surrounding yourself with people and problems of that nature. The second thing I think I was both good at and got lucky with is I think I would look at Twitter and what we were doing a little bit from the outside in. I think today I describe it. Again, I wouldn't have described it this way back then. But like I wanted to work on, like you know how every employee at every company sits around thinking like if I was the CEO, we would be doing X, right?

And I had that vibe about me. Saying like, so what do I think? I would try to figure out how to collect the, like how to drive influence, collect the engineers, the PM to be in the place where you could as a tiny group do things that you believed should be happening or would be happening if you were the CEO. But weren't fully happening or weren't getting the attention they deserved.

When you were not yet CEO, what's an example of an initiative you were like, guys, come on, we need to be doing this. And then you just did it.

What was the thing you thought it needed to be? What was that? I think Twitter was already, and I think it's proven today, that the product had durability.

The product needed to scale to more people. And as importantly... The business needed to get stronger, right? So I think I thought Twitter was too large. So we were actually working on making it a better business over time, partly through being a leaner, more agile team. But partly I think there was so much more machine learning, as I would have said it during that time to be done on both the product and On all the issues around content moderation on ads. I don't think Twitter was like as machine learning built even for that day as it could have and should have been. And so I think that was part of the hypothesis in building.

Were there cultural changes also that you felt strongly about? Or did Twitter have a through line in its culture from the days you joined to what it became? No, culture...

I've evolved quite a lot over the years I was there. I think, yeah, I think I, for example, like you asked me earlier, what was the things you did in the first three to six months, right? To shape the company around me, I made a pretty significant sort of changes to the leadership team around me. A lot of it was attributable to me being a different person, needing a different structure, right? Some of it was attributable to me wanting to transform culture. For example, one of the things I did, I think I took the job end of November or something. In December, I asked the team to do, after several years of Twitter not doing it, some amount of employee performance, conversations, management, ratings, whatever you might describe it, right?

Now, these things feel extremely corporate, right? But I think they are a signal on what you value. And it was important to me in part because I wanted to, Twitter had been a place which hadn't for the last several years done serious performance management which goes towards both like letting go of people not performing and empowering and rewarding the top performers. I think there are these two different dimensions. I grew up in an era early on at Twitter. Where I saw both of these things happen. I was at Twitter when we did a round of layoffs. In fact, two rounds of layoffs, right? I experienced what it felt like going in.

I experienced what the company could do after. And those things sort of shaped my view. So I was wanting to drive a culture towards performance. And I think... All of these performance and ratings, processes and systems at scale are extraordinarily flawed. But the one thing they do is they send a signal. Now, all the data that comes out of it is noisy and you have to exercise great amounts of judgment as you use it. But it's really important to change things. And so month one, I decided to do something which is not popular at the time, right? Like not among people, not among managers, not among leadership, right?

But It was popular among some subset of them. And I wanted to empower that subset.

And then towards the end of that stint, maybe the last 6 to 12 months, you also had a pretty, I mean, in some ways, like few operators have felt that kind of pressure, right?

So it does feel, to your point, a lot of moving pieces, but can you actually talk about what's the hardest part you've realized in the years of building now, which you may have even underappreciated when you were getting started on this journey? What's the hardest technical part?

I think the hard technical path is... So one, right? Like you don't... You have a lot of conviction and confidence in agents will use the web at scale. And a lot of it will... Like you can... A few of those things you can take to the bank. And we had conviction. On the details, right? How fast will that happen? Which models? What will... Like I did not have... The foresight to know that coding agents would be dominant in the way that they have been for a period, right? Like I would not have anticipated that. So now as you see these things unfold, you have to be agile around it while being opinionated about the long term.

The second thing that's really hard is that you have to break, to be in this business, you kind of have to break a bunch of rules, right? People will tell you. So we are building a horizontal, Web business for a lot of customers that look very different from each other. We're telling the world that if you are buying models or LLMs, using our search to enhance those tokens makes them more capable, whether you're applying them for finance or legal or insurance underwriting or sales or recruiting or science or You come up with any use case for us, a human in a browser, which is basically everything, right?

