Reid riffs on GPT-5, Figma's IPO, and the end of AOL dial-up

This week, Reid and Aria discuss the much-anticipated launch of GPT-5, Figma's blockbuster IPO, Perplexity’s bid to acquire Google Chrome, and the end of AOL’s dial-up internet service. Plus, Reid offers his take on why some companies find explosive growth and others fade just as fast. For more info on the podcast and transcripts of all the episodes, visit https://www.possible.fm/podcast/ Select mentions: For the Hamilton v.s. Satoshi Bitcoin Rap Battle: https://reid.medium.com/bitcoin-rap-battle-hamilton-vs-satoshi-de3058b3dff0 The innovator’s dilemma by Clayton Christensen

• 0:00Speaker 00

  I'm Reid Hoffman.

• 0:02Speaker 01

  And I'm Aria Finger.

• 0:03Speaker 00

  We want to know what happens if, in the future, everything breaks humanity's way.

• 0:08Speaker 01

  Typically, we ask our guests for their outlook on the best possible future. But now, every other week, I get to ask Reid for his take.

• 0:18Speaker 00

  This is possible.

• 0:25Speaker 01

  Reid, no surprise, we are going to start off today talking about GPT-5. Our coworker Parth, I don't think, slept for the five days leading up to it. Everyone was so excited to see what's to come. And this was sort of a different release than the previous. People who watched the rollout weren't sort of wowed as much by the technological changes. But what happened is this was an all in one. They deprecated all the previous models that people had come to know and love, but also be made fun of for whether you should be using 3.0 or 4 or the one that thinks or, you know, the one that does all these other things, which I think sort of boggled the minds of some more regular people who were trying to figure out which AI to use. What is just your first take on the GPT-5 launch?

• 1:06Speaker 00

  So this might be a paradox, but I was expecting both a little bit of the blowback and I think the GPT-5 launch is a very good thing ultimately. It's almost akin to, I wonder how many people remember this, when Facebook launched News Feed, there were actually protests outside of Facebook's headquarters.

• 1:25Speaker 01

  I mean, people went truly insane. For people who don't remember, it was crazy.

• 1:29Speaker 00

  Right. And I was like, nope, News Feed's a very good idea. It's a good thing. It will continue. Very quickly, everyone went, oh, I really like this. And so that's kind of a little bit of the parallel in terms of what I think about like GPT-5. I think it's the, when you make these kind of changes where people are familiar with the previous thing, there's a bunch of people who are unhappy about the new thing and want to stay at the old thing, whether it's a change in interface on, you know, your computer or a phone or anything else. And it's like, ah, that's just not better because it's different. And, you know, there are a whole bunch of GPT-5 increases. I think Ethan Mullik, I think, told me the one that I think is the most relevant broadly, which is There's more already intelligent model

• 2:14Speaker 00

  direction. And since most people don't actually know how to choose models well.

• 2:18Speaker 01

  Exactly.

• 2:19Speaker 00

  For which kind of problem and thing they're trying to do. The fact that you have a little bit of AI intelligence on, oh, this one, you should use the more difficult thinking model for doing it. And it doesn't do it all on everything. For example, still with GBD five, like I find myself going and clicking the deep research button to make sure it's doing that. And a little bit of the kind of the fun hack is to put think deeply in your prompt as a way of doing it. Because obviously, to some degree, the intelligence algorithm is also driven by cost for OpenAI. And so it's going to try to get you a good result, but it's going to default to the inferentially cheaper model. I haven't yet seen where the the real question on coding and healthcare is, what

• 3:01Speaker 00

  is the network of thousands to tens of thousands of people and doing it in comparison? Like, I haven't yet seen the the roll up of that. I know that OpenAI believes that it's trained the current best. And I think a lot of people are like, that's just really good. Now, of course, the other part of the GBD five launch was the fact that OpenAI said, hey, we've got our current best models that are there through the service. And then we also made some open source models just to show you that the open source models, we can make ones that are better than anything that's currently out there and enable them and put them out there, I think, has also been a very significantly noteworthy thing.

