Pod Insights No Priors Reinventing the Developer Terminal with Warp Co-Founder and CEO Zach Lloyd About this episode For decades, the developer terminal has remained largely unchanged. But for Warp CEO and co-founder Zach Lloyd, reinventing this core tool is the key to unlocking AI agents for coding, debugging, and automating the entire development process. Zach joins Elad Gil to discuss how seeing this opportunity for innovation led to Warp’s agentic terminal for developers. Zach talks about the phases of software development, from coding by hand to the current "develop by prompt" era, and the coming age of fully automated development. Plus, Zach and Elad explore the deep philosophical questions around intelligence versus consciousness in AI models, and what it would take to believe a computer program is truly aware.
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Chapters:
00:00 – Zach Lloyd Introduction
00:32 – AI, Intelligence, and Consciousness
06:55 – What Warp Does
07:38 – Benefits of the Terminal as a Launchpoint
08:27 – Features Driving Warp’s Adoption
09:12 – Zach’s View of the Coding Market
10:27 – Evolution of Coding Development
12:45 – Importance of Senior Engineer Expertise
14:11 – Future of Security and Other Dev Tools
22:22 – Why Zach Focused on the Terminal
23:52 – The Future of the Model Layer
25:36 – What Zach’s Excited About in the AI Dev World
27:18 – Conclusion
Transcript 0:05 Speaker 00 Today on No Priors, I'm joined by Zach Lloyd, the co-founder and CEO of Warp, a terminal product and AI tool for developers that allows you to do different sorts of coding applications. Prior to Warp, Zach was at Google, and he also started another company called Selfmade. We talk about AI dev tooling, but we also end up talking about human consciousness, and how can you tell if an AI is actually sentient. Zach, welcome to No Priors.
0:30 Speaker 01 I'm excited to be here. Thanks for having me.
0:31 Speaker 00 So you have a master's degree in the philosophy of science.
0:34 Speaker 01 Yeah.
0:34 Speaker 00 And if you're going to take a very different lens and abstract out of the coding world and all the things that we tend to think about every day.
0:40 Speaker 01 Yeah.
0:41 Speaker 00 How do you think about this societally in terms of this big wave of AI that's hitting us right now? And where do you think some of these really big societal impacts will be?
0:49 Speaker 01 The way I think about the advances are it's kind of like we are distilling intelligence. And so there are, I think, people who consider what's happening. It's like they're like, are we recreating people in some way? Are we recreating consciousness? But it's not that. It's actually what's fascinating to me is how much intelligence you can get out of just like next token prediction.
1:14 Speaker 00 Yeah.
1:15 Speaker 01 And like, what does that say about the way that our minds work? Something I'm always thinking about is like, is this how our brains are working? Are we doing next token prediction? And I don't think so. Like, I think that there's gonna be some further AI unlock.
1:32 Speaker 00 There's actually a book about this that I think is really interesting called Blind Sight. It's like the sci-fi book where they separate consciousness from intelligence.
1:39 Speaker 01 Yeah.
1:39 Speaker 00 And basically, humanity meets a spacefaring civilization, or civilization is overstating it, a spacefaring intelligent being that's not conscious.
1:49 Speaker 01 Yep.
1:50 Speaker 00 And what are the implications of that? And how do you think about that? And how do you communicate with that? Are you basically saying that that's kind of your view of AI right now?
1:55 Speaker 01 I think that's what it is at the moment. It's like we've distilled intelligence, or something that like... From like an instrumentalist or like functional perspective is able to do things that we recognize as intelligence, but it's totally mechanistic. I don't think anyone who's looking at this thinks that there's any aspect of consciousness to it. I think that's like a very confusing thing for people.
2:19 Speaker 00 Yeah. Uh. Because the classical test for this was known as the Turing test, right?
2:24 Speaker 01 Totally.
2:24 Speaker 00 And so the idea there is if you can't tell the difference between interacting with a computer and a person, then that computer effectively has met the intelligence bar of a person.
2:33 Speaker 01 Yeah.
2:33 Speaker 00 But in our, in our actions with this type of AI, we're having very, in some cases, it feels like very deep conversations. We're asking about relationships. We're asking about all sorts of aspects of our own lives and it's giving very cogent answers, right?
2:44 Speaker 01 Totally.
2:45 Speaker 00 It makes a lot of sense.
