The Venture Capitalist Who Finds the Best AI Products—Before They Win - Ep. 45 with Nabeel Hyatt

[00:00] Rory Sutherland says there's like [00:01] three types of innovation. There's faster horses, and then there's teleportation. Like, you want it to exist. You don't know how to get there. But if I tell you you want teleportation, you want teleportation. Everybody wants teleportation. And then there's, like, Japanese toilets. For me, the things I'm, like, wandering around and trying to find are the Japanese toilets of AI. I am looking for, mostly, new experiences, things that surprise you with the place that they're playing. [00:31] Thank you. [00:38] Hey, it's Dan. We're going to get to the episode in a moment, but I wanted to share with you one thing before we do. I think that writing is the most important skill in the AI age. Now that you can code in English, the line between a writer and a builder is blurring. And I think in a world like that, the most important thing you can learn to do, no matter what your job is, is learn to tell great stories. [01:08] know to write incredible things with AI. We go through all the latest technology, including ChatGPT, Claude, and some of our internal incubations like Spiral and Lex to give you a powerful toolkit to tell amazing stories. The course starts February 13th, and Early Bird Access ends this Friday, January 24th. So if you want to save $300 off list price, grab your spot at writewithai.xyz. And now, on to the episode. Nabil, welcome to the show.

[01:32] Good to be here. So for people who don't know, you are a partner at Spark Capital. That's right. You've made a bunch of impressive investments, including in Cruise, Discord. A very recent one is Granola. And before we started, you said something which I didn't know about you, which is your investing strategy is not prolific. You only do a couple a year. Why is that? [01:55] First of all, I just think that – so I was a founder before. [01:59] becoming an investor. Um, and I found that I had no horror venture capital stories that sometimes investors have, or entrepreneurs have, um, um, [02:10] But I also basically had a bunch of no-ops. I had investors that were fine and great board members and maybe offered a random piece of advice, but weren't in the muck enough and in the nuance enough to give good feedback because they were investing in 15,000 things. What does no-ops stand for? Oh. No opposition? Yeah. Like they were – Just do it every once. They were just fine. It was like they're no damage. I don't have a horror story. Did no harm. [02:40] not there, probably. And I just [02:44] There's a thing on our website that I think we collectively believe at Spark, which is that there aren't really any startup playbooks. I think as a founder, you're doing something super unique with every, so you probably already believe there's really no playbook for what you're trying to do. But generally, every single journey is unique and all the devil's in the details. And so I think for me, the proxy is if you're a startup CEO or running a small org, you can manage eight or nine direct reports together.

[03:13] where you kind of understand everything they're doing. And outside of that, [03:18] It starts to, the edges get fuzzy. [03:20] And it's just the same thing. Like I want to work with eight or nine or 10 companies really closely as much as a founder really wants me around. And I'll go away if it's not. And so you try and make the rest of the math work. Yeah. And like construct life about the way you want to live and then see if you can make it work versus letting somebody's financial or business model force you into working the way you don't want to work. I like that. I mean, I think it's it takes some balls. [03:45] Um, it's better than like, like, I think obviously the sort of spray and pray, like small checks into a lot of things like that. That's a, a, a well trod strategy. Um, but I think, uh, uh, taking enough risk to be concentrated and to, uh, uh, actually call your shot is, I think it's, I think it's quite cool. Well, it's not even spray and pray, even on, on the front end. I mean, basically the whole venture capital industry, since I joined, I've been to this for over a decade now, [04:15] spectrum, right? You've got the, I'm going to write a hundred K checks into a million things. And then you have the, well, if I raise a hundred billion dollars, then I can own a proxy of the whole market firms, which is like a lot of our peers that started there on the same time we did. That's been their strategy to mitigate risk over time. And I'm like, look, the whole point of this thing is risk, like accept the risk and like, go do the work you want to do with good people. That is interesting. Something about what you said about doing something unique,

[04:45] um [04:46] I feel like I've been grasping for words for how to describe whatever it is for, for a while recently. Yeah. And I think that that's a really interesting place to be because, um, [04:57] like we're doing something that's working and there isn't yet a word for it. The closest thing I've come up with is, um, multimodal media company. [05:06] - Right. - And-- - Wait, what was the other idea you had a little while ago that was not good? - Malleable media, metamedia, multimodal media is my-- - I like multimodal media. - But there's a lot of M's in it, which is a problem. So like, it's multimodal publishing maybe, I don't know. We're working on it. But like the point is we publish writing, we publish videos, we publish podcasts, and we publish software. - But that's of the time, right? Publishing software, [05:32] is a lot closer to publishing articles than, [05:34] in 2025 than it was 10 years ago, right? And that's new, you're newly able to do that, right? Yeah. So like there's, so there's not really a word for it. So I'm trying to like figure that out, but there's this interesting thing where like, [05:46] Um, I'm like, I'm realizing that working on something that I don't have a word for is actually like really valuable and really cool, especially because it's starting to work. But then there's also, um, this, this trap that I think you can get into sometimes. And I've definitely fallen into this too, where it's like, you think you don't have a word for it, but there is actually a word and it's been done a lot before. And you, you can't, you can't fool yourself. Do you have an exact example of that in your head?

[06:16] example, uh, but like, I don't know when we started every, for example, um, um, [06:21] we were like, oh, like this kind of media company has never been done before. We wanted to be a bundle of different newsletters. And it's like, it's a magazine. A bundle of newsletters is a magazine. It's a magazine. And so like, and yeah, there were some things that were different about it. But like about a year or two in, we realized that all of the complexity that we had built into the model, like didn't need to be there. And it was just like, it was just a newsletter basically. And the way the newsletter worked was sort of like a magazine. [06:51] is like, of course it proxies to something that's preexisting. Of course it proxies something. But if you then adhere, once you, did something change in you when you start calling it a newsletter? Because that's also a trap. Like the early days of, we were an early investor in Postmates and back in this on-demand land, you had Postmates and Uber and DoorDash and Lyft and, and. [07:12] The Twitterati looks at that and is like, that's just a delivery company. That's the same thing as a taxi company. And yet if those founders had internalized that and just been like, yeah, we're just a taxi company, you just wouldn't have done that. [07:27] Like you wouldn't have done any of the things. [07:30] that you ended up doing over time. And so I don't know. I think definitions really matter if you're doing something new, which I think you are trying to grasp for something new right now. I would find the weird words that are capturing that essence inside of you, right? I think for me, actually calling us a newsletter was quite freeing.

