BUILD TOOLS

“What Snapchat proved was actually that it's not about the the size of your network or the number of people you can contact on your network. It's about who you actually talk to. Mhmm. And that tends to be a much smaller group than the total size of the potential network or even your total number of friends. Right? In fact, most of your conversations, I would guess, right, on a daily basis are like with your wife. Right? Maybe with some of your close friends.”

“Yeah, so I read the tweet. The tweets are essentially, oh, Kapathi says agents are overhyped and can't do the work. So then I listened to the interview, and it's like the point he's making is, you can't just give an agent a prompt and expect it to do everything perfectly the first time. You still actually have to do lots of work to provide the right data and do all the correct context and actually do the evals and all the actual tooling. And my interpretation of that was, that's a fantastic opportunity for startups and anyone who can build software. Fantastic. There's tons of stuff that's still yet to build. And I just found it an interesting raw shark test almost. If you fundamentally want to believe that everything is overhyped, you're going to read into that, that, oh yeah, look, AI expert confirms it's overhyped. But if you listen to actually what he's saying, there's tons of opportunity to build really great tooling.”

“I don't necessarily think we're gonna move beyond the smartphone. I think the smartphone's actually gonna play maybe the most important role of legacy. So beyond solely a smartphone. Yeah. So I I mean, I think it you know, if you look at the capability of of glasses, at least when it comes to specs. Right? What I actually would estimate is that a lot of the large screen use cases are the first to move.”

“So I built that using Chat GPT and a Raspberry Pi. The keyboard is in the other room, otherwise I'd get it, but we got the Raspberry Pi here, the whole hookup. I've never built hardware before in my life. I've always wanted to, but besides the robotics kit when I was a kid, it just is a mini keyboard for $10. When I press Enter, it's essentially a keylogger. So I can lie in bed, write down an idea, press Enter. It sends an API request to Zapier, because again, I don't know how to code.”

“Another good tactic is to find founders whose companies were acquired by big companies and get them to be a champion. With Triple Byte, we were able to work with Apple and almost no recruiting companies working with Apple, and that was all because of a YC company, Q, started by Robbie Walker and Danny Gross, actually, that had been acquired by Apple, and then they helped us get in there. And then, actually, I remember we got a pilot with Oracle through a founder who had sold his company to Oracle and was just pushing for them to hire better engineers and helped us through procurement and gave us all the internal politics and step-by-step playbook to get the pilot going.”

“I don't necessarily think we're gonna move beyond the smartphone. I think the smartphone's actually gonna play maybe the most important role of legacy. So beyond solely a smartphone. Yeah. So I I mean, I think it you know, if you look at the capability of of glasses, at least when it comes to specs. Right? What I actually would estimate is that a lot of the large screen use cases are the first to move.”

“I'm mean, not going to lie. I'm like, AI is my slave. Like, not fronting here is like being mean to your AI. I don't know why people say thank you, it's a robot. And it performs better under pressure unlike men. But this is what I mean of the random. But like, yeah, I would say like, kind of like push your AI to like be more unhinged. Like, it's okay to curse. Like give it like, like AI is kind of like, you know, somebody on their first day of the job where they're like, they don't really know you.”

“I would recommend any startup, like there's no excuse anymore. Why do you have a PDF download? Build a tool. It takes actually less time to build a tool nowadays and nothing wrong with PDF downloads. Obviously, we do that occasionally, but it's very easy to just build a tool now and think about what weird tools they are, and then put them at the bottom of your site where people can try out different tools and weird galleries and even games. We've started screwing around making minigames. These are now just as easy to do as write an e-book, which is, if you're trying to collect more leads or e-mails for your newsletter, your business, etc., there's nothing better than building a mini tool that solves the first problem that gets people into the bigger problem that your actual company solves.”

“But now I think we're realizing there's no one to blame but us. And we've talked about why are these assets not going up because of, oh, it's a capital access problem, so we've got debts. No, it's not. We have an asset problem, and we have a trust problem. That's the core of what's happening right now.”

“I've heard it's actually a particular archetype of big company employee. It's someone that really wants to do a startup or has always had dreams of a startup, but they're not actually ever going to do it. They're too risk averse. And so they can kind of live vicariously through an exciting startup with founders that they get along with. And if you find someone like that to be your champion, it's like they want you to succeed because they're going to feel like they're on the startup journey as well.”