• 3:38Speaker 01

  I think one thing that's interesting is there's sort of two different directions. One is you want to get the best possible models out there, people on the cutting edge using it. And then you also want really broad adoption. You want people to have good models when they're using the free version. You don't want them to have to think, to your point about, ah, do I click deep research? Do I not? OpenAI, honestly, with this launch seems to be winning on both counts. Why is OpenAI ahead of the other frontier labs on this one?

• 4:03Speaker 00

  Well, the key thing that OpenAI, you know, started very early and they built on some work that was done at Google. This was part of Ilya and Greg and Dario. OpenAI went, we are going fully at scale.

• 4:22Speaker 00

  Right. And we're going to think it's just scale compute with various patterns of learning and scale data, and we're going to apply whatever scale team we need to. And we're going to aggregate that and we're going to go for that. And they started that earlier than even Google, which had created the baseline techniques, but was not as convinced about scale, was not convinced about productization. And so was not as fully into it, even though the the initial side. And then, you know, we're followed by Microsoft in the combination of doing the deal with OpenAI and then learning and doing that. And so they have a the scale path and the learning to how to do the scale path as the advantage. And they continue to

• 5:04Speaker 00

  blitz scale along. I mean, it is, in a sense, a classic Silicon Valley blitzscaling story, which is bet on the fact that the scale version of this is going to really work. So invest in ways that people think you're crazy. Go after scale team. Like, yep, we're going to move from 50 people to 500 people really, really fast. We're going to put all that together. We're going to put that there. Do scale data, right? Which is like, we're going to take data from wherever we can legitimately get it. You know, everywhere on the internet, come and crawl, everything else. We're going to do whatever deals we can. And we're going to be throwing as much data at this. And we're going to be, we're just going to continue to blitz on all of these runs. And what's more, even though

• 5:48Speaker 00

  the chat GPT rollout was a research rollout, was not a launch, once they saw it, they would blitz on the chat GBD deployment as well. And that's part of the reason why OpenAI maintains its lead. And part of, you know, in a baseline, OpenAI's strategy is to say, we're ahead on this scale compute, the deployment, etc. Let's just keep doing that.

• 6:09Speaker 01

  Well, I think one thing that's interesting is, you know, chat GPT seems like such an overnight success. Like you said, they did the research launch and then turned into an actual launch, such like a classic Silicon Valley hockey stick. And I'd say another company that has been in the news recently that has that also classic, you know, nowhere, nowhere, nowhere, nowhere, and then everywhere is Figma. They famously took nearly a decade to go from their MVP. To somewhat mass adoption. And for those of you who don't know, it's sort of the design tool of choice for startups and large enterprises. And they were famously blocked by Adobe's attempted acquisition and they just went public recently, one of the biggest one day gains in the stock market history. And so they're one of those companies that took over 10 years to

• 6:51Speaker 01

  get to a real revenue place. And yet with AI, we're seeing companies go to 100 million ARR in a year or two, like are the figmas of the world, the sort of slow growth until you get mass adoption. Are they the thing of the past? Like, do you have to have revenue immediately in these sort of AI days?

• 7:09Speaker 00

  Well, I think you certainly don't need to have revenue immediately. I mean, that's part of what venture capital and capital markets about, the part of what Silicon Valley has understood in venture capital well before all the rest of the world, like actually, in fact, proving your strategic value in various ways and then potentially getting the revenue. Now, you always have a revenue thought, you know, and you have to get there for long term, but like getting there kind of strategically first, like people don't remember this was early criticisms of Facebook, like, oh, it's great for college students, but it'll never make any money, right? Four years of commentary on Facebook, you know, as an example, and it's multiple through these things. And it's actually understanding that getting to strategic position first as your leading edge where revenue may be trailing. And look, I have a soft spot in my

• 7:54Speaker 00

  heart, not just for Figma, which is awesome, and Dylan and the whole team are great, but also like this whole, oh, it's nothing, it's nothing, it's nothing. Oh, my God, it's everything. You know, to some degree, this is a Greylock VC special, you know, because there's not only Figma, there's LinkedIn, which is very similar, which is dead relevant. Oh, amazing. You know, there's Roblox, you know, oh, trivial little kids thing, trivial little kids thing, oh, major platform. You know, we tend to do this a lot at Greylock and that pattern will continue, right? Now, you want to get to strategic value as soon as possible. And, you know, one of the problems with slow bakes is if someone gets ahead of you on a slow bake, then you could kind of die out in the wilderness and never get to your hockey stick. Now, those of us who have