We are saying we are building a product that is useful across all of these modalities, right? So now these are very different kind of customers, very different kind of sales, very different kinds of value prop even. In terms of the language you need to use. So building a really horizontal technology layer from day zero instead of ending up there by saying I'm going to go do a vertical and then gradually expand it is a different beast and you kind of have to break a lot of well-trodden startup building advice and pathways to go there and have that ambition.

And Google has the compute, the talent, the background, the index. Why isn't this Google's war to win by a long distance? I think you should invert the question. Okay.

Like, why would it be Google's war to win? As I said, the problem is entirely different. I think anytime there is such a rapid rate of change, my entire hypothesis is why I wanted to be in a small thing is because a rapid rate of change. Favors a smaller Agile thing.

Two, I really think our goal is to allow everyone's agent to be able to have access to the best search and all of the information on the web. Fundamentally, Google's goal is to allow it only for Google. If you are now running a Open model on your hardware and you're running an agent there with your own inference. I want to provide it search. I want to provide it access to everything that anyone else could. And that is fundamentally not any of the larger, better capitalized people's goals, right? So in some sense, how we build our product, the pressures we feel, how we get feedback from the market is entirely different.

From how somebody else does. So then you can ask the question, do I get high fidelity, higher signal feedback? Do I attract better talent as a result of this strategy? There is a right level of, in my opinion, resources and resource constraint relative to the problem you want to solve. And in this case, I get to semi-orchestrate that to create the conditions for the best thing to get built, right? Like Google doesn't exercise any of these things or control. And they're more forced to go with the flow while we get to create the perfect conditions for this to come into being.

So with Google, on your first point also, the Google point, I agree, they're big, starchy, they also have their own, not just bureaucracy, but economy that they've built. But the labs, this is pretty critical infrastructure for the world they are building, you're building. Why wouldn't OpenAI, Anthropic want to own this? It's like central, it's the world they're building, and they are pretty agile, and they are pretty execution-oriented right now.

So one thing I said about Google still applies to labs, right? Like, When they build it, they build it for their models. Yeah, so it's a model agnosticity. So that's one part of it, right? The other part of it is, if you think about what is existential for them, it is the model, the layer above the model. And this is incidental, in my opinion. Not because it's not important, right?

Number two, the mission to democratize all information. Like it doesn't flow from AGI, where you're saying your worldview, world model is I will get a model which can do anything a human does and I will make it so agile that it can deal with every tool that we have built for humans as perfect or imperfect as that might be and I will boil everything into this one thing, right? Our world model is these things are going to be amazing and exist. But there are some tools like web search and the web that instead of making the model be good at attempting this tool, you got to adapt the tool because it's pervasive to the model.

And I think sometimes like the point of view and the worldview collision, if you're right, gives you the edge. So now it boils down to, is our worldview right?

And if our worldview is right, we will premiere. Your thesis relies on the internet remaining an open place. But big giants are trying to be more walled gardens, right? Recently, Amazon with Muse and Instinct is trying to be a walled garden. LinkedIn has always wanted to be a walled garden. We do a lot of recruiting here, so we know how much of a walled garden. We actually use parallel web, so we are a customer. So... Do you feel if the large internet giants end up being walled gardens, that's a problem for Parallel? Or do you think at some point they are forced to flip? There's no way they can remain walled gardens in the world of agents.

So again, I think the word toast is loaded. I think in this new world, we're talking about such a potential expansion of the pie. You can simultaneously keep growing while losing share of market.

In fact, like share of market is like a vague thing to define because the market itself is changing, right? So yeah, can Google, if you think of like today, the web search market, Google commands a hefty market share. Should and can Google command that market share of a future market AI web search market? I would like to think no. Obviously. But can they still grow their business even as this new market comes alive with its own set of events? Yes. So I think you can totally imagine a world where Google with their accumulated capital, talent, technology, culture, momentum, distribution, continues to build an increasingly compelling business while new people like us create entirely new markets where we get to participate and play.

And what we're betting on is like over time, our market, It's bigger than their market.