“And I think actually, funnily enough, what's causing the sentiment drift here is that that ideological movement industry blob that is crypto won. And so now that it won, it moved from being a movement which is on the fringe, on the outside and countercultural, to one which is in the mainstream and it's struggling with an identity crisis.”

“I mean, I I think it's extraordinary. Now more than two thirds of, you know, new code is written, you know, by AI at Snap. That's happened really, really quickly. I think, you know, the the rate at which these models are getting better is just extraordinary. So I think I think for us, we're really excited because we're so fortunate to be in a software business that has network effects.”

“Eventually what we've settled on for a lot of our features is instead, we have like the engineers have scheduled time on our calendar every week, where we go into our meeting room and we just stare at a Notion database of all the bad cases, like individual outputs that were bad, that were reported by our users, and we ask ourselves for each input, what is the exact step in the pipeline where this failed? What category does this belong in? We kind of treat it like a software bug.”

“Well, Norway was the first place that Snapchat got traction. I mean, we had no traction anywhere. Not The US. We had no traction anywhere except Norway. In fact, in the very early days I did not know this. Oh, it was it was a blast. In the in the early days, I think this was, like, after we had gotten venture maybe after we got an adventure funding. I think in the early days of of getting our first round, you know, we'd raised $400,000 or something like that. And we were really growing in Norway.”

“The kind of interface that I'm eventually building towards is a tool that lets you edit text or work through ideas, not in the native space of words and characters and tokens, but in the space of actual meaning or features, where features can be anything from, is this a question, is this a statement, is this uncertain or certain, to topical things like, is this about computers versus plans, or to probably other kinds of features that we don't really even have words for.”

“What Snapchat proved was actually that it's not about the the size of your network or the number of people you can contact on your network. It's about who you actually talk to. Mhmm. And that tends to be a much smaller group than the total size of the potential network or even your total number of friends. Right? In fact, most of your conversations, I would guess, right, on a daily basis are like with your wife. Right? Maybe with some of your close friends.”

“Building a ground up operating system on Linux was really difficult to do, but it's way more performant than trying to repurpose Android. Right? We we learned that Actually, you don't use Android. It builds your own, OS for it. Yeah. Android is way too bloated to work effectively on a on a pair of glasses. I mean, I think that's why you see the the most recent, you know, Google experiment project, Aura, has a huge compute pack.”

“Money amplifies your nature. AI amplifies your intelligence.”

“I think what parents need to know, what's so important for parents to know is they can already configure this on their teen's phone using the operating system. So Apple's got a ton of great settings. We use them at home for our fifteen year old Mhmm. Where we can decide exactly what apps he can use, how long he can use them. All of these settings are available to parents at the operating system level, which is a much more resilient way to implement this sort of of policy.”

“Building a ground up operating system on Linux was really difficult to do, but it's way more performant than trying to repurpose Android. Right? We we learned that Actually, you don't use Android. It builds your own, OS for it. Yeah. Android is way too bloated to work effectively on a on a pair of glasses. I mean, I think that's why you see the the most recent, you know, Google experiment project, Aura, has a huge compute pack.”

“You have to be driving AI fluency from the very bottom.”

“Zapier, for example, they have four levels where they're looking at employees and measure them on performance.”

“And there's a company that I worked with called Greenlight that also sells AI systems to banks, and they were telling me a story that is exactly along the lines of what Garry was talking about, where there is a bank that they were trying to sell to, and the deal fell through, because the bank had an existing relationship with Ernst & Young, who apparently builds all the software for the bank, which is apparently not that uncommon. And they're like, well, you know, we trust our vendor, Ernst & Young, we've been working with them for years. They say that they're going to build this AI system.”

“The thesis that Mike and I had was eventually this really retail-driven asset class will become a big institutional asset class. And those institutions are going to need something that looks and feels more like maybe a Wall Street Journal or a Bloomberg, something that they, and I'd underline this word, trust.”

“I mean, I I think it's extraordinary. Now more than two thirds of, you know, new code is written, you know, by AI at Snap. That's happened really, really quickly. I think, you know, the the rate at which these models are getting better is just extraordinary. So I think I think for us, we're really excited because we're so fortunate to be in a software business that has network effects.”

“I started Memelord and we could get into this. I started just as a newsletter for $6.90 per month, sending you the newest memes and then I sent you to a Google Slides deck because I didn't know how to code. That's really the evolution of Memelord was from that. It's the same thesis of you just want to be on the current trends and remix them for your brand. The future, know UX is the best UX. Good news for Sam over here is he could use it from any agent now.”

