00;00;00;00 - 00;00;23;15 Unknown We are enabling the builders. We are enabling, like the creatives of the world to build new things. Jeff is just like the direct line. It's machine to machine intelligence. You just talked about more code, pushing more applications, pushing more products. Where do you see Jeff in that equation? I see Jeff as the intelligence per dollar. Like intelligence per dollar is a cornerstone of what at type safe is like our goal. 00;00;23;15 - 00;00;35;09 Unknown We want it to be as cheap as possible because that's what enables everybody to use it. 00;00;35;12 - 00;01;05;28 Unknown I am Ali Lobs I am the devil at type safe. I am our dev rail department. Okay I am both our our lead Devereaux and our most junior Devereaux. So yeah, it has been I mean, this is what the word unprecedented is made for is defined for. It has been. It has been absolutely mind blowing. It's just one of the most, one of the most bizarre experiences of my entire life. 00;01;05;28 - 00;01;26;04 Unknown And I think probably everyone at the company could say the same thing. It has been, you know, we've been working on this a long time, and we've been so close to this technology for a long time. And, you know, when you're really close to something, it you get very familiar with it and it becomes very normalized in your mind. 00;01;26;04 - 00;01;46;07 Unknown And it's like you remember, we remember we know that this is like a really cool thing and something that doesn't exist yet, and that it could be that it's really, really useful in a lot of ways. But like one, are we going to be able to convince people or, or the, the fear that can sometimes be in the back of the head is like, is it just actually not as good as we think it is? 00;01;46;08 - 00;02;10;06 Unknown Like, you know, what I mean is, are people going to be like, why would I want this? And so for it to, for it to have caught on like this as so it's so exciting and it is just mind blowing. I'm like, I'm, I'm, I'm at a loss for words to describe it because it is just something that is so outside of what we could have predicted. 00;02;10;09 - 00;02;29;13 Unknown You know, something I like to say is, you know, had we had we prepared for a launch this big, that would have been an irresponsible use of resources like that. Anyone would be like, no, like, don't prepare for one of the largest launches of all time. Like, that's just like, makes no sense. That would be bad planning. Yeah. 00;02;29;15 - 00;02;51;13 Unknown And yet, here we are. I'm incredibly proud of, like, the team and especially our platform team and how things like things are online. Our people are using it. It's in production, and it's staying up, for such a so much larger than we could have possibly anticipated. That's, like, such a huge achievement. And so, like, shout out to our platform team big. 00;02;51;15 - 00;03;09;07 Unknown What do you think? Besides obviously scaling the infrastructure, one of the biggest challenges that you're facing right now. Oh, the biggest challenge we're facing right now. So there's like there's a couple of ways to answer that. There's from from the personal perspective, there is the like making sure that everyone's taking care of themselves as we are just like sprinting like crazy. 00;03;09;08 - 00;03;36;17 Unknown You know what I mean? And I feel very I feel very fortunate to be under the leadership that we're under. You know, Diogo has multiple times in this past week and a half like we do like we do stand ups every morning. We have an all hands every week. And we do like a lunch discussion every day. And so and multiple times he's talked about like the importance of like balance and making sure that people are taking care of each other, you know, and that we're taking care of ourselves. 00;03;36;19 - 00;04;06;19 Unknown Because while we do need to like, put in as much as we can right now to meet this wild time that we're in. Like, he very much understands that. Like, if you put into much, your productivity will decrease. And it's worse than if you didn't put in as much. And so like we're we're all like pushing as hard as we can, but also being reminded by ourselves and by, you know, everyone else to be like, hey, it's okay. 00;04;06;21 - 00;04;25;00 Unknown Like, you can go home, like, this is like a well, we'll get back to this part in the morning. You know what I mean? And it's like that. That's really cool. So that is that is one of the challenges. The other challenge is, you know, it's for I would say for me, in Deveraux, the challenge is I want I want to please everybody. 00;04;25;00 - 00;04;42;22 Unknown I want to answer every message. I want to answer every email. I want to answer every discord message request. I want to be there and discord. I want to be talking to the builders. I want to be helping every project. And it's just impossible right now. And it is. It's impossible to hit them all. And so the challenge is figuring out like exactly where to focus. 00;04;42;24 - 00;04;45;12 Unknown And. 00;04;45;15 - 00;05;10;15 Unknown It's, it's a it's what we call, you know, it's what they sometimes call a champagne problem. Right. It's like it's a, it's a, it's a problem because of such great success. So it's not like the saddest problem, but but we really, really, really want to do right by our users. We are a very like, like builders oriented company where this is very all along this our product has been we wanted it to be for the people. 