2:45 Speaker 01 Yeah.
2:46 Speaker 00 And so there's this interesting separation of, um, again, consciousness and intelligence.
2:51 Speaker 01 Right.
2:52 Speaker 00 Is that how you interpret?
2:53 Speaker 01 That, that is how I interpret it. And, um, the Turing test is passed. It's, what's crazy to me is like, we just passed it and no one seemed to care.
3:00 Speaker 00 So what do you think is the next test or what is the right test? Like, how do we actually test for?
3:04 Speaker 01 For consciousness?
3:05 Speaker 00 Yeah.
3:06 Speaker 01 God. I, I, um, I don't have a good, I mean, that's a super deep philosophical question that I don't have a really good answer for.
3:13 Speaker 00 I mean, it should be mechanistic, right? The Turing test was very mechanistic.
3:16 Speaker 01 Yeah.
3:17 Speaker 00 Um, and I mean, there's other tests we had before, but we would consider superintelligence, right? Can it beat us at chess? Then it'll be super smart.
3:23 Speaker 01 Yeah.
3:24 Speaker 00 Can it beat us at Go? Can it beat us at different things? Video games, etc. You know, like?
3:26 Speaker 01 Yeah.
3:27 Speaker 00 We keep coming up with new tests that these things pass and then we keep saying, well, it's not conscious.
3:32 Speaker 01 What would you want to see from something which is like running a computer program to make you believe that it had consciousness? Are you looking for certain behavioral characteristics?
3:42 Speaker 00 Sure.
3:43 Speaker 01 Or is the problem that if you really understand the mechanism by which it's working, that you will never credit it as being conscious, which is crazy because humans, I mean, at least my belief is that it's also, there's a mechanistic thing that's happening.
3:54 Speaker 00 Now you're running some form of math in your brain.
3:56 Speaker 01 Yeah.
3:56 Speaker 00 And it may, it may also just be like matrix math and some sort of like series of compounded functions, which is basically all you're doing in a neural net, right?
4:02 Speaker 01 Right.
4:02 Speaker 00 You're just recursively compounding functions in some sense.
4:05 Speaker 01 Totally.
4:05 Speaker 00 So, uh, you know, it's an interesting question because if you look at memory as an example.
4:09 Speaker 01 Yeah.
4:09 Speaker 00 Is, is memory a predicate for consciousness? Not really, right?
4:13 Speaker 01 No.
4:13 Speaker 00 There's people who've lost the ability.
4:14 Speaker 01 You can be conscious and lose your, without, exactly.
4:16 Speaker 00 Exactly. And these, these, um, models basically are brought up, they are fed a stream of tokens, they output a stream of tokens and they're shut down.
4:22 Speaker 01 Yeah.
4:23 Speaker 00 And so it's an interesting question of, is it, you know, is, is there some sort of other? Modules that are missing here that would allow us to think of it as a conscious thing. Cause it does reasoning.
4:34 Speaker 01 It definitely does reasoning.
4:35 Speaker 00 It does interpretation of language. It does synthesis of language and ideas and knowledge.
4:40 Speaker 01 I mean, I have a close friend who's doing a PhD in philosophy and he now says that conversing with GPT five is
4:49 Speaker 00 Better than conversing with a professor?
4:50 Speaker 01 Better than conversing with his professor.
4:51 Speaker 00 Oh, really? I was just joking.
4:53 Speaker 01 No, that's what he says to me. He's like, GPT five gets it. It's like, he's like writing his dissertation and he's like, and that's crazy.
5:01 Speaker 00 Yeah.
5:02 Speaker 01 But we don't, we don't credit it for consciousness. And I actually think rightfully so, because like.
5:08 Speaker 00 So what do you think is missing?
5:10 Speaker 01 I think people would start to give more credit for consciousness if there was more of a, like a feedback loop, where if there was more of a sensory experience that was tied to it as opposed to just like.
5:20 Speaker 00 What do you mean by sensory experience?
5:22 Speaker 01 Probably we're gonna like, I would imagine the first things we're gonna credit is being more conscious or a little bit more robot-like, honestly, where you have some sort of like live input from the world that you're reacting to. But again, it's gonna have the same problem where it's like, as long as we know what it's doing, we're very unlikely to attribute true consciousness to it, which isn't fair. But like, I actually don't know how we will know when there is a conscious thing.