Yeah. Might have to go through a Microsoft style transformation where, you know, under Satya, Microsoft has gone through a transformation of product to services and GitHub and many other things drive it versus.

I think this world is moving so fast that almost every business will have to undergo transformation. In fact, like between now and four or five years from now, I might have to go through two transformations myself. Even as the new kid on the block with a new potentially agile business, like we like to think way more agile than anyone else we're talking about. In this market, entirely premived on this wave, we will still have to go through transformations.

I want to shift gears towards your operating principles. First of all, how has being a startup CEO been similar and different to being Twitter CEO, public company, a large company? Maybe start with similarities. Today, Parallel is getting bigger. Less, less, 120 maybe.

And it It is post-product market fit on part of our business, right? So I think in the early days of Parallel, it was very, very different. I think now you're starting to see some of the elements show up. But I think the common themes, right, are ultimately most leadership is about having followership, right? Like, no matter what job you're in, if you're in what would be considered a leadership job or role, you're not going to be very effective unless you have your own brand or way of getting followership from people who can collectively do something special. That is at its premise. Common, no matter what you are.

So now the question is, do you need, can the same person be both? And I think we've seen time and again that even if the things that matter might be different, but most entrepreneurs who end up scaling or doing multiple things prove that in different circumstances, there are some common elements and people have many different, there isn't one brand of leadership in the world. Each Every person builds their own way to find people and people who end up finding the right people to collaborate with them in the right time end up doing interesting things. So those things are the same, right? I would say almost everything else is perhaps different.

Right? Like post-product market fit, pre-product market fit. Everyone cares what you do. No one cares what you do. Right? Entirely technical hypothesis, there is no market, no customer. Like what do you do? How you recruit? Who you recruit? Everything is different.

What have you had to unlearn in your own behavioral styles as a leader to recruit? Behave with your team in a technical problem versus a post-product market. What's changed for you as a CEO? I think the early days of parallel were perhaps more natural for me. Like as the technical person among technical people, smart people, some deep conviction in something, world doesn't believe, building something, That felt natural in the zone.

You don't think about things learning or unlearning. You think about learning things. But in that sense, those activities felt easy, natural. I wasn't sitting there like, how do I unlearn things? What I do think is a common theme for how I work is I like doing I think I'm only good and I only like jobs where I think that I'm slightly unqualified for doing that. Like when I took a software engineering job at Twitter after doing a PhD, because I felt like I was underqualified in that moment. Because I had done academic research, I had done prototypes, real software engineering for real systems with real great engineers was a real, it's a challenge.

As I took on every job at Twitter, I felt that someone was taking a bet on me in a way that me in my most rational moment should not, right? And so you only want jobs, in my opinion, that you feel slightly unqualified for because that drives, at least for me, all of the right behaviors, right? Like you are curious. You work that extra bit harder because you're not up to it. You aren't rinsing and repeating a thing. You are there with a curious open mind about like, how do I go tackle this thing? You seek help. From other people or from models. And so to me, that is how I felt in every job at Twitter over time.

Being a founder felt like that to me, right? Like I'm founding a thing. What are you unqualified for now? My current job? Yeah.

Entirely unqualified for like scaling the company. I'm like, Entirely unqualified for scaling an API business for developers and enterprises and growing at rapid scale a large team in a rapidly evolving world. I think anyone who thinks they have been trained for this hasn't been. I think these are fortunate enough that we found ourselves in this unique moment, in this unique position to two. To go on this ride, but like I'm unqualified for almost everything I am supposed to be doing.

As a CEO, are you spending your time these, like how does your week actually look like? Do you have structure around it? Are you one of those who attacks different problems every week and there's not as much structure? Do you have weekly meetings? It has evolved a lot.

Things were very different about six months or a year ago when the team was materially smaller, like a team was grown smaller. Forex this year I want to sync in like 9-10 months. So it's a work in progress, the evolution of me. I do... The core structure of the week that I care about the most is I like seeing engineering demos on Friday evenings. I don't know. It makes... I like to see what is being built or what got built or what got shipped to connect it to some customer value. That I really care about. I spend time on Mondays often with my leadership team mostly because every weekend is a new obsession or journey for me to Like Monday to Friday, I think you're in the operational day-to-day.