[07:52] Okay. Because it was like, [07:55] We were doing all this complicated stuff to not just be a newsletter. And then once we just, like, dropped it and it was just like, no, it's just a newsletter and, like, it's a bunch of creative people writing stuff and, like, we're going to do interesting stuff. We just, you know, we don't know what it is yet. But for now, we're just going to write because that's what we love to do. That was, like, that was really helpful because I think – [08:14] What's been quite important for me entrepreneurially is to [08:19] Um, [08:20] you [08:20] start to be really comfortable with like whatever it is that I authentically believe and want to do as opposed to like triangulating between like what I believe and what I think will sound okay. And like what I think I can justify basically. Um, and, and I think like being able to say, no, it's a newsletter and I'm like going to write a lot, uh, is like, was an expression of that. It's like, that's what I want to do. And everything else has like flowed from that. And then we found some new stuff that we're doing that is like, oh, I can't really describe what [08:50] and I'm like really excited. It's so fun. [08:53] So yeah, obviously like in entrepreneurship in general, like there are no hard and fast rules. Like sometimes you don't want to call yourself a newsletter because like that ruins the like, you want to find the magical thing, but you don't want to like force it. Yeah. The irony of this conversation is like what you're doing to find what you really want to do [09:09] is a little bit rooted in the past, but also this awkward new thing you're now trying to describe. And then, like, what I found that I really want to do is also anachronistic, but because it's the old way venture capital used to be. Like, I just want to invest in a handful of companies, work really close to those founders in a smallish firm where I trust my partners. We all work together on something. You know, there's only seven of us on the venture team at Spark.

[09:32] That was how Sequoia was 40 years ago and it worked well. It's just not the way people are building firms today. Yeah. What does that like do like now that the ecosystem is like these gigantic mega funds that look at like seed investing as like loss leaders for like big growth rounds? You know, like how are you thinking about how that changes or it seems like it doesn't really change what you're doing. But like how does it affect your approach? [09:57] Hmm. Um... [09:59] I think an important start of this is we're still good citizens with all of these players as well, right? You end up co-investing with people. I really wanted you to shit on them. I know. I was like, I must hold back slightly from – [10:18] It is not a... [10:19] I think those firms are a viable strategy. [10:23] I think they are a different product. [10:27] And as long as a founder understands what product they're buying – [10:31] then I'm super happy with all of them existing in the ecosystem. I think the things that make me frustrated is when I'm in a conversation with [10:40] Sometimes it's with a current founder. Like, I'm on the board of this company. They're going out to raise. So never mind, I'm competing with them. Like, they're going out to raise a Series B or a Series C. [10:47] and [10:48] And the stories they're being told by investors about what the product is – [10:54] Without going through the whole... It's just, like, not entirely... [10:58] Truth. You cannot be investing. [11:02] Five times a month.

[11:03] and operating out of a $10 billion fund and, um, [11:07] get anything more than a random phone call every four years on a thing. [11:12] And there are firms that are very good at being transparent about what that – this is a transactional relationship. You get the money and you run away. I think actually Founders Fund is very good at being very honest. Yeah. [11:22] about this. And there's lots of people that do a lot of storying around what they're selling. So as long as people know what they're buying and what they're selling, it's fine. We sell a different thing. [11:30] And some founders, that's really important and it's wonderful and they want that process and some don't. You have a connection, a kismet with anybody or you don't and we work on those things. That makes sense. Well, I want to talk about like one of your latest investments, which is Granola, which is one of my favorite AI products. And I think it's becoming one of everybody's favorite AI products. We've had Chris on the podcast. Chris read an article for Every You that did really well. It's like really amazing stuff. I think he's super talented. What did you see in that? [12:00] when you invested. [12:02] Well, um... [12:04] When did you invest? Like, was it before they had the product they have now or is it after? [12:08] So I've known Chris for over a decade. Chris was a founder of a company called Socratic back in the day, kind of like previous AI generation. And that was actually a Spark portfolio company. And so he's been part of the family for a really long time. And – [12:27] His first attempt at making this was, as he'll talk about now, was a little bit of a misfire. So he got to notes as a canonical thing that you can work on. But it was very interruptive, and the use flow without going through it all was…

[12:43] It just wasn't the thing. It was like the place to play but not the thing. And so I hung out with him much at Seed. We played and talked about product and looked at early prototypes and so on and so forth. [12:53] For us, it just wasn't over the line, and so he did raise a seed from somewhere else. And then we just – you connect with certain people, and so we just kept in touch. And then probably about four or five, six months, something like that, after the seed, he stumbled into what is now granola. Yeah. [13:09] as soon as you play with that, [13:11] If you have any taste or product sense, you're like, oh, this is the thing. Yeah, this is great. Let's go. And so we then catalyzed around really quickly at that point. And that was a big round, right? [13:25] I don't know what big is. It was like $20 million, right? Yeah. [13:30] That's pretty big. Yeah. It was the thing that felt so unique. [13:36] and I know you're somebody that, like, I listen to your podcast, we've caught up a bunch, I know you're somebody that struggles with it as well, is like, [13:41] There's a – [13:43] Thank you. [13:44] I don't know. Rory Sutherland says there's like three types of innovation in his like canonical way of talking about the world, which is like there's there's faster horses and there's like. [13:54] Which is like obviously like just make the thing go faster. And then there's teleportation, which is like this thing that you don't know should – like you want it to exist. You don't know how to get there. But if I tell you you want teleportation, you want teleportation. Everybody wants teleportation. Should we have a colony on Mars? It would be awesome. Like I don't know how we're going to do that. And then there's like Japanese toilets.