• 8:38Speaker 00

  been close to Figma, inclusive of myself, inclusive of John Lilly, inclusive of, you know, a number of other people, we knew Figma was awesome. And was coming. And it's partially because it's a product focused, like more and more of the, these things are product focused entrepreneur. And Dylan was an intern at LinkedIn. You know, we've known Dylan a long time. And the notion of that design is the front end, how you work generally across a number of different things is part of it's not just like, it was all just like Adobe. And it's like, well, actually, there's obviously some questions about where you use Adobe and some questions where you use Figma, but it's also a, it's a design approach to collaborative work. And that's the thing that makes Figma, you

• 9:20Speaker 00

  know, kind of interesting. And as, and you know, Dylan's one of those very product founder, true north, choose the thing you're doing. How does it make happen? And so we just couldn't be more delighted for Figma, you know, having its first moment on the public stage with its IPO.

• 9:40Speaker 01

  I mean, Dylan seems truly like one of those founders who's not chasing the latest hot thing, but super smartly integrating AI as appropriate, making sure he's true to this sort of core of designers that they've always served.

• 9:53Speaker 00

  But by the way, one other funny thing to say about Dylan, just because it's like, your question's reminding me of how much I like Dylan. When I did the Bitcoin rap battle, Dylan was one of the people we had in the audience, right?

• 10:03Speaker 01

  Oh, that's awesome.

• 10:04Speaker 00

  Had as part of one of the people doing the reactions to Satoshi versus Hamilton. Anyway.

• 10:09Speaker 01

  We'll make sure to include the link to the Bitcoin rap battle in the show notes because it's amazing, hilarious and prescient, uh, because it was many years ago. So speaking of another sort of hot company, perplexity has this sort of eye popping rise in valuations, at least from 520 million to over 18 billion in, in just over a year. And they also just made headlines with a $34.5 billion offer to acquire Chrome. A lot of people think this is just a marketing stunt. They want to grab attention. What is your read on this offer to acquire Chrome? Is it real or is it just marketing?

• 10:44Speaker 00

  Well, if Google turned around and said, sure, I think perplexity would do it. So it's real in that regard. I think it's not real in the regard that completely speculating as an outsider.

• 10:56Speaker 01

  Sure.

• 10:56Speaker 00

  I think that maybe perplexity might have reached out to Google beforehand before I made a public offer, or might not have, who knows? And I'm pretty sure Google's not interested in this for a whole wide variety of reasons. And, you know, I think that given perplexity is one of the efforts that's trying to compete with Google on what does AI mean for search? Like, I think it would be very low on Google's list.

• 11:20Speaker 01

  And so how does a company like perplexity, which certainly has users and has name recognition and people are talking about it, but they're going up against the behemoths? Like, how do they differentiate? Is it specialization in the long term? Like, what's the long play for them?

• 11:34Speaker 00

  Like, I'm not close enough to perplexity to have a specific answer for perplexity. You know, it's pretty amazing what they've accomplished. You know, it's, it's take risks that the incumbents won't take. It's move fast on various things. It's tried different distribution strategies. It's do product direction that, for example, the incumbents can't really do because they're also servicing their current customers as a way of doing it. You know, it's kind of the classic Christensen innovator's dilemma, which is, you know, initially the thing seems small or less relevant, but you bet right and it grows large. I think all of those things would be naturally things to consider within the perplexity kind of set.

• 12:17Speaker 00

  You know, I did think, by the way, the, the marketing stunt was clever. No, it's a clever move that also, you know, comes at Google's expense. So it's not the kind of thing that, you know, Google's got to be particularly happy about as a stunt, but, you know, all fair.

• 12:31Speaker 01

  Right. Typical incumbent versus entrant, figure out what you can do. So I want to end talking about one of the true OGs in the space. I remember very clearly, I think I was in eighth grade and I made an all-stars with a Z23 I am chat name and it was all the rage among me and my eighth grade friends. And just recently AOL finally Only said no more to the dial up connection that we all know so well. Those of us a certain age can probably even sort of sing the dial up song. So what does this mean for the cycles of technology? Like it was used for 30 years. Do you think these cycles are getting shorter or no? We're, we're still going to see these technology companies being used 30 years into the future, just like AOL was.