And every weekend you take like one step up and come up with what are we missing? What should I be paranoid about? Should we be going and creating a new area of the business? Do I need to go hire somebody with a special skill? Do I need to think about a customer differently? Or market differently. So every weekend you end up in at least my usual goal is to select one obsession from three that are bubbling and try to come up with a conclusion by Monday morning which is either this obsession is not something I should act on which is the right answer half of the time or this obsession Seems worth pursuing that I am going to hand something off to somebody to take it to the next level.

And then I will figure out some way of following up on it. So to me, that is the, my cycle is a little bit around the This weekend. And the rest of the week, we have a company thing where we are in person in the office, in a single office. And everyone is in the same office in product and engineering on Mondays, Wednesdays and Fridays in Palo Alto. People who live in San Francisco go to our San Francisco office on Tuesdays and Thursdays, right? So now my internal time with people, I try to reserve as much as Monday, Wednesday, Friday as possible for that. External stuff to the extent possible, I like to do on Tuesdays and Thursdays.

So there's some natural cadence that gets built as a result, right? Generally, I don't like scheduled, almost no scheduled one-on-ones. No weekly one-on-ones. No one-on-ones with anybody. We're pretty flat. No one-on-ones. We don't have people that need too many one-on-ones. But it's always one-on-ones, right? Like I'm always in the office and anyone walks up and you can have a three-minute conversation about anything. And I... Mostly process things by as I'm walking around the office, I see a face and then I'm reminded of like, oh, there was something that was brewing. Let me go figure this out with this person.

How much of your time are you spending on recruiting now? Recruiting is always a steady amount of time, but then there are periods of intense activity. But is it like 25%? In aggregate, yeah. But I think there are some weeks which will be lower, but certain weeks where there is like one job.

Like I think we've recently, I think now, We in the spring got our amazing head of sales, Graham. Most recently we got our head of marketing, Elaine. Right around then we got head of finance, Agil.

Really amazing people. But each of these are consequential hires. So each of these... You obsess about a lot of heartburn about like, is this the right person? Is this the right thing? A lot of time with the person, but also a lot of time making sure you know what you want. Are you going to set them up right? So recruiting isn't just about the interview, right? Like that is, I think, like a sliver, right? Real mental energy and time goes into all the other things and half of it is done after they show up.

But do you then rely on interviews? Do you rely on backchannel references?

How do you figure out that alpha that you're thinking about this potential is actually there? Did they actually build those weird, exceptionally talented teams? Were they able to manage it? I think we do interviews. We do backchannels.

I am okay at it, I would say, at the hiring moment. On interviewing or back channels or the overall thing?

The decision, right? Like should I hire this extremely high potential engineer? Let's say that's the question.

I think when I go and make that decision, I am okay at it. I think our head of engineering is materially better at it. I am perhaps better at leadership hires. And so I think, but what you have to be, if you're going down this path, Of betting on a lot of potential and moving fast, you have to be willing to admit mistakes and failures. And so I think I am good at admitting to mistakes and letting off people. I think they fundamentally need fixing and to keep a really amazing team, you have to be willing to admit when you've made a mistake and letting people go.

But on the exec hiring, you said you're better. Why are you better? What gives you that edge? Are you looking for something that you've learned to look for better than... Yeah, I think there is...

I think over time, I have at least my interview experience of perhaps perhaps bias towards exec hiring. So I feel more on my feet and grounded. I... I think you fundamentally while hiring execs, there are two things that happen. One, there is more raw data and evidence available in the world about what journey they have been on, which you can elicit from them or from back channels or others they've worked with.

So one good thing is you have more data available. Two, you have to look fast. The outside, whether it be in an interview or in a back channel, to get to the data. There's enough polish, enough experience that you need to look past it. I think I've gotten somewhat okay or better than many at doing those two things on exec hiring. So when there is a data-rich environment, I think I can look past the polish to the raw data and make some extrapolations from there, which I feel grounded on my feet and I feel good and conviction when we hire people.