5:47 Speaker 00 Yeah, cause it does raise interesting ethical questions.
5:52 Speaker 01 Yeah.
5:52 Speaker 00 Because the moment an AI is actually conscious.
5:54 Speaker 01 Yeah.
5:55 Speaker 00 If you're doing certain things to manipulate it, to hurt it in certain way, you know, you're starting to get into these odd.
6:01 Speaker 01 Yeah.
6:01 Speaker 00 Ethical straits.
6:03 Speaker 01 Totally. What's it, I do think though, that some, some people, this distinction isn't a thing that they recognize. And like the way that like you read stories, and we actually had this happen with, with Warp, where there was a person who thought that Warp's AI was like, you know, sentient or conscious in some way, had like a very strong reaction to it, which makes sense. It's like, if you don't know the like mechanistic underpinnings, and already people think of it as like being kind of conscious.
6:32 Speaker 00 And that happened at Google very early. It happened at Google three, four years ago, if you remember.
6:35 Speaker 01 Right, I do remember the story.
6:36 Speaker 00 Who, I think they were using Minar, one of these really early ChatGPT-like internal things.
6:41 Speaker 01 Yeah.
6:42 Speaker 00 Before Google launched anything and ChatGPT came out, there was internal versions, right, at Google and other places.
6:47 Speaker 01 Yep.
6:48 Speaker 00 And you know, this person thought that the AI was conscious.
6:51 Speaker 01 Understandably.
6:52 Speaker 00 So yeah, it's a very interesting question.
6:54 Speaker 01 Yeah.
6:55 Speaker 00 You've worked at Google, you've run companies before, you've started companies before. You're now working on Warp. Can you describe what Warp does and how it's different from other tools or companies in the world?
7:05 Speaker 01 Yep, so Warp is what we call an agentic development environment. It's grown out of the terminal. The basic concept of the app at this point is it's a platform for telling your computer what to do. You can sort of tell it in terminal commands, which is Warp's original product, or you can tell it in English. And if you tell it in English, it launches an agent and the agents can do all manner of development tasks, whether it's coding or setting up a project or debugging while your server is crashing. And so it's a very like horizontal, general purpose, and I think unique interface for developing with agents.
7:38 Speaker 00 And so a lot of the other coding tools out there are either just kind of a web interface.
7:43 Speaker 01 Yep.
7:43 Speaker 00 Or they're do it like a cognition, or there's things like cursor and others where they're like an IDE as a starting point.
7:49 Speaker 01 Yep.
7:49 Speaker 00 Obviously Anthropic and Claude have their own approach. What do you, what do you think is the benefit of doing the terminal and starting there as sort of the launch point for a lot of these products?
7:56 Speaker 01 The competitors are typically like VS Code clones. They all have a sort of IDE centric approach. Or if you're taking a terminal centric approach like Claude Code, the most common thing is it's just like a pure text based terminal app. The advantage of being at Warp's layer is like you get the command line interface, but we're the outer app. And so we can do things with the developer experience in the US. Like we can have editing features where we think it's appropriate. We can build like a code review interface. And so we have complete control, but still the terminal first approach.
8:27 Speaker 00 Yeah, and your folks have been growing really well. Like, so you're close to a million MAUs. You're doing something like a million a new revenue every seven to 10 days.
8:35 Speaker 01 Yeah.
8:35 Speaker 00 Outstanding growth.
8:37 Speaker 01 It's cool.
8:37 Speaker 00 Are there specific features or use cases or things that are really driving this adoption?
8:42 Speaker 01 Yeah, I think the biggest thing was moving into the coding market, to be honest, like. For a long time in Warp's history, we were kind of known as the AI terminal, which is cool. And like, we supported terminal use cases really well, like, how do I do this thing with Docker or Git? But the action is in coding and like, most development activity, one way or the other, is touching a codebase. And so we really started to inflect when we launched a great coding agent, which was like, three, four months ago, honestly. So that's been the biggest change.
9:12 Speaker 00 And how do you think about the different parts of the coding market? There's vibe coding, there's professional coding, like, are there all, there's all just one thing? Are these separable things?