“Well, Norway was the first place that Snapchat got traction. I mean, we had no traction anywhere. Not The US. We had no traction anywhere except Norway. In fact, in the very early days I did not know this. Oh, it was it was a blast. In the in the early days, I think this was, like, after we had gotten venture maybe after we got an adventure funding. I think in the early days of of getting our first round, you know, we'd raised $400,000 or something like that. And we were really growing in Norway.”

“And that maybe brings me to the last point, which is that specs are coming, to consumers for the for the first time, later this year. So after twelve years of investment, in glasses and the next generation of computing and trying to make computing more human, it's actually coming. So, it's it's a pretty extreme time, at Snap, and then we're doing all of that, while transforming the business with AI.”

“They built the solutions to replace a lot of the systems that they're paying for.”

“The quality of the tools and how much you can iterate on the tools, I think bottlenecks how much you can iterate on the thing that you're working on with the tools. And so it pays to be able to quickly tweak the tool or add the functionality that you need to see something new, whether that's a tool that's for evaluating models or running models or visualizing things either in the outputs or in the training like behavior. And because of that, I think I've mostly defaulted to building my own little tools whenever I needed them.”

“The closest analogy that I have is spectrograms when people are dealing with audio. Normally, sound is like a wave in space. It's just a single kind of, I imagine, like a single string vibrating back and forth over time. If you work with audio, that's like the base thing that you work with. But if you work professionally with audio, then you actually most of the time work in a different representation space, where you don't look at vibrations over time, but you look at space of like frequencies over time, or what's called a spectrogram.”

“They're looking at the non-technical people that aren't AI native and they're going to be cutting.”

“To be fair to IT consultants, Apple is very bad at software. You know, my favorite example is Apple of the company that can have infinite access to capital and infinite access to the smartest people in the world. All of us use iPhones, and I use the calendar app. I think you guys do too. We use it many times per day due to our schedules. And even the calendar app is a piece of trash. You know, you probably run into some sort of weird bug in that, like, almost every single day. So Apple, a company with infinite resources and infinite access to the smartest people in the world, cannot make a good calendar app. So, you know, if that's true for Apple, how could any normal company, let alone an internal IT system, let alone, like, Deloitte or Ernst & Young, like, very well-meaning people, but, like, you know, most of the time, the output of something like that is bad.”

“You are an example of a company and a product that's going to get an inflection point because agents are going to become your users. Because agents don't get in their mind about being funny or not funny. They don't overthink. They just go straight to the tokens and YOLO something out. I think working with an agent as a user, especially in marketing, just reduces the friction across so many things. It helps you climb Cringe Mountain in a way that's very hard to do as a human.”

“One of the things that I've learned in doing more research things over building product is that in research land, I just do not feel guilty about copy-pasting code because you have no idea how the thing is going to change. And it may be that copy-pasting is just going to like save you from not having to overgeneralize anything.”

“That's the core of what's happening right now, which is, you know, we'll get into some of the data that backs this up later. But I mean, the average token or the median net return of a token over the last five years is down 80%. That's the problem with the industry. And there's a lot of startup market structure reasons for that.”

“I'm generally a pretty optimistic person about technology, as long as the way we package these things is more humanist, rather than just automate all of the things. You see companies situated at different points in the spectrum between, you want models to automate things in a way that takes away agency, i.e. replacement, or you want models that amplify. I think OpenAI is very much on the replacement side. Literally, their definition of, I think, AGI is something like a thing that can take over a single full human's job, where if you look at a company like Runway, a lot of their framing of usefulness is about extending that agency of what you want to express.”

“The main ones that are always top of mind are, we want models that hallucinate less, we want models that are cheaper and faster, lower latency, and we want models that follow instructions better. There's a fourth one, which is a big one, but a very hard one, which is we want models that are better at general reasoning.”

“Models are very lazy about what it has to learn. And it only learns the thing that you want it to learn when it's run out of options. It's exhausted all the other options that it has to try to minimize its loss. And the only remaining option is to finally learn the thing they want it to learn. In language data broadly, I think it's so difficult to get to that point. Even if you think about the math proofs that occur naturally in the internet, for example, there are a bunch of proofs on the internet that are just incorrect.”