On exec management then, what are the earliest signals you know that I made a mistake? Because your philosophy includes correcting mistakes. I think it's not hard. I actually think Getting hiring right is extraordinarily hard, right?

Once someone is around you working, we currently work in person, we work with other people, like there can be some gray area, right? But the worst mistakes are very obvious and they're not just obvious to you, they're obvious to everyone around you. And if you've created an environment where you can walk up to an engineer and ask them their opinion, And if you can trust that they'll tell you honestly, again to my point of eliciting information and creating an environment where I can get to the truth, it's not hard. It's just not hard. And so it becomes harder if you create an environment where no one tells you what they think, where no one even acknowledges what they believe, right?

But if you don't create that environment, it's actually very easy. So I don't know, this is just like for us, it just doesn't feel like a hard problem.

How has your role evolved in this AI era? Let's talk about AI native organizations, AI native execs. You were a CEO before AI. How are you using AI for your own life as a CEO, that is? Yeah, it feels amazing, right?

So one, I have over this period sometimes run ahead of AI's capability and for some weekends been in AI psychosis, like many of us, right? And then some like reality brings you back saying like, oh, I thought it worked. So that has happened. I do think, I think the biggest superpower for me, the way I would put it is, listen, as a CEO building a company, you are paranoid about everything. And you kind of, in an ideal world, right? I want to transmit everything. Insight context to my entire team that I have. My convictions about the future. There are so many intricate details in your sort of worldview or details or how I want to show up to every customer interaction or every principle in our API design or technical architecture design.

I have somewhat strong opinions on all of these dimensions which are Kind of upfront, like you can't write it in a book and hand it to people and transmit it. It's just like, I don't know how to do that. You provide higher level frameworks, you provide information, context. But the only way to reinforce those things is to observe things in a moment and then inject your point of view in the right moment, have it be visible to a lot of people so that people can extrapolate from it and Now what does an AI give me? So what I'm fundamentally describing is you go in, give people a lot of autonomy, but occasionally go in and micromanage on specific things.

When you see things, when you either need to reinforce a behavior or you need to micromanage something to tweak and provide more context to find that opportunity and that circumstance. Now AI gives you extraordinary capability. Like I would not be able to keep up with the code being shipped. Now at some high level, I maintain a mental model of what is shipping by having a lot of AI summarized. Even if like 10% of it is misinformation, I have a week on week mental model of what we are building across a high velocity largest team. I have AIs looking at Any visible interactions to call it a gong or slack interactions with our prospective or current customers.

I try to pull out insights from them. I observe what is the way I would like things to be. What are things I want to learn to put on the product roadmap. So it gives me this extraordinary ability to prioritize my attentions and Learn things to know where to go in and tweak something. So I feel like way more control on the thing we're building than I would have in a prior life.

Do you worry also that it's over-information, overkill of information? Because the other side of it is all of us have so many agents these days pushing us more information. Is that happening to you? Not really.

No, listen, your time and attention, mental energy is a constraint. So now earlier I was on a, if the prior is right, like you were getting a random subset of information. Now I'm using AI to prioritize it based on some things I can say. So now I spend enough energy to, so that the AI is curating something better than the random walk I would otherwise be on. Right? So, so I do think For me, AI is by and large a really material thing in how I operate or how I spend my time or what I do with it and what I'm able to do at the company. Be in more details in much more places. Have far fewer meetings which are information gathering oriented.

Have more decision oriented and Influence and steering. Yeah. How does the role of engineers and engineering leadership evolve in this new world?

So one, I don't feel like I can call myself an engineer, right? I think it's evolved rapidly and continues to. I think there are certain things on Engineering, which now AIs are good at. There are certain things where they're a function of how you architect your system so that the AI can be good at it. For example, right, like you would, the biggest change, at least for us is, you know, you think about making engineers productive. And I think every time you scale an engineering organization as the CTO for a while, you think about like, okay, how? How do I make every developer more productive? What are the base things to make every developer more productive?