00;05;10;16 - 00;05;31;03 Unknown Right. This is for individual builders to build with. It is also, hugely valuable to companies. And we've got that, you know, we've, we've got our sales pipeline going and like we're, you know, working with a lot of different companies right now. And you're seeing us put into production from more and more places and, you know, that's that's going great. 00;05;31;03 - 00;05;54;06 Unknown But what we want to never lose sight of is that we are we want this to be for each individual software engineer. We want this to be a thing that everybody can use. And that requires like supporting the individuals. We give $5 a month, in free credits to all users. We, we, we have so far. And that is like a companies don't need that. 00;05;54;07 - 00;06;13;11 Unknown Right? Companies, they can just like whatever throw $100,000, whatever it is that they need into their account and just like get going and experimenting. But individual builders, sometimes even $5 for plenty of people in the world that would be like too much. So we want you to be able to get in and build with it right away and at our prices. 00;06;13;11 - 00;06;32;06 Unknown $5 is a lot of tokens, like, you can do a lot. You can put something live in production on $5 a month for a lot of like indie projects. So that is such a it's such a focus for us that we want to we want to enable the builders of the world to get to like use this. Yeah. 00;06;32;07 - 00;06;51;11 Unknown I think my next question. Just because there's, there's so many people, obviously, having heard about Jeff, we just you just gave an amazing speech of like, all the tips of how to use it. Can you explain for somebody who's just heard about the hype on X, what exactly is the difference? Like, why is it such a big change? 00;06;51;11 - 00;06;54;25 Unknown The succinct version is. 00;06;54;28 - 00;07;26;04 Unknown Jeff is a way of accessing the intelligence that is within these these eyes, these systems, you know, these these models that we in the present day call AI like there's intelligence within them. And Llms provided a way of tapping into that intelligence, but it provides a way of tapping into it in a very narrow way, only through the context of like generative text output that has been reinforced. 00;07;26;06 - 00;07;54;15 Unknown You know, the three reinforcement learning has been designed to be like pleasing output to do, to follow instructions. And this gives an entirely different way of accessing that same wealth of information, that wealth of intelligence inside these models, but through something that is far more expansive and is for machine to machine communication, you want your code to be able to use intelligence within its software. 00;07;54;17 - 00;08;25;26 Unknown And that's not what Llms were made for. They were made to chat, they were made to produce text. Yet we've bent them over backwards to get them to output text that represents a human user interface to a computer. My mind is blown when I think about the way we're using Llms, where we're like taking we're taking the intelligence, we're turning it into text to interact with an interface that was already to access something in a computer. 00;08;25;29 - 00;08;47;09 Unknown We turned it into a human interface. Then we get the LMS to output text to be able to interact with the human interface, and then it goes back into machine language. And it's like we started in machine space and we ended in machine space. Yet we did this extremely expensive bridge through like text and through like a human interface layer. 00;08;47;10 - 00;09;09;01 Unknown Why, why if it's if it's from machine to machine, that's all you actually need to get to. This is an incredibly expensive way of doing it. And Jeff is just like the direct line. It is just it's machine to machine intelligence. That's very interesting. Reminds me a lot of that discussion. I think a lot of I speak to a lot of other dev roles as well as engineers, founders in the Valley. 00;09;09;03 - 00;09;38;19 Unknown Some of them say that at some point we will just be writing mathematics at any point. So the translation layer will actually be a new programing language that is solely based on linear algebra or. Yeah, just I could see that I'm not as familiar with like the actual like the, the mathematics like within these things. But I do think, I do think that is one of like the really interesting things about this, like AI revolution that we're in is it's not like all the things that the AI can do. 00;09;38;19 - 00;10;05;20 Unknown I like, I like that it's a different approach to computing, you know what I mean? It's like it's not like you said. It's like it's it's linear algebra instead of like binary arithmetic. It's such a it's such a shift at the very lowest level of what computing means. And I think, I think we've only scratched the surface of what that will actually mean in the long term, even in the medium term. 00;10;05;22 - 00;10;34;12 Unknown Yeah. You said let's turn to around a little bit more towards the product. Again. Can you give people a practical grasp of the possibilities that are now enabled through Jeff, like some use cases, some tips and tricks that you just mentioned first? Yeah, a practical grasp is just like this is the hardest part about talking about Jeff and teaching people, Jeff is that it is such a it's a category creation product. 