[14:16] Which is like nobody – you didn't know – I was like where is this going? You didn't know you needed Japanese toilets in your life until the first time you go to Japan. [14:24] You walk out of the toilet, you're like, why isn't this everywhere? - I've been missing this my whole life. - My whole life. And it's not even that complicated. And that's granola. - Yeah, yeah. - Like, it's this thing that's not like, the execution is actually really subtle, it's really hard. But I think for me, the things I'm like, wandering around and trying to find are the Japanese toilets of AI. Like, like, the faster horses are mostly what's getting funded. It's mostly what's come out of this like, [14:51] B2B SaaS [14:53] you know, big industrial machine that we have in venture capital is churning out startups after startups and incubator after incubator. And most of that stuff is like fine. And it'll also be arbitraged out of existence in like four years. And who cares? And so mostly you're looking for new – I am looking for mostly new experiences, things that surprise you with the place that they're playing. And like so for me when I use Granola, you're like, oh, this is – [15:22] So intuitive. It's like the 50th thousandth AI note taker. Like, did the world need another AI note taker? It's like, yes, except I didn't want to use any of those other AI note takers. When Fireflies joins my Zoom meeting, I never let it in. Oh, the anger. I never let it in. The immediate anger.

[15:40] Yeah. And whereas this is just like, no, no, it just basically looks like Apple Notes. And it's just going to like append a little extra to the things that you took notes on and make you a little smarter along the way. [15:52] Yeah, it's brilliant. How do you think you become someone who makes a Japanese toilet? [15:57] Mm hmm. You know, like versus a faster horse, you know, like there's something I was talking to Chris about this, like something about like the way that he looks at or thinks about the soul of a product and the way his intuition works and all that kind of stuff. And I'm kind of curious. [16:11] I assume you've invested in other people that have that same kind of archetype. Like, what have you learned about that? [16:17] There's a similar journey to Andrew Mason Descript. There's a similar journey to an investment that was just announced recently called WordWare. They have a similar milieu, which is very different from – [16:34] I would say Kyle Vogt at Cruise, that's an example. That's a teleportation pitch. That's like self-driving cars, amazing. Probably impossible. Can you do it? That's a very different kind of pitch. What are the habits of those kinds of founders or what are the journeys that they're on? I would say that – [16:54] The remarkable thing that comes out about a person like that is, [16:57] Usually... [16:58] comes out when they're talking about how they got to whatever solution they [17:03] that they're talking about. [17:05] Um... [17:08] I don't yeah I'm trying to like what is the right answer here.

[17:13] What's the authentic answer here? [17:15] Why is Chris or Andrew really special? [17:20] I'm trying to think about this through the lens of when those kinds of founders come into our firm – [17:27] You can feel it in the room. It's not just me, like the whole team. And this is partially because we cast for these types of people, but like the whole firm, like, [17:36] rallies pretty quickly. [17:38] And so what are the patterns in that pitch? It's usually [17:42] that they are telling you insightful reasons [17:47] why they put things into the product that you would have never normally thought of from customer development calls. [17:54] So it's like some combination of like storytelling and... [17:58] attention to small details in a way that like levels up into something that [18:02] makes all, all make sense together. Yeah. There's some, uh, yeah, there's some connectivity, uh, [18:08] Between the choices a person made in the product that like you can feel and some insight about a customer. [18:16] Like they're listening very, very closely to the behavior of what's happening. And so in Chris's case, it's just noticing, for instance, the very first version of Granola was a tab complete, almost like Copilot, right? So you type a couple words in and you type tab and it starts filling out. [18:32] Seems actually kind of magical when you first look at it. [18:36] It's like – but if you just like listen to yourself closer, if you're self-aware enough closer, especially if you're the user of the product and you're your own customer, you realize like, oh, I'm kind of like super distracted in this meeting because every time I press tab, like it fills out things and it makes an error and then I want to correct the error and now I'm not paying attention. I'm not making eye contact. It's like not why I'm on this Zoom call. Like it's that. And so that little –

[18:58] I don't even – it's not brilliance. [19:00] It's not even creativity in the like canonical definition of creativity where you come up with 15,000 ideas. And it's more like – [19:11] investigation or like a word that's coming to mind is like sensitivity and [19:16] like you're sensitive to what's actually going on. You're like got your hands like all in the, [19:21] In the milieu and you can kind of like feel the changes in the weather patterns or something like that. Yep. Yeah. It's like the the spectrum on scale is like how kinetic how much kinetic energy do you have? [19:35] Because you have to move very fast. [19:37] But we all know people that like are just all horsepower. Like they are just kinetic energy. They're the people that are like, I want to start a startup. And the way I'm going to start a startup is I'm going to come up with a new business plan every single day for the next three months until I find the right thing. And I'm going to push it through like that. [19:53] And that's good kinetic energy without a lot of sensitivity. They're trying to plow through the problem. [20:00] They are very, very uncomfortable with fog of war. [20:04] with like wandering in the wilderness to find the thing. So the opposite spectrum is sensitivity. [20:10] And [20:11] And... [20:12] The problem is that sometimes if you go too far in the sensitivity side, then you're the artiste who is just like has absolute like analysis paralysis. You just think and think and think and think and think and think and think and think and think and think and think and think and it's just too slow. Your iteration cycle is too slow. And again, you're trying to solve by listening closely that fog of war. Like you're trying to just listen to every single animal in the forest to figure out how to track it before you walk in. And so it's this like I think those types of founders you're trying to sense for are –

[20:41] They have a pronation to movement. They will move, but they will move while still listening. [20:48] I love that. That's beautiful. [20:53] Tell me about WordWare, because I have a feeling that there's something very spiritually aligned between WordWare and whatever it is that I'm doing. Really? Yeah. So I'm not diving into WordWare until you start answering that. Like, what do you mean? Well, I've been thinking a lot about, like, okay, what does it mean to be like a multimodal publishing company, media company, like that kind of thing? And the way that I've been thinking about it is – [21:17] Um, [21:18] As you can start to code in English, writing is building. [21:27] I think the opposite is true. Like, uh, building becomes, uh, like in, like at every, it informs all of the writing that we do. So there's a sort of sort of feedback loop and, and, and usually in most organizations you have builders over here and writers over here, or they're in totally separate organizations. And at every there, there's a lot, a lot, a lot of overlap because all of our, all of our EARs, everyone that works at every, they write articles. They don't just write articles. They write code by like writing prompts. [21:57] I have to like... [21:58] pull on that thread a little bit, like, [22:01] The commonality is writing, but underneath that is storytelling, having a perspective and bringing a perspective to the medium or the craft, the thing that you're doing, whether that's the output is actually writing, whether it's podcasts, whether it's building. And so that's the unifying thing between all of the different parts of the organization and something about wordware, the way it's phrased, just expresses that really cleanly.