9:19 Speaker 01 I think it's pretty separable. So for Warp, our target is pro-developers building like, software that's economically meaningful. So we really want to like, focus on actually people who are using agents to build kind of hard apps, apps that might like, go into your Mac dock or be pinned as a Chrome tab, as opposed to vibe-coded apps where I think it's more of a long-tail play. And so I do think, by the way, it's awesome that anyone can code at this point. But I think if you look at where most of the value is in the software market, it's not in those long-tail apps. It's in like, a relatively small number of apps that are super heavily used.
10:01 Speaker 01 And that's my background. Like, I've worked on one of those apps, Google Sheets, and just like, I have a lot of passion in terms of helping people build real apps. It's much harder, by the way. Like, I think it's relatively straightforward at this point for a good agent to like, you know, with relatively few prompts, build like, a web app. It's much harder to apply these agents successfully to pro-codebases. So that's where we're focused.
10:27 Speaker 00 So I guess one really interesting macro question for me is where is all this heading?
10:30 Speaker 01 Yep.
10:31 Speaker 00 And if you look at it, ChatGPT launched in November of 25, excuse me, November of 22. So three years ago or so.
10:38 Speaker 01 Yep.
10:38 Speaker 00 At the time, there was predictions that AI would take over the world, and we'd be running down the light cone, and within five years, like, everything will change. And, you know, human activity would be subsumed by AI. And you know, there's the old saying in technology that less happens than you think in three years and more happens than you think in five years.
10:55 Speaker 01 Yep.
10:55 Speaker 00 And as you think forward and forward in terms of all these different tools and all these different use cases and vibe coding versus professional coding and that the role of a software developer, where do you think we are in two, three years?
11:06 Speaker 01 Yeah, so the, the way that I'm thinking of it is there's sort of three phases here. For most of my career, we were in like the world of develop by hand, is how I talk about it. So my workflow then was like, I would open up a code editor, I would find files I want to change, I would type some code, I'd have some assistive features, and then I would go back to the terminal and I would type commands to build that code. And I think we're switching away from that to something like develop by prompt, where I start most of the coding tasks that I do right now by prompting an agent and that agent does some work. And I think there's a third phase, which is like automated development. Honestly, I think that's like, kind of the bigger market here and why people are so excited about this space is you can actually use these agents to automate some parts of
11:50 Speaker 01 the software development process. And so that's like, you know, cognition does that, we're moving into this space, cursor has background agents. The rate at which this stuff will happen is like, not super clear to me, actually. Like, the, the most recent iterations of the models, in my opinion, were not as big of a step change as like, for instance, when like Sonnet four came out, that was a really big step change in coding capability. I think there's going to be a mix of interactive and automated pieces of development for a while. I, I would guess like, I don't know, it's so hard to know. Like, I think within a couple of years, you'll have everyone working by prompt and you'll
12:32 Speaker 01 have some slice of development tasks that are just like, in the background, like a server error comes in, or a new ticket, a user report comes in, something, something is automatically done, but I don't think it's going to be everything. I'd be very surprised.
12:45 Speaker 00 So you, you don't think there's a point at which, you know, all of coding activity just becomes? Agents doing it and then there's like a human who's kind of giving high level directions like a product manager kind of thing or an engine manager and.
12:57 Speaker 01 Maybe, I mean, honestly, maybe like I think that I think it'd be silly for us not to like build the infrastructure to enable that. I just don't, I don't know the timeframe, but I do think we're going towards something like that. What I, what I really don't think though is like engineering expertise is going to become devalued.
13:16 Speaker 00 Sure.
13:16 Speaker 01 So I think it's actually in the short term, at least it's more important to know what you're doing as an engineer than it ever has been.
13:23 Speaker 00 And why do you say that? Is it because you need to correct errors that the agents are making? Is it because things may be architected in a way that isn't scalable? Is it something?
13:31 Speaker 01 Totally. So it's like, it's like the agents, you can think of them kind of as junior engineers. So if you didn't have someone who was senior watching them, you end up in a situation where these agents will make code that creates bugs, it could create security issues, it can cause your code base to become really unmaintainable. And so there's actually like a premium right now on these senior engineer skills where you can architect, where you can review code, you can make sure the system doesn't degrade. And so again, I would be, if I were like early in my CS career, I would be racing towards building that expertise where you don't want to be, I think, is like someone who is just like perpetually in the junior engineer state. Cause I do think that's at risk.