00;10;34;12 - 00;10;49;20 Unknown That's a term we used a lot leading up to it because that like drives a lot of the strategic thinking about how to present this to the world. It is a category creator. A category creator is very can be very challenging to get people to wrap their heads around, because it's not just coming in as a better version of something. 00;10;49;20 - 00;11;20;03 Unknown We're not an alarm, we're not a better version of LMS. Like we sit in harmony with LMS. We play certain things that I think we're using LMS to do in a really weird, backwards, incorrect way. But we don't replace LMS on the whole. So it is there are there are simple use cases to think about. The simplest way to think about where Jeb fits in practically, is thinking about any place where you're using an LM to do, like classification. 00;11;20;05 - 00;11;54;23 Unknown Some people think of Jeb as a classification model. Fine. That is one of the ways that can be used. That is one of the things that it does. So if you have a classification shaped problem in your, in your software and you're using LMS to do it is almost certainly a better drop in for that, right? If it's categorizing emails, if it is, if it is categorizing a financial transactions, if it is categorizing these or if it's scoring, you know, if you're scoring things, you're having an decide like how good, how bad, you know, how much of X, Y or Z Jeb like fits into that really easily. 00;11;54;23 - 00;12;13;08 Unknown And so those are the those are the first use cases that come to mind. And those are the ones where people that are like putting us into production, like really quickly. It's because they already had problems, like I call them. Jeb shaped problems like they already existed. They were maybe using a more expensive, slow, less effective tool for that. 00;12;13;08 - 00;12;40;24 Unknown And now there's a better tool. Great. Drop it. In the other case, though, that is far more exciting to me. Is that true category creation side of things. And that is where, because Jeb is so fast and because it is so inexpensive, and you can put Jeb inside the software loop like you can put, we call the the questions that you send to Jeb, the decisions that it's making. 00;12;40;24 - 00;13;11;07 Unknown We call them primitives on purpose because we want people to think of them as the lowest level components in your code. Some people, it's helpful to describe Jeb as a smart if statement or a smart switch statement is like an intelligence infused logic gate. So when you think of it like that and you really think about, oh, at the lowest level anywhere, where there is logic switching happening in my code, what if what if I had intelligence there instead? 00;13;11;09 - 00;13;40;25 Unknown Maybe you're doing a complicated regular expression. Maybe you haven't even built it because you conceived of what the code would need to do. And you're like, yeah, but that would be like way too hard to like, figure out if blank, therefore do X or Y or Z. But maybe Jeb can now unlock that that it becomes it's like a we call it a primitive because I think in a lot of these use cases, it will be a truly new like path of code that couldn't exist before. 00;13;41;01 - 00;13;57;21 Unknown And now, because it's there, you can I'm going to drill down a little bit deeper. I hope you're okay with that. Please. Just because it's been amazing to watch from the outside on X Twitter, all the things that people put up. But then more often than enough, you see people building a snake game or building like some other thing that we've seen before. 00;13;57;26 - 00;14;13;26 Unknown Yeah. What are some of the use cases that have really surprised you in your team? You know, it's the funny thing is people ask me this and I should have better answers off the top of my head. There have been so many and my brain's like, so fuzzy from the the, the the fervor. I'm also drawn to the very like to the toys. 00;14;14;00 - 00;14;35;16 Unknown Yeah. Like my what stands out most to me. What I remember is the like silly experiments people have been making Jeff talk, using it to actually generate text by like looping and asking Jeff like what words should come next? What word should come next. It's a it's hilarious because it's like bending Jeff backwards to become like an LLM again. 00;14;35;17 - 00;14;51;24 Unknown And it has a like a personality to it. That's very silly. Like we have it hooked up in our in our slack, like there was an open source code base that someone made. Now we can talk to it in our slack. And we all think it's very like adorable and charming and like, dumb. And it's fun. Do you think Jeff would have pink hair as well? 00;14;51;26 - 00;15;13;18 Unknown Oh, that's a good question. I, I feel like Jeff like, talks like a toddler kind of it. It talks like Rocky from from, you know, from a project Hail Mary. Right. We someone pointed out that out there, like, it's like Rocky. It's like it speaks so like yes. No bad bad bad. It'll like like literally will do that. 00;15;13;19 - 00;15;33;14 Unknown And that is like so those are the things that like, stick with me at the top of my head. And I think as a like that's also what like keeps me going like with this wild fervor where like currently in, it's just like because like I said earlier, you know, we we are enabling the builders. We are enabling like the creatives of the world to build new things. 