[22:31] Um... [22:32] It's certainly trying to put people in the role... [22:36] It's trying to open up – WordWare is certainly trying to open up the idea that everybody is a maker and that you should – [22:42] It's still really frustrating to me [22:44] that [22:45] And I'm sure you bump into this a lot. Like, [22:47] And nobody is using Cursor and Windsurf and Replit Agents and Claude for Code and all of these things. Like I had a random – [23:00] Look, during lunch today, I made an app. Like I had 15 minutes and I was like somebody had tweeted out a couple of days ago the right way to structure O1 prompts. And I was like, you probably saw this tweet, right? Seems great. So I took a whole article on that and I just shoved it into a Replit agent. And I was like, here's your PRD. Make me an app so that I can just write here and then pitch the cloud to give me back an expanded product. Took 15 minutes. It was like while I was waiting for my next call. [23:30] Like that's nothing that would even pass through my head a year ago. That's the thing is like writing is building, but software is now content. [23:38] So one of the really cool things is like when we just launched this app called Quora and like that has 10,000 people on the wait list. Those are all now every subscribers. Like you can't like write an article that's going to like get you 10,000 new subscribers. But you can write software that does it. And that's like – that's incredible. But yeah, I interrupted you.

[23:59] The vast majority of people, just simply if you sit down and show them – [24:06] Reflit Agents, which is a great, brilliant product. McKellie's amazing. I've never used it, actually. I used Reflit a lot, like a year ago-ish, but I have not used their new Agents stuff. How do you compare it to a Cursor Composer or a Windsurf? [24:21] I think it's in the same category. These are direct competitors. I would put – if you put a spectrum – [24:30] on coding agents, and we're going to come back to WordWare, because this will link back in. But I can keep these all in my head. If you put a spectrum on all the coding agents today, [24:38] The spectrum I would put on them is basically like how long are they allowed to work before they ask for feedback. And so if we're starting at the low end, you have like Microsoft Copilot, which is trying to finish one line of code. And on the other end of the spectrum, you have Devin, which is trying to run away for four hours. That's a great spectrum. And I actually think when I talk to people today, when we're going through product sessions and I'm working with teams about this, on whatever they're trying to innovate on, that's the spectrum I first start from, which is like, hey, [25:08] for whatever problem you're trying to solve, let's try and think about what is the reasoning of our current SOTA models. [25:14] Let's think about how long do you think you can leave them? How good are your evals internally? Because if you can evaluate longer and better and how good the code base is, you can let it work for longer. So how good are your evals internally? And then let's set a mark. Are you letting this thing go for an hour, four hours, three days, one sentence, 16 seconds based on whatever you're trying to solve? And that's a really interesting new heuristic. I found a couple of different product innovations from startups I'm working with come out of literally just that thought exercise.

[25:44] So I would say – [25:46] The interesting thing about Replit is it generally works far less than Devon, [25:52] which I think we found Devin, for most people, they find Devin to be like, it breaks a lot. Yeah. It's a little slow. It's a little slow. Like it will be an amazing product over time. They've made a long bet. But right now, they probably set the mark a little bit too long on how long they go. I find for me, [26:08] Replit agents... [26:10] Even though the models probably aren't as smart and so on and so forth, the kind of like time variance they give before they come back and ask questions is like a – [26:19] A little bit longer than Windsurf, a little bit shorter than some others. Like they just set the right – Michele, who's the head of AI there, now president, just did a great job setting a variance. And really that sounds simple. They do a bunch of really other good things about the product that we're good right now. Just literally that, setting the right altitude of reasoning is everything for getting really good results out of it. Because they're all using – well, most all of them are using Cloud at the back end anyway. [26:49] Thank you. [26:49] Like it's all cloud. They're great. We're an investor in Anthropic. Love it. Build more things on top of cloud. [26:55] So I'm going to loop that back to Wordware. Yeah, please. [26:58] So wordware is starting from a different orthogonal, which is what do I have to give this thing for it to be able to understand what I really mean? Right. [27:09] And it turns out if you open up [27:12] I don't know. [27:13] windsurf or if you open up cursor or if you open up replete agents it's a chat bot like it looks like a chat window and so what is the normal thing that a

[27:22] person who doesn't talk to chat TPT or Claude all day long, like you and me do, they type in one person. [27:27] three sentences, two sentences, which is like plenty, just enough room for a model to hang itself. Yeah. Yeah. [27:35] Right. Like it's exactly the wrong amount of information to give a model to go then code and make a bunch of things. That's the thing is like, I find with like the Windsor for or Kershers of the world, like the agent experience, um, is, [27:50] It will just start. [27:52] without like, I kind of wanted to start in a like, [27:56] Uh, we're going to define together a little bit more precisely what I actually mean before you start coding, but it just really just starts the code. I'm like, I often like at the end of the initial prompt, I'm like, if anything's unclear, like ask me questions before, which helps. But, um, my other very common prompt there is give me five ways to solve this. Oh, interesting. Are you like, I would say every second or third prompt into one of these coding agencies, [28:22] give me five options so that it doesn't run ahead. And so is WordWare like, is it like a Google Docs instead where it's like a big empty sheet of space? Yeah. And then does it like prompt you with how to fill that in? Like is there some sort of – Yeah, it is working on that as a second stage right now. Right now the way it approaches you – I would say the first big trick it does that's very simple is by approaching with a blank doc – [28:51] And maybe there's a commonality between Descript and Wordware and Granola that I think Blink. You just love the Blank page.

[29:02] There's something about a Blank page, man, that then AI helps you fill out. [29:08] But Wordware, just literally the conceit of… [29:12] Please just write down in plain English the way that you would maybe write a long email to an engineer on your team what you want built. Let's start with that. You can already imagine. Your brain can do all of the things that WordWare is going to do over time, which is right now you have to do at symbols to call different functions and say which inputs and outputs you want. And honestly, WordWare and the founders would say this. It's like a little overly technical today. [29:42] and this is why they're seeing so many people use it right now, is that – [29:46] Once you have that blank page filled, it's pretty easy to learn the syntax of how to use WordWare, how to call certain functions, how to fill it out, and how to really build a usable product. And is it intended for programmers or is it intended for PMs who are sort of like – they took a coding class in college or is it intended for – [30:04] 18 year old who's never coded before and is just like, I want to get. I would say today's level of functionality is very good for somebody who is just slightly technical. I don't think you need to have. [30:15] Been a coder, but it is better if you understand what an input is. Yeah. [30:19] and an output is, and you think in if-then statements just a little bit, like that's going to help you an awful lot. [30:24] That stuff gets glossed over time pretty easily. Going back to that spectrum that we were talking about, like the agentic spectrum, which it sort of reminds me of – you know those dogs that – like the dog leashes that like they extend out? It's like how much leash do you want? How much leash do you want?