“Let your marketers cook. You have no idea what they're capable of. Either let them cook and let them market their stuff or watch them leave your company. Obviously, I'm biased here, but the last company I was at, they didn't let me cook, and that's why I quit. And then I raised money and built my own company. And you're going to see a lot of that. And I think a lot of marketers and non-technical people are in a revenge mode right now, and they want to cook. So either let them cook and let them market their stuff, or watch them leave your company.”

“Everything monotonically improves from here, right? I think that's the scary part. Omneky has this good video on Sora where he occurs this phrase of like, this is the worst that this technology is going to be from here on out. And I think that's a really succinct way of expressing the fact that like, okay, you may maybe you think GPT-4 is like not super, super, super smart. But like this is like, if you look back at the history of smartphones, every phone when it came out is the worst that smartphones are ever going to be from that point on out.”

“Engineering teams at these orgs are filled with people that themselves don't actually really believe in AI, don't use cogen tools, think it's all super overhyped, are really excited when an MIT study comes out saying that it's all like hype and retweeted, and really want because it's a narrative they want to believe. But the consequence of that for the companies is that they can't build the product. So if your engineers don't believe in this, then how are you going to build a product that actually works? The knock on effect for start-up centers, if you can actually build something that works, the enterprises will talk to you because they have no other options. You can't build it internally, you can't go to an established company, so the start-ups are actually getting the shot that they never had before.”

“There's a lot of benefits of retrieving limited context rather than just putting everything in a model window. Some of them include observability. So if you give the model 10,000 inputs and it gives you the right answer, and it gives you the wrong answer, how do you debug that? Where if you have a pipeline that gives you maybe that top 10 documents and has a language model answer that, if you've got it wrong, you could ask useful questions like, did the answer exist in the documents that it saw? Was it at the beginning or the end of the context?”

“Here's one other point from the study that I also thought was really interesting in terms of why enterprise is such a big opportunity for startups. I'll actually read this quote. This is from some enterprise buyer person. We're currently evaluating five different gen AI solutions, but once we've invested time in trading a system, the switching costs will become prohibitive.”

“I think what parents need to know, what's so important for parents to know is they can already configure this on their teen's phone using the operating system. So Apple's got a ton of great settings. We use them at home for our fifteen year old Mhmm. Where we can decide exactly what apps he can use, how long he can use them. All of these settings are available to parents at the operating system level, which is a much more resilient way to implement this sort of of policy.”

“And I think the promise of glasses or or at least what I love about glasses is it actually brings computing into the world. I mean, I think this is some something that computing has suffered for a very, very long time is that it just by its nature has been isolating. Right? When I was growing up, you know, I loved computers. I built my own computer. But, like, to use a computer, you had to be in the computer lab at lunch when all your friends were on the school yard, you know.”

“This is a very impressive case study. The company is called Reducto. They just announced their Series B recently, and they actually closed a fan company 154 days after the batch, which is, I haven't seen that happen. And this big fan company reached out to them because they did a YC launch. That's how they found them. So our launches get people watching them. And they reached out and they go, this is interesting, we'll love to try it. And we've been working on a solution. Turns out this particular company has been trying to, what Reducto does is document processing for AI. And this company has been having a lot of internal systems and build internal solutions for years to run a lot of the operations. And a lot of the solution, they tried open source, they tried AWS, Tesserac, all sorts of OCR solutions. And they were not cutting the mark. And this is where product excellence really got Reducto to win the deal and be a pretty big one.”

“And that maybe brings me to the last point, which is that specs are coming, to consumers for the for the first time, later this year. So after twelve years of investment, in glasses and the next generation of computing and trying to make computing more human, it's actually coming. So, it's it's a pretty extreme time, at Snap, and then we're doing all of that, while transforming the business with AI.”

“And I think the promise of glasses or or at least what I love about glasses is it actually brings computing into the world. I mean, I think this is some something that computing has suffered for a very, very long time is that it just by its nature has been isolating. Right? When I was growing up, you know, I loved computers. I built my own computer. But, like, to use a computer, you had to be in the computer lab at lunch when all your friends were on the school yard, you know.”

“I think for the last year, I've been talking about crypto. There's this big line in the sand moment for crypto. You got the first 15 to 16 years, and then I'd say 2025 was this line in the sand moment, and you got everything after 2025. And I would say this rebrand for Blockworks marks that for us.”