00;15;33;14 - 00;15;57;17 Unknown And so those are what just like energize me the most. But it's really cool seeing things on all sides of the spectrum. And I think, I think one that has been really interesting to see is like real time analysis of like speech, like people talking. I think there's a lot of potential in this space and have already seen some, like really interesting projects come out. 00;15;57;19 - 00;16;23;26 Unknown Labs put out like 11 labs, developers put out a, a video of like using it to using their like real time transcription, like feeding into Jeff. You can do like analysis of what you're saying and it can. So it can sort of be like a speech coach in real time. I built a teleprompter project that that does something very similar, shows you what, like bullet points you have. 00;16;23;28 - 00;16;37;04 Unknown Like you could have it in a teleprompter right now of like all the questions that you wanted to ask. And it doesn't matter what order and they'll just disappear once you've asked them because it's just Jeff will be like, oh yeah, that question was asked. And you can just call it over and over and over and over again in real time. 00;16;37;08 - 00;16;55;10 Unknown It's those real time use cases that I'm most excited about and that I think is really going to be that's going to be really the the cool stuff. So you say like for example generated if you I is that something generative. You. Oh okay. There's there's a good one generative UI I think is a is that's a super cool one. 00;16;55;10 - 00;17;10;21 Unknown And that's something that we a lot of people's projects I can name like a demo that I made on our lead up to launch, like when we were experimenting with different demos for our launch. I made like a lot of tiny little experiments. And so a lot of what people have been like better versions, more complete versions of stuff. 00;17;10;21 - 00;17;33;20 Unknown I experimented with generative UI, never even thought of, like never even went into. And I have a personal belief that generative UI is going to be a huge part of how we interact with computers in the future. I think that more and more, what people interact with is just going to be tailored to exactly what they need to their style, to their skill level, to like just to their to the personal person. 00;17;33;23 - 00;18;02;06 Unknown And y show a whole bunch of options that you don't need. If the AI, if the system can be smart enough, infused with intelligence to basically like, well, you probably want one of these three and can quickly figure out the one that you do want. And that will make things so much better, frankly. You know, computer, those of us that are that use computers all day long, we can take it for granted that we can use them effectively, that we're proficient in them. 00;18;02;08 - 00;18;21;28 Unknown I try to really stay in touch with people that are like completely outside of the text. Fear, right? Even the, the, the things that we think of as like very like public friendly, like, you know, modern smartphones, like things that are like you made to be, you know, hardcore tech people will be annoyed because it's like, oh, you can't hack into it and it's so simplified or whatever. 00;18;21;28 - 00;18;40;16 Unknown Even then, these things are hard for people to use. They are. People get so upset when there's like an OS update, and now all the buttons have changed and us techies, we can learn it really quick. There are people out there that like, that's the most dreadful part of their years when they're forced to upgrade their like phone OS and they have to like, figure it out. 00;18;40;16 - 00;19;01;08 Unknown This isn't just like your grandma. It's a lot of people. It's a lot more people than people in the tech bubble can oftentimes think it can remember. So the world of generative UI and like making it so that it can truly be tailored to people, I think is going to increase the accessibility of software and everything that a computer can do to so many people. 00;19;01;08 - 00;19;26;03 Unknown And I think that is that is a really, really like, energizing thought. I'm a big proponent of like accessibility and like lowering the, the, the bar of entry into anything that I love doing. I want anyone in the world to be able to get started in that thing. I have no interest in gatekeeping. I have no interest in being like, oh no, you need to be like, you have to have like studied or done this to be able to like, get into this. 00;19;26;03 - 00;19;49;00 Unknown It's like, no, if you can just do it right away, that's better, that's better. It makes more creatives in the world. So yeah. Yeah, no wonderful rant. Let's talk maybe segue on that. What do you think Jeff could which role do you see Jeff playing in this entire builder economy that we are now experiencing? Right. You just talked about non-technical people being able to access UI better. 