[30:42] How do you find the right setting? [30:43] Like, are you just trying different things or, yeah, how are you when you're working with people or what are you finding for people? How do they find that sweet spot? Oh, isn't that the wonderful journey that we're all on with AI? Is that changes like every quarter? [31:00] Like I have a company right now that will go nameless because they're about to release a pretty awesome new thing that actually had an aha moment relatively recently about this, that they've been in AI for a while. They're doing really well. [31:13] But they realized, like, that it's a short leash product. And they kind of had the epiphany a month and a half ago, like, oh, these models are good enough that if we just stitch them slightly differently, what would a longer leash product version? And it's like – and it's not – I say just longer leash. It's not just that it thinks differently. It's like, oh, that makes different demands of the UI and the UX. Like, it just is a different thing. It flows into everything. It's like a whole flow is a different flow, and it will feel like a different product. So you got to – I mean, if you are – Try it out. See if it works. And then, like, in three months when a new model comes out, like, try again. [31:43] aren't reevaluating how would I destroy my own startup six months later every six months right now during this like Cambrian explosion of stuff like that like that's the way you have to navigate things today have you gotten a three yet uh I do not have oh three we have somebody on the team what is what do they say what are the early uh early signs that is not that is not that is not that is not a conversation we're having [32:07] Okay. [32:09] I had to try. Not my place. I had to try. Okay.

[32:14] And then – and I know you're playing around with – so you're doing a lot of – [32:20] working with these sort of like coding agents and, and, and thinking a lot about agentic workflows, like what else are you learning or what else are you excited about in, in that whole space? [32:28] Well, the first thing that I've noticed in my own behavior over the last six months, and this is definitely how you're running every, is like – [32:35] because [32:37] We can code so quickly and make so quickly. We just make so much more. Like I am – [32:43] simultaneously working harder on Spark than I've ever worked and also – [32:48] I'm building a... [32:49] card game with my kids um i'm also opening a board game library with a handful of friends like it's not just code like like i'm opening a freaking retail space we'll see if that works at all that's amazing for for board games for the board yeah for board games a private library it's called tabletop library it's a private library for people who play board games together where is it in berkeley of course it is it's actually it's on a block in berkeley the other [33:19] bookstore and a comic book store. It's like the nerdiest block in America. That's the best. Do you live in Berkeley? I live in Berkeley. Yeah, yeah, yeah. But like, that's a good example of like, there's no way that I have enough available time. And, and the other people involved in the product are all startup people. Like, there's no way any of us have available time to ever do this before AI. [33:37] And so, like, that's a strange thing because it's not like an AI project. Yeah, what part of it is AI making more efficient for you? Literally...

[33:46] every single thing from the beginning from the more boring bits that are like, oh, we just got a lease. [33:53] draft in on retail i've never looked at this i'm going to drop it in chat gpt and ask questions that's the normal stuff are you are you you're going to chat gpt for that are you going you're going to oh one are you doing claude like what's your who's your who's your legal advisor right now uh legal advisor would be oh one okay um not oh one pro [34:11] Not too expensive. No, O1 Pro. Yeah, O1 Pro, O1 Pro. I mean, come on. It's a real contract. [34:20] Most everything else where I actually care about the output in terms of its language, the way it speaks to me, things I might reuse, that's all clawed. Everything's clawed. All coding's also clawed. Everything's clawed. [34:31] But so that's the obvious one is just like please analyze a contract. But like I'll give you an example like – I mean I can show you the code. [34:41] at... [34:41] like a floor plan back of the space. And so like I fed the floor plan into Claude, started coding. That turned into a windsurf project, which turned into an actual like demand model to try and project how many members we would have in the space before we maxed out demand, which then boiled into like, oh, well, we have six to eight personas for different types of people that come at different times. And that turned into a price sensitivity test. [35:11] now and like this is all a model that then i can go fix and change and rerun and like that would have never i mean you could have done that before but you would have had to like hire people and think about it and like or you just had to spend your own time like you know hours and hours and hours and hours and now you can just be like i want to see what's the sensitivity analysis and you're like oh here it is you know yeah that's the best another another one exactly in the same project just a rat hole on board game clubs is like we went through a process where we then

[35:41] All the SaaS companies that exist out there, like vertical SaaS companies that exist out there that help you run a membership club, run a co-working space. There's that kind of thing. Yeah. [35:54] all of them after evaluating them, they do what all SaaS software does, which is kind of good. They're not ever perfect for me, so on and so forth. About halfway through, we realized like, [36:04] I don't know, the four of us could just build this ourselves. And so we... [36:08] We're building all the custom-for-spoke software for running the space. And so now you can do things like – [36:14] make a voice phone call and say, hey, I want to play ARCs with three friends Wednesday at 3 p.m. It checks an air table. [36:23] It's agentically books the thing, writes it in the table, like all of it. It's just all bespoke. What does this do in your mind to like funding models for software businesses now that software is so much cheaper to make? [36:35] I mean, I don't know. I think the precise amount of people that should work at any company is eight. [36:43] We just passed that. [36:48] But I think around where we are, I love it. It's so much fun. And by the way, I've been a... [36:55] operator and founder everywhere from, you know, one to hundreds, like, you know, and like it's [37:02] There's something incredibly magical about that. [37:05] you know, one pizza stage. And that's where it feels like a team. That's where it feels like a literally just one cohesive pod team.