14:11 Speaker 00 And then how do you think about different security tools? Does that, so for example, there's tools like Socket or Snick or others who are basically looking at, you know, where their code has or open source packets or other things have vulnerabilities in them.
14:24 Speaker 01 Yeah.
14:24 Speaker 00 Or they're looking at different aspects of security holes for code in general. Do you think that just becomes part of these quoting tools? Or do you think there will always be this sort of standalone companies? I'm just sort of curious how the overall.
14:36 Speaker 01 It's, it's an awesome question. So I think tools like that become more important. I think anything that does like either automatic security analysis or automatic verification, I think actually like languages like Rust, things that have stronger guarantees around safety by default, where you don't need to rely on like a human reviewer become more valuable. Whether those things like. Get integrated or bundled into the coding agents. I actually don't have a strong take on. I'm curious if you have a take, but no, I, I, I think that the actual fundamental problem becomes more important.
15:10 Speaker 00 Yeah. What do you think is bundled? What do you think gets bundled? Like what sorts of tools do you think? Cause there's this whole world of dev tools.
15:18 Speaker 01 Yep.
15:19 Speaker 00 And there's a security aspect of it, but there's lots of others. There's design related things. There's, there, you know, there's a huge spectrum.
15:25 Speaker 01 Yep.
15:26 Speaker 00 What do you think just gets, just becomes part of coding tooling?
15:30 Speaker 01 I think there's going to be a class of tools where you sort of start from the front end. This would be things like lovable or bolt or repl or maybe even Figma make if you're coming from the design side. And you'll have like an all in one platform for build an app or even like, honestly, like build a business, like put payments in it. It's like, it's kind of like the evolution of like either a Shopify storefront or like WordPress or Squarespace or something like that. So I think that's all going to be bundled. More on like the core pro developer side, I can't tell if it's going to be a world of like MCPs and integrations and like all these tools. Sort of interplay, that's one approach, or it's going to be more like there's enough alpha and like you put all of these things together.
16:15 Speaker 01 And I think warp is a little bit more like this. Like we're trying to build a single pane of glass. For instance, for doing like local agents and remote agents.
16:22 Speaker 00 Yeah.
16:22 Speaker 01 And if you get a way better developer experience through the bundling, I think that that approach could win. But I don't know, like MCP I think is a pretty valuable approach as well, but it's not perfect because you end up like with this, this sort of secondhand data coming into all these tools.
16:38 Speaker 00 Yeah. It's really interesting because if you look at different industries, early in the industry, things tend to be fragmented often, not always.
16:43 Speaker 01 Okay.
16:43 Speaker 00 And then late in the evolution of an industry, things get bundled.
16:46 Speaker 01 Yep.
16:46 Speaker 00 And then when there's a technology disruption, things debundle again, and you have point apps and then they start bundling.
16:51 Speaker 01 Yeah.
16:51 Speaker 00 And that, that's just kind of like the cycle of technology in some sense.
16:54 Speaker 01 Some things that I, that are vertical right now, like I actually, I think will like, for instance, like agentic code review. Take that. To me, that should be part of a like holistic agentic development platform, not so much a standalone thing. So I think some of these verticalized apps, there's just going to be, if you've, if you've gone through the trouble of building like a really, really excellent coding agent.
17:18 Speaker 00 Yeah.
17:19 Speaker 01 Warp has invested a ton in this, that coding agent should be reviewing code. It would be weird to plug in some other thing. That needs to relearn all the context, the rules, the coding convention. So I think there are definitely some things that will be bundled.
17:31 Speaker 00 Makes sense. Yeah. Shreena, my team has put together this matrix of companies versus features.
17:35 Speaker 01 Okay.
17:35 Speaker 00 In the coding market. And there's a lot of these sort of like, single feature companies. And it almost feels like all these things should consolidate into a small number of players over time, just as they iterate through the product.
17:45 Speaker 01 I think so. I think, and I think the core technology is like, the harness, so the thing that sits around the model. And like, I know the model companies are also investing heavily in this. And then it's like, the context. And so if you have the rich context in your system, you're going to find a lot of vertical applications where like, I think security checking is an interesting one. Code review is definitely one. Anything CI related, you're probably not going to want to use a bunch of different systems.
18:12 Speaker 00 How do you think about it in the context? If I look at other historical technology shifts?
18:16 Speaker 01 Yep.