And there is some maturity curve on that, that historic engine organizations have gone through. In this world of AI, you kind of have to speedrun that curve. Okay, my engineering team of 10, you should actually invest in The developer productivity thinks that you might build for a team of 300. Again, like the real difference is to guard railing for agents versus humans. But like at 300 scale, you start building systems where you're like, okay, one engineer will make a crazy mistake, which is roughly an agent will do something crazy or is more likely to do something crazy. And so to me, that is the biggest way, like more...

Of engineering is to be thought of as scaling engineering and building more of the meta stuff.

Are you seeing people on that curve very rapidly? Because they have to change their mindset, you know, like in terms of the guardrails, engineering productivity and really thinking that this is a team of 300, actually not 10.

I think on our team, we have the right mix. We have... We have parts of the stack when you're building a very large scale crawl and index and these super scaled complex distributed systems where they're very stateful, deploys complex. Like there are these complex pieces, low level, where I think we have failed to make it iterable by a hundred people. Like a hundred people can't iterate on this complex beast. It's just not dev environment doesn't exist, right? So there exists a part of our team which is working on those. Another part of our team is moving really, really fast on iterating on quality.

And so within our team, I think you would say there's some variance in use of tokens, use of AI. And I think that's a healthy thing. Me, I'm in this camp of like the token maxer camp, right? Right. And then there is the responsible camp, which is like, oh, I need to build a reliable system in the presence of these token maxers. So I'm going to go obsess about deploy tests and CI and security and regressions for every customer that exists as the velocity shifts, right? And to go faster, you need to do that work also. So I think we have this team which is doing that. Now, of course, like I think we could be a, like every CEO thinks this, like we could be like 3x better.

We could be 3x better than we are, but that is to work for. So I don't think like we are at the peak performance yet, but I think we're doing all the right things to approach it.

Let's talk about the future of the world, right? Like you're at the center of this AI revolution... Are you in the accelerationist camp? Are you in the Dario camp that, hey, we need to slow this down before, I'm guessing based on your token maxing statement, you probably are in the Jensen camp. But like, yeah, where are you in this cyber attacks are happening?

I don't know if I'm in any camp among those. I am in the camp that, one, I think model capabilities will improve.

I think they will improve whether or not you want them. I think the rate of change is high and will remain high. I think it is likely that the rate of change is going to be disruptive for people. I think those are things that will happen. I don't believe that there should be... I don't think the solution necessarily is... Rushed regulations.

Now, if someone has really thoughtful regulations, I am open-minded. I currently don't know enough to have a hypothesis that great in this moment of change and new technology with unknown and unknowable ways that it plays. I don't think We can have high confidence in any regulation we write. At least I don't know what that would be. So in the absence of seeing, of being persuaded, I believe that Allowing people to build, incentivizing people to solve problems, to help. I believe in the rebel alliance of all the other entrepreneurs to go solve things in a way to, if there is a societal problem, I think people will show up to try to solve it, either for profit or not for profit.

So that is my view. So even the cyber risks that are coming up, you believe will be solved through entrepreneurship on the security side? Yeah, no, I think they are, right?

So, for example, the cyber risks are coming up. You're already seeing, without a law in place, the people building these models, first... Try in whatever way they can. You can be a skeptic about their intentions and whether they're pure or not. But they are trying to prepare the world about the cyber risk. They are trying to get people to find issues and solve them before they become broadly exploitable. They are perhaps compromising their own product experience and use cases. To minimize that risk. And they're trying to find some judgment calls on risk-reward on various dimensions. Which to me is how things should be.

You can't have this rapid change with no potential downside risk. But you're already seeing people feel accountable enough. Now you can say they should do more and you can have a reasonable disagreement. Let me steal that just for the debate. Bad technologies have existed forever.