[37:15] And so I don't know. I think the challenge is how much can we use AI to solve all of the things that are really just faster horses problems. [37:28] I had this story – [37:32] That stuck in my head for many years – [37:37] It's Paula Shear, the designer. [37:40] She has a story where you should talk about the difference between art and craft and how – [37:44] And she's a very famous graphic designer, logo designer. Back in the day, she did some really famous record covers in the 70s. And you fast forward and she did like Shake Shack logo and stuff like that. So just like legendary – [37:56] Logo designer. [37:57] She used to talk about back in the day, someone would come in with an album cover and they'd be like, oh, it's a new Zeppelin album. We need a cover for it, blah, blah, blah. And then she talked about what it would take to get that done. And, you know, back then, this is obviously pre-Adobe, pre-Photoshop. She's like, there's a person that spent a whole week just on the lettering. [38:17] just like literally hand drawing every single letter on this cover. There's 20 people working on that project. And she's like, listen, the truth is that – [38:26] Only one to two of those was actually – they were all quote-unquote artists and they all quote-unquote went through art school. [38:32] All that's craft. Yeah. [38:34] Like there's really only one person making artistic decisions and making the core decisions. Almost everybody else is just execution. And the execution goes away when the craft is not covered by software. That's already happened. Now I open up Illustrator and I pick from fonts and maybe I tweak a font or I custom a font, but like it all happens in…

[38:52] A day or two. And instead, I get faster iteration cycles where we then work on this to make it better. If you fast forward today, it's the same thing in a company level. Like if I'm at 16 people, you have to ask or 20 or 200. You have to ask yourself, like, how many of those people are actually making the core decisions of that company and how much of them are involved in just literally whittling the wood? Yeah. [39:15] Yeah, that's sort of where we are internally is like, [39:19] Everyone at every is like a generalist who's multidimensional. Many of them are technical. Um, and we have like, [39:29] We have three products that we run internally aside from the media product. You know, there's that whole other thing where we're writing some of the best stuff in the industry that you should all subscribe to. Thank you. I appreciate that. But also that's – that was not a paid promotion. [39:48] And each one of those has a GM. [39:52] And the GM is doing everything from writing the code, like writing the release notes to like whatever. Then we have our creative lead who does all the design for everybody. And then we have writers who will go in and do some reporting on like what are we releasing this week and then write that up in Context Window, which is our Sunday newsletter. And then we have a bunch of writers who... [40:16] Um, but it's, it's interesting. Like it feels like, um, [40:21] So,

[40:22] Uh, it's, it feels very cohesive, but everybody has their like little domain or their little universe where they're responsible for a lot of things. Um, instead of like one person who just, their job is just like to tweak this, like one knob basically. Um, and, uh, I really love working with, with those kinds of like multidimensional people. And it's, it's quite common, I think for like early stage startups to like have a bunch of journalists and you replace them with specialists and whatever. [40:52] it's quite uncommon. I think a, we'll be able to get further than we would have before with the sort of like generalist vibe, but it's also quite uncommon for people, [41:01] a really early stage company to like be able to have three products and, and a media product that it can do. Like, I think we can do them at a high level. Um, and that's like totally new and it, and, and, and it allows us to like, and it's driven by generalists who have these like special power tools that can like do all of the like execution work so that they just need to know what to do. And then they can get it done really quick. Um, like we've done like, [41:28] I think three feature, like, real releases for Quora so far this week. And, like, that's one guy. Yep. Kieran, he's super talented. It's one guy and O1 Pro. Yeah. To be clear, it's also this many-billion-dollar model doing a thing in the background. [41:48] But, yeah, I just – it's – I think there's something new happening where those kinds of, like, yeah, eight-person, one-pizza companies can – And do you always use O1 Pro, by the way?

[41:58] go-to? Well, [42:00] - It's interesting. So I use O1. O1 is like my go-to model. I rarely use Cloud anymore. [42:07] which is really interesting because I was a big Claude guy for like a long time. Um, [42:12] Actually, the place where I use Cloud the most frequently is actually not in Cloud itself. It's in Lex, which is the AI writing app that we incubated. And that default model is Cloud. So I do use it a bit, but I'm mostly 01. I use 01 Pro a little bit. Like I do this exercise every year where I like reflect on things that I've learned and like I set goals and like do all that stuff, right? Same. Yeah. It's really cool because I've been doing it for five years and I can just like go back. It's like right before I started every year is when I started doing it. [42:42] back and just like look through each year and there's so much like juicy stuff in there so i just like took that and i put it in i put it in clod i put it in o1 and i put in o1 pro um and o1 pro is definitely the best like i i cried i cried a little yeah yeah because especially like the like o1 and o1 pro um because they can do the kind of like chain of thought and they can like retrace their steps or whatever they're much better at following a progression and like seeing and like

[43:12] That's right. [43:42] and it will fix all the bugs and it's like... [43:46] It's crazy, you know? I've had that a little bit. Like, I'm doing some... [43:51] So I'm like [43:52] apps that are i wouldn't they're like they're light incubations like maybe they'll become a nick in every product or maybe not and yeah i get like one of those a week yeah we actually for a while we don't have one right now but for a while we had an ai hacker in residence at spark for the same reason that that you guys have people like that which is just like because the number of particular things that you just want to take like a quick one shot is like more than i have available time in the day exactly so like please can we play with whatever's new [44:22] but you have to be playing yeah um and so like sometimes like i'll build something with o1 or with claude or whatever and and like this the particular example i'm thinking of it like had some it had some like more complex stats that it was doing that i i like i'm not like a big stats guy so like i was just like i think this looks right but i don't know and i just put it into o1 pro and i was like check the work here and i just trust that if o1 pro says it's okay that it's it's

[44:45] Because there's a trust problem, right? It's like, it's the same thing for like a manager when like a human manager is managing someone to do work that they don't know how to do themselves. That's why technical managers have a much easier time managing engineers. And what's really interesting about, about AI right now is I can really cheaply manage an intelligence to do a lot of things that I'm not qualified to do. And there's a question of like, how do I know if it's right? [45:15] And that's a really interesting question to figure out. But that's trust based on – [45:22] Have you ever tried [45:23] Have you ever found a set of prompts that are good at asking the model? [45:27] whether it thinks its previous work was good and getting a good response out of that. Because obviously if you say, hey, are you sure, that tilts the model towards not being sure. So it almost always comes back like, no, now that I've rethought it, and it gives you almost like the wrong answer. Yeah, that is interesting. I mean, I mostly am like, I do say, are you sure? So maybe I shouldn't do that. Or like I will take it and put it into another bottle and I'll just be like, do you see any problems with this? This is what I'm trying to accomplish. Are there any issues in this code basically or in the way this is set up? [45:58] I have trended towards asking for confidence intervals and pluses and minuses. Like, how confident are you in your answer? Give me a reason why you could be right and give me a reason why you could be wrong. Again, kind of chain of thoughty. And that usually gives me enough information, which is, again, proxying back to human behavior. If you don't understand something, get somebody to explain their logic around it a little bit more, and you can kind of try to figure out whether they didn't know or not. Is this for code or for what kind of problems? Literally everything.