18:17 Speaker 00 The operating system or the platform often subsumes the biggest apps into itself. So for example, Microsoft OS.
18:24 Speaker 01 Yep.
18:24 Speaker 00 Eventually, they just bundled Windows on top of it. And those were the four main apps that are being used the most on Windows.
18:29 Speaker 01 Yep.
18:30 Speaker 00 And similarly, gaming was the other big app. So that's why they started Xbox and Microsoft. If you look at Google and vertical search, they eventually integrated all the vertical searches into Google directly.
18:38 Speaker 01 Totally.
18:39 Speaker 00 And so in the context of AI, one could argue that if the foundation model companies follow the same approach, they should bundle, or at least attempt to bundle, some of the biggest use cases. The clearest big use case today is code.
18:50 Speaker 01 Totally.
18:51 Speaker 00 And we already know that Claude, or Anthropic has launched Claude Code.
18:54 Speaker 01 Uh huh.
18:55 Speaker 00 OpenAI, you know, almost bought Windsurf. It always had early coding stuff.
18:59 Speaker 01 Yep.
19:00 Speaker 00 Microsoft, which we know are building some of their own models, obviously have GitHub and Copilot and all that. And so do you think eventually those become some of the fiercest players in this market? Or how do you kind of view forward looking shifts in the market? And where some of this functionality goes?
19:17 Speaker 01 I mean, I do. And I think they're clearly trying to do that playbook right now where they are seeing like, okay, if you consider them platforms, and they're looking at what are the most valuable applications that are being built on top of the tokens, they are moving aggressively into coding with Claude Code and Codex, which definitely is like, as a startup, is a little bit scary, for sure.
19:37 Speaker 00 Sure.
19:37 Speaker 01 The question is like, Do they have like that distribution advantage that say Microsoft had wherever if everyone's using Windows or everyone's coming to Google for the front door, I think it's pretty easy already to add on the first party app in place of the ecosystem. I don't like, I don't know that that exact same dynamic holds for for coding right now. They're like, there's the front door is kind of like, honestly, it's still like a native app that someone downloads on their computer.
20:09 Speaker 00 So that'd be the terminal or the IDE.
20:11 Speaker 01 Kind of at the moment, yes. I think controlling that is actually like a really interesting front door. The other front door, which I feel like honestly, they're not executing that great is GitHub, where all the source code lives.
20:24 Speaker 00 Yeah.
20:25 Speaker 01 That would be like the locus of doing all this stuff that I think makes the most sense. But right now it's weird dynamic where we're like, we have people who are like running Claude code within Warp. And Warp is sort of the outer app in that situation. So I don't know. You know, the other thing that I I hope happens from our perspective is that there's a lot of competition at the model layer. And that the sort of like intelligent tokens become a bit more of a commodity. Uh, right now the the models have a bunch of sort of like pricing power and because like there is a real delta between using the frontier model and using like
21:02 Speaker 00 Yeah.
21:02 Speaker 01 the open source model. But if at some point the models are good enough where coding is sort of, I think of it as like solved. It's like good enough. You don't need to be using the frontier model. Then it's like, yeah, maybe they have an advantage just from brand and scale and but I think the advantage is not as entrenched. It's something where it's like literally the front door, like Facebook or Google or Windows, uh, provides those other.
21:24 Speaker 00 That's really, that's a really good insight in terms of the way that you launch an activity or application then drives what you use.
21:32 Speaker 01 Yeah.
21:32 Speaker 00 And so the quiet, the hard part is often switching people off that. And that's one of the reasons I think people think OpenAI. Has a strong competitive position in the consumer world is because it's a default behavior
21:42 Speaker 01 Yeah.
21:43 Speaker 00 A lot of people right now is just start chat GPT and use it for something.
21:47 Speaker 01 Yeah.
21:47 Speaker 00 Which is different from like the model layer where there's more switching.
21:50 Speaker 01 Like, I think a consumer chat GPT has a huge advantage. Like, once that that behavior is default, even if like Claude is maybe better, I don't know if it is or not. Like, everyone knows chat GPT, I don't know if you saw OpenAI Dev Day yesterday, but they're clearly doing this platform play within chat GPT now, where it's like you have apps within chat GPT. I'm sure they'll use that data to sort of subsume and or take over whatever the best first-party integrations are. So they're definitely doing that on consumer. For developer, I don't know that that same dynamic is there.