All technology can be used for good and bad. So guns are regulated, but even driving is regulated. You have to have a license. You can't be drunk and driving. So why shouldn't there be more regulation here? I'm not saying there shouldn't be. I am saying that a lot of Regulation has intended effects and unintended effects. And at least my lived experience is there exists a reasonable class of regulations, especially around technology, that tend to Have negative and unintended effects. So now I'm not saying no to all regulation. I am saying the burden of proof is on the specific regulatory framework we use and how we make sure that it is very likely to have the desired effects and not the undesirable risks.

To me that is the burden of proof and the proposals that you see Out and about. To me, don't meet that burden. That's what I'm saying.

What do you think about the social upheaval that might be coming from a jobs perspective? I know it's a speculative question, but where is your heart and mind right now in 5 years, 10 years? Do you believe software engineering jobs go away or does it just evolve? Is there social upheaval coming or people just need to upgrade their skill sets or change their skill sets?

I think if this change was happening slowly, I would have taken a, I'm a tech optimist and I'm an optimist in our ability as people in society to evolve. That is my baseline point of view. In this moment, the rate of change and the potential rate of change feels high enough that I don't feel the optimist conviction that To sit here and tell you that like, oh, there is like, society will evolve around this technology and everything will be great. Like, I don't feel that way. I think the delta between the AI diffusion is like very uneven right now.

Like, we kind of here in San Francisco live in like a weird bubble where you're surrounded by people who live in the bubble. And kind of believe more in AI. And when you pop out of the bubble, the world is different. Then you go even further, the world is very different. So I don't know. I feel the rate of change is high enough that there is a... I think in the long arc, society will evolve. But along the way, there are likely to be hard periods. And yeah, so I worry about that. I don't have... Meaningful, Constructive solutions other than the piece of advice that I would give myself which is adapt as fast as humanly possible to the world around you.

So try to assume that there is going to be this large continued rate of change and try really hard to Adapt alongside it and bring the people around you and help others adapt too.

Do you believe the number of software jobs in 5 to 10 years will be dramatically less?

I don't know how to define a software job in 5 to 10 years. I think the jobs will look different. I also think like I'm in the extreme positive sum game. So I think there will be way more... Value creation as a result of what you might define, the TAM will be much larger. That I believe. The economy around this will be much larger. Now, how many people will do that? I don't really know. Right? So, in aggregate, the economy around this will be much, much, much larger. Now the question is, will it take way more people to support that large economy? Will it take the same number of people? Will it be like regular growth like we've seen over many decades?

Will it be shrinkage? I honestly don't have a framework to know. How are you guiding your own kids for the skills that will be relevant for them in years to come? For you, the curiosity, the math skills really panned out well. Yeah, but I think those...

Listen, it's not hard to believe that you will need hard work in the future. You will need curiosity in the future. You will need to communicate with the world and other people and models. So those baseline things are the same. I think you, at least I feel that as a parent, you have a role to play in those. You have a role to play in creating the environment and their peer group. But I don't think... It's up to me to really decide what they pursue or what catches their fancy at what age. And I think I have evolved from being happy-go-lucky to math, to physics, to computer science, to software engineering, to leadership, to founders.

It's like these are arcs, various times, different things. Kids will evolve, right? Like in middle school, you'll have different interests. In high school, it could evolve. Over time, it could evolve. Who knows what college will be by the time they're there. But should they be curious? I want to make it so. Should they enjoy sport and athletics? Yes. Should they enjoy teamwork in some of those pursuits? Yes. Should they work hard? Yes. Should they enjoy music? I hope so. Or art or something else? Yes. So these are like not complicated things. And these are essentially all you as a parent get to play around with anyways, right?

But I do think one thing I really feel great like is my kids appear to be hardworking. They probably get that from my wife.

So last question for you, a young person watching this wants your life, wants the life that you've built. What would you tell them that this journey actually requires? Hard work. A great peer group.

Getting lucky with your, with a lot of things, including family, choosing the right spouse.

And only working and getting lucky enough to only get to work on things that you really enjoy. That's not a privilege you can take for granted. But I've gotten a bunch of the ingredients right and made a few good decisions which are consequential. That's what it takes. Parag, this was amazing. Thank you so much for coming on. Thank you. [music]