[46:27] sure about a response back. Because you're talking about trust, and one way of talking about it is [46:31] you know, use a model you have more trust in. But we're always going to be wandering into weird territories. And so you kind of have to develop some techniques for trying to figure out what they're right about. That's interesting. Because the reason I ask is one of the things I found with Claude, like if you ask it for editing feedback, and you're like, can you grade this? It pretty much always gives you like a B plus A minus no matter what. That's right. It does. And then even if you only change a little bit, it'll give you like, oh, now it's an A or whatever. [47:01] Owen's a bit better at that. But yeah, I haven't yet had a lot of success with like getting accurate confidence in their roles. So I find that it's right. It's better. It's very bad at grading its own work that way. How good was this writing? Subjective reads, objective logic. I see. It's quite good at. Yeah, yeah, yeah. So, hey, you just answered a question about the history of startups. [47:31] me your reasoning and then afterwards give me a confidence interval, usually in that order. And it's quite good at that. [47:39] But again, like all these models, it's like trying to figure out what they're good and they're bad at. I find if I care... [47:44] about the answer. [47:46] being like specific, uh, [47:48] Then maybe 01 is better right now because it basically because it's doing reflection, thinking about it longer. So like, great. Think about it longer. Awesome. You saved me five more chats to get you to think about it longer to get the right answer. Sure. Shortcut.

[48:00] If I actually care about the words that are being used – [48:04] Like I might reuse those words or I'm literally trying to brainstorm how to talk about something or storytell something. Claude is still so much better at it. Yeah, I think you're right. I guess I don't really – [48:16] But you might not be using it that way right now, right? [48:19] I do. So I'm using when I use Claude, it's in Lex and I do use it to sort of like [48:27] I'll often like I'll be writing something and I'll have it like sort of complete Lex does like the it's it's sort of copilot. So it'll complete like maybe three more sentences or whatever. And I find that to be helpful. But I think Owen is getting better at writing. Like if you give it a big enough sample, it'll be it'll be much better than I think it used to be somehow. I know it's I know it. I know that doesn't make any sense, but like that's my experience. [48:54] Are you sure that's not just a skill issue? [48:57] But I know you probably – I know you saw the like O1, like had a prompt O1 article you mentioned that was going around. Do you have any specific like things you've learned about O1 Pro that has – have gotten you better results? No, I'm just a student there, honestly. Like I will say – well, actually I'll put it this way. [49:19] I read the [49:21] tweets about how to use a one, [49:23] And I read the guides on how to use 01. It was like basically give it more context. It's not a chat model. That's the like gist. That gist is give it more context. Tell it what you want. Give it an example of what you want. Say more. Yeah, yeah, yeah.

[49:38] For anybody who plays with these things every single day and is really out on the edge, like, I was already starting to do that anyway. So mostly it was, like, a head nod. Like, yeah, I should probably do that more. You're right. More than it was some kind of, like, big epiphany or some unlock. I'll let you know if I get an unlock on O1 Pro. [49:55] Any other, like, startups or products or, like, research-y type advances that you're, like, thinking about or interested in right now? The areas that I really – [50:08] Think about right now and we'll go back to this earlier. You I'll give you an example directly from earlier you have a [50:16] You do every year, like annual review thing. Yeah. Is it the same like five questions or 10 questions or something like that that you ask yourself? Or is it just more an exploratory conversation? Um... [50:26] The format is I will do... [50:31] goals. [50:33] Right. Like I'll do I'll do some like value exploration of like what do I want to like. [50:39] uh, move toward in my life. Like what is important to me? And then I'll also do like a bunch of, uh, [50:46] uh, [50:48] Uh, like what are the things that I learned about myself or about the world or, or whatever? Um, yeah. [50:54] And so it's not necessarily like a pre-prescribed set of questions, but it is a sort of prescribed output format. And then I'll like use a bunch of different questions and a bunch of different ways to get to those answers. Yeah.

[51:08] Like it's quite possible that existing out there in the world is a – [51:14] best practices for how to do your annual review. And it's quite possible that, you [51:20] There's no one answer. There would be one that's better for you than somebody else. But there's probably people that have really, really thought about this. [51:28] And one of the reasons the coding models work as well as they do is because we actually have [51:34] Lots of books about best practices in coding. We have popped up one altitude, and we don't just have a bunch of samples of code that get fed into a model. We actually have a bunch of examples of PRDs and descriptions and documents that describe how to do coding well and how to make this thing well and then the output afterwards. [51:56] I'm looking for markets where either a company or – [52:00] or somehow we have that. And so it is one thing, for instance, to build the AI therapist. It's another thing for... [52:07] Me to start an exploration at altitude one level above that where I get to figure out what the right therapist is for me with what area of knowledge that I want to bring to bear for this journey. [52:19] And there's very little that operates at that altitude. Most of them try to get to solution really, really fast. [52:25] and let you wander very, very low in the altitude. The same is just starting to give you code without saying, to go back to the word wear example, like, why don't you write down all the things you want here, and then we'll get started. Interesting. Well, there's a lot – I mean, let's take therapy, for example. There's a lot of books about how to do therapy, how to be a better therapist. Of course. Is that an example of the kind of – is that a field you're interested in? That's why I picked it. Okay. I picked it because there are – is an incredible amount of academic literature and other literature about ways to do therapy