• 13:14Speaker 00

  Well, one thing you're entertaining me with, with your particular eighth grade self is back then. The wisdom was anyone who claimed they were a teenage girl was actually a 30 year old man.

• 13:24Speaker 01

  Fair, fair.

• 13:25Speaker 00

  So you were actually one of the actual teenage girls.

• 13:29Speaker 01

  That's correct. That's correct.

• 13:30Speaker 00

  I think the short thing is that people over predict in the new things, the death of the old. Like a classic one is when mobile started growing, people said PCs are over. And what happens is PCs grow, like mobile grows a lot more, but like PCs have continued. Right. And actually, in fact, if you ask me, would they be continuing 10 years from now? The answer is yes, I think they will be because when it fits something that's, that's really useful. It actually continues. It has incumbents. It has a bunch of integrations, like not just in enterprise, but in people's lives and all the rest. As ways of doing this, I myself, as you know, you know, use, of course I'm old. Use PCs and laptops and all the rest more than I use mobile.

• 14:14Speaker 00

  I actually deliberately use mobile somewhat just to be familiar with the experience and to know where that's going. But I think as people begin to use these things for more intensive activities. For example, how many people write their PhD on their mobile device? And it's like, not that many, obviously the mobile device goes with you everywhere. And you go, oh, I can respond to this email right now and all the rest like that. That's part of the whole thing. So that's part of the growth you see. And this is, I think, a very standard part of people's misunderstanding in technology. Like, for example, like one of the memes right now is vibe coding is going to wipe out productivity software. And it's like, well, actually, in fact, what I think you'll see is productivity software will continue. And then vibe coding is going to add on to it and add a bunch, either at a lot or a little, but it's not going to like suddenly like productivity

• 14:59Speaker 00

  software is going to go away.

• 15:00Speaker 01

  Mm hmm.

• 15:01Speaker 00

  Right? And so it's kind of that, that, that's the pattern that people need to understand. Now, partially because we venture capitalists and we public markets, when you look at all the valuation of rails, you're betting on the 10 plus year future in terms of how this stuff plays. And so that's why you go, well, if it's going to grow massively, I want to bet on the things that are growing. So I want to bet on mobile, or I want to bet on maybe vibe coding. And that's the kind of way that this plays out. But it's a very standard pattern that what happens is it persists for a while. And then, by the way, when it dies, it dies very quickly in smaller number of years. And it's mostly because the organization no longer has the economic throw weight to keep it going. It's like, okay, this class of mainframes, there's just not enough revenue. And then that kind of

• 15:45Speaker 00

  mainframe goes away. I'm sure there's probably still some IBM mainframes around somewhere or other, right? But that's the way the death kind of happens. And it's like, okay, the economics around dial up just don't work anymore. So, okay, so there'll still be some smaller ISPs probably doing this in various regions. But generally speaking, everyone's like, ah, like, why use dial up? Let's just try to do other connectivity solutions.

• 16:10Speaker 01

  And to your point, so often, technology just makes the market bigger. It's like, people have been talking about the death of the book forever. And it's like, no, no, no, the book is still with us. We just also have eBooks and audiobooks and websites and mobile sites and, you know, all the rest of it. And so, you know, we'll pour one out for AOL, but it's certainly not the death of the big technology company. Reid, thank you so much. Always a pleasure.

• 16:32Speaker 00

  Yep. Always look forward to next.

• 16:37Speaker 00

  Possible is produced by Wonder Media Network. It's hosted by Aria Finger and me, Reid Hoffman. Our showrunner is Sean Young. Possible is produced by Katie Sanders, Edie Allard, Tanasi Delos, Sarah Schlied, Vanessa Handy, Elia Yates, Paloma Moreno Jimenez, and Mulia Agudelo. Jenny Kaplan is our executive producer and editor.

• 17:00Speaker 01

  Special thanks to Surya Yalamanchili, Saieda Sapieva, Ian Alice, Greg Beato, Parth Patil, and Ben Ralas.