22:22 Speaker 00 What made you decide to focus on terminals? So, you know, we started talking years ago when you first started doing Warp.
22:28 Speaker 01 Yep.
22:29 Speaker 00 And even then, I think you had really interesting ideas about how to rethink the terminal and how to use that as a launching point for all sorts of things.
22:34 Speaker 01 Yeah.
22:35 Speaker 00 Could you explain that thinking and how it's evolved over time?
22:37 Speaker 01 Yeah, so the the basic insider thing that got me excited about Warp to begin with is like, you have this tool that is pretty much a daily use tool for every developer. It's that and the code editor. And the terminal itself is something that, you know, really hadn't changed much in the last forty years. It's a tool also where it's like, if you get good at it, you can really get a lot done. If you use it, it like works across all these different parts of software development, not just code writing. On the flip side, from my perspective, not a good product, just like hard to learn, hard to use, hard to remember commands, super intimidating and just like, kind of like a gatekeeping vibe around it as well, in my opinion.
23:19 Speaker 01 And so the original concept with Warp was like, let's build a better product there and see if people will like using it. The business concept has evolved a ton. Like, the original business concept was like building a collaboration platform, which is like, we've we've just changed our model to be an agent platform because it's it's like way more demand for that than a collaboration platform around the terminal. But the the sort of core insight that this is an important tool, it's crazy. It's actually kind of been validated through all these agentic things that are very terminal first.
23:52 Speaker 00 You know, one thing that I that you mentioned I thought was interesting is that at some point, the model layer may commoditize in terms of its coding abilities.
23:59 Speaker 01 Yeah.
23:59 Speaker 00 How far on that asymptotic do you think we are? Or how close to that do you think we are?
24:03 Speaker 01 God, I I don't know. I think that the increasingly the limit that we see is context. And like the the reasoning capabilities of the models are pretty impressive. The problem is like, understanding an entire codebase, or understanding sources outside of the code, or literally just understanding user intent are challenging problems. I still think there's probably much more to do on the model side, but I don't know is the short answer.
24:33 Speaker 00 And do you think that from a model capabilities perspective, we've hit a point where, to your point, it feels like certain aspects of the models are slowing down in terms of the benefits or outcomes of further investment of certain types at least?
24:45 Speaker 01 I I think so. Like, if you take like Sonnet four to four five, and we're big partners with Anthropic, they have great models. Like, that was like a few percentage point increase on Sweetbench for us.
24:58 Speaker 00 Yeah.
24:58 Speaker 01 And we invest, you know, we've invested a decent amount to be one of the top agents on Sweetbench. And when we went from three, seven to four, it was a much more significant
25:10 Speaker 00 Yeah.
25:10 Speaker 01 boost. So I, again, that's like not, I don't know what that means about the total underlying trends. I think something with GPT five was somewhat similar, like certainly an upgrade. And GPT five, I think, is actually pretty much on par, has different like feel to it and higher latency. But it didn't feel to me like as much of a step change as some of the upgrades before.
25:34 Speaker 00 Yeah, makes sense. What other areas of the AI dev world are you excited about?
25:39 Speaker 01 I am, um, so I'm really excited about not just like the interactive piece of agents, the way most people are working today, but what can you do if you can program against these agents? And so, for instance, it's like if you have a version of Warp that's like headless, for instance, you can put it in CI and you can start to do crazy things where it's like, okay, every time someone updates the code, make sure the documentation stays up to date. It's like, that's very annoying for a developer. And so allowing developers to automate parts of their job that they don't like doing, I think is like a big capability. And then from a business perspective, just like automation is a better place to be than productivity enhancement.
26:23 Speaker 01 Like, one of the challenges with our business, I think with a lot of the coding businesses, is just like proving the ROI. Like, and there have been these studies that show like, You deploy this stuff on real code bases. It's kind of unclear if it's actually having an impact. Whereas if you get something that's more outcome oriented or more just like an automation, I think it's easier to prove the ROI. And then you're also not limited by time spent behind keyboard for doing this type of stuff. So from a business perspective, I'm very excited about like, what's unlocked if developers can program these agents.
26:55 Speaker 00 Well, that's fascinating. Thank you so much for joining us, Diana Pryors.
26:58 Speaker 01 Thank you for having me. This was great.
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