[52:55] effective and so on and so forth. Now that has to be translated into model language and so on and so forth. I'll tell you another area that's actually quite hard. [53:01] What makes a game fun? [53:04] That's good. [53:05] Like if I pick up and – in fact, there's no – it's called ludology. There's no great ludology that would explain Super Mario Brothers on a spreadsheet. Like I can't look at Super Mario Brothers. [53:16] And we don't have a language for even describing things. [53:18] how you would get to fund there. [53:20] Yeah, I think that that touches on some of the like some of the stuff we've talked about in previous conversations about like, OK, so for therapy, like one of the problems is that there's there's no one answer to that because the thing that makes therapy effective is the therapeutic therapeutic alliance. [53:39] It's like, is like, do you like your therapist? Do they like you? Like, is there a fit? Right. Like the form and the context is a fit. You think it's literally just personality fit? I don't. I bring any theory of therapy to practice. But if we vibe, we're good. Um, what I. [53:57] Yes. What I think is that, um, really skilled clinicians are. [54:06] can, um, [54:09] can reduce some part of their skill to rules and ways that they make decisions. But actually, what's going on is totally subsymbolic and it's totally intuitive. [54:22] And, um, and the way that a non-skilled clinician would apply that rule is very different from the way that an actual skilled one, uh, will apply it. And so, um, the, the way to like, uh,

[54:36] for example, to create a model that does... [54:39] really good therapy is I think to some degree, like the methodology or whatever can be helpful, but it's really to, um, capture all of the nuances of a lot of really high quality interactions and then have the model learn all the like little sub symbolic rules that no one can really talk about to apply in the appropriate contexts. Um, it's very contextual and it's, it's, there's no, there's no answer to that, to those questions of like, what should you do in this situation? [55:09] dozens of different answers that you apply at the right moment, which is exactly what AI models are really good at and exactly what was previously incredibly hard to transfer between humans. And that's why we love like rules and logic and like scientific explanations and all that kind of stuff. Okay, so we kind of agree there, but let me disagree a little bit. Please disagree. So, yeah, you're pulling on a thread that we've talked about before and I actually do agree with, [55:39] by capturing enough knowledge that the model itself is, [55:44] will understand things about the world that we can't understand. Like the only way we pass down science and the way science works is because I found a way to verbalize the thing so I could tell you about it and then you can go do the thing again. And so there are just going to be a new set of things that we still don't have the words for. And it's awesome. There's new knowledge that's being created, even if we can't describe it. Awesome. Love that. [56:05] I think that's quite different than the point I'm trying to make. I think the point that I'm trying to make is there are times where the user's choice about the knowledge that they want to navigate or use themselves has value. And so a good example of this is just thinking about the keywords that we use nowadays.

[56:21] sometimes when we're trying to [56:23] Tell a model to go somewhere. Can you please rewrite this essay in the style of Paul Graham? Like we are using a keyword to try to normalize to a bunch of behaviors and to try to give it an indication. But where is the Wikipedia – [56:37] of all of the APIs that exist in the world and all of the chains of thought that exist in the world so that I can navigate and look at that library myself. I don't necessarily trust ChatGPT to pick the right app [56:52] modality of therapy or whatever it is, just as much as I don't really trust them to pick the restaurant for me. I want to talk about the theory of what kind of restaurant I want. And similarly, there's millions of things in the world where there's a set of five different ways you could go do the task. And certainly sometimes it's like, just pick whatever. But many, many [57:22] control. Just tell me what, tell me not, tell me the five different best practices for how this could be done. Yeah. [57:27] And let me pick that versus your, you know, weirdly amalgamated, you know, LLM version of best practices all merged together. Yeah, you want to be able to, like, allow, like – [57:40] You can't make the entire terrain of possibilities explicit because it's going to be too big, basically. But you do want to make – I think what you're saying is rather than have the LLM zoom right into a specific – Answer. I'm supposed to give you the answer. Yeah, get better at making some of the implicit stuff explicit so you can explore within reason and then dive a little bit more deeply. Yeah, I'll give you a really simple side project.

[58:10] - But I think there's actually like real startup opportunity, business opportunity here. But like my little side project was the first thing I ever built in WordWare was a startup advice [58:18] like, it was like a [58:21] I don't know. [58:23] Was it like a... [58:24] Startup invest mentor. So basically a little webpage you go to that you say, this is the startup decision I'm trying to make right now. It just says like, what decision are you trying to make? What in your gut do you think it should be? And then hit go. And then instead of just doing the chat GPT thing, which is just like, I'm just going to splurt out an answer. [58:43] I fed it very simply like a bunch of PDFs of like HBS articles and like a bunch of other stuff, which is basically decision theory. Like what are the 20 to 30 best practice decision theory, SWOT analysis, blah, blah, blah, blah. And so the first order of business it does is actually just trying to figure out – [59:02] three or four decision theories that you could use to come to the decision, make a recommendation on those, and then walk you through the steps that those things do to get you to the answer. It's that. It's like pop up one altitude. Help me learn from the things other people have used to structure whatever discipline they have been working on for 100 or 200 or 300 years. I love that. That's really interesting. What it makes me think of, it actually brings me back to the agente continuum you were talking about. It's like how much of a leash.

[59:32] It's maybe a related continuum, which is like how – like do you want it to have like a microscope like go right in or do you want to like look through binoculars or do you want to look through like panoramic like theater glasses or whatever? And you need to get both those dimensions dialed in and right now like the models are like – [59:53] only doing the microscope thing. They're only zooming in right away for you unless you ask it specifically. Don't do that. Like, give me start with the like, you know, decision theories or whatever. But yeah, I love that. I think that's really cool. Are people working on that? [1:00:07] I come across it very rarely. I would love to, if you're thinking that way, let's jam. [1:00:18] Cool. Well, that's actually a really good place to start to wrap it up. If people are looking to jam with you on any of these ideas, where can they find you? [1:00:30] You can email me, NabilaSparCapital. I'm on the web. It's not hard to get to. Great. Thanks so much for coming. This is awesome. Yeah. And thanks so much for doing what you're doing. We need more multimodal media companies in the world. I appreciate that. [1:01:00] the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure unadulterated knowledge bombs about chat GPT. Every episode is a roller coaster of emotions, insights, and laughter that will leave you on the edge of your seat.

[1:01:16] craving for more it's not just a show it's a journey into the future with dan shipper as the captain of the spaceship so do yourself a favor hit like smash subscribe and strap in for the ride of your life [1:01:29] And now, without any further ado, let me just say, Dan, I'm absolutely hopelessly in love with you.