00;19;49;03 - 00;20;18;19 Unknown Very likely. They're also I mean they're pushing right now also more code, pushing more applications, pushing more products. Where do you see Jeff in that equation? I see Jeff as eventually it will be a tool in every engineers tool belt. It will be. I like to compare Jeff to Docker and AWS Lambda serverless function execution. Both of these are products that I see as when they first came out, they were hard to learn. 00;20;18;22 - 00;20;32;13 Unknown It was a totally different way of thinking, and a lot of people would be like, this isn't worth the trouble. Like, why do I want to learn containerization? How to spin up Docker container? I already know how to set up a server. We've been doing it for decades. Like what's the big deal? Or serverless function execution? Even weirder. 00;20;32;13 - 00;20;53;27 Unknown Why would I want. What do you mean? Like I'm going to run a JavaScript function without a server. Like very bizarre. But now you can't be in the infrastructure space without being super familiar with both of these. Or at least like knowing that they're available tools and likely the right tool for a whole lot of jobs. And I think Jeff will be that for people in the future. 00;20;53;28 - 00;21;11;05 Unknown Like you'll just always know that, yeah, of course you have a decision model, like you're going to use that like a, like a regular expression. Like people know that regular expressions exist. It's the wrong tool for a lot of jobs. It's very much the correct tool for some jobs. I think Jeff is the same way. You know, it is the wrong tool for plenty of jobs. 00;21;11;05 - 00;21;31;06 Unknown When it is the right tool, it is the right tool and it just needs to be there for for everybody. And, you know, that's a big part of why we also just have such a focus on the intelligence per dollar, like intelligence per dollar is a cornerstone of what at type safe is like our goal. We want it to be as cheap as possible. 00;21;31;11 - 00;21;54;23 Unknown Measuring intelligence, whatever the ephemeral unit of measurement of intelligence is divided by dollars. We want that to be as as close to zero as possible, because that is what enables people. That's what enables everybody to use it. Beautiful. Yeah. You just talked about the learning curve on Jeff. You said it's not the tool for everything. Can you give us like you just did before, some practical tips. 00;21;54;24 - 00;22;24;22 Unknown Like what is your piece of advice as somebody who's used the tool for much longer than most of us, how do we use it best? It's that's that's a really good question. I think Jeff is so much easier for people that have been engineers for a long time to grasp, because people that that have been programing, especially for decades before the advent of AI, before the advent of the first time you could ever even ask ChatGPT to write a little bit of code for you, we had to design systems by hand. 00;22;24;26 - 00;22;53;28 Unknown They'll hold artisanal, artisanal, you know, crafted by hand systems. And Jeff, for for people that are already familiar with that way of thinking about software, Jeff fits in very easily. It's like, oh, I get it, because you've designed systems for so long, but we have this incredible world of people that are getting into creating software in the era of AI agents, in the era of coding agents. 00;22;53;28 - 00;23;26;08 Unknown And I think that's wonderful. There's a whole nother, yeah, passionate ranting conversation that go on about why I think that's a wonderful, wonderful thing. So I would almost say like to the to the old timers like me, I don't really need to explain how to think about Jeff. You're going to you're going to get it right. You're going to you're going to understand it's the it's the people that are less familiar with that kind of like systems engineering that I really want to, that I really want to be able to speak to and have them understand, you know, and there's there's a couple of different approaches. 00;23;26;08 - 00;23;50;21 Unknown One is tell your AI agent to look at our documentation. There are there are some there are some great like skills that the community has made. There's like a couple of them that are both called. It's basically like a brainstorming skill. It's like, look at my project and understand this about Jeff and like, let's brainstorm how it could fit into it. 00;23;50;21 - 00;24;08;06 Unknown That can work really, really well. We were even going to make an official brainstorming like skill as part of our skill package. We didn't get around to it before launch, and it's awesome to see that, like the community you up immediately did that. It's almost nothing that we need to make now because everyone's making it all so cool. 00;24;08;08 - 00;24;43;06 Unknown But that's also like that's a little bit hand-waving. Oh, just tell your agent to do it right. I do want people to be able to understand it. And it's it's thinking about it as, as the lowest level bits of a system is, is the most important part about wrapping your head around it? It is anything you can do to kind of wrap your head around the idea of like smart logic gates or like smart if statements, and if that's not something that you're immersed in, it can be it can be harder to visualize it. 00;24;43;09 - 00;25;06;29 Unknown And but you want to break it down into that, into that. Like how does the code flow through your system? What is actually happening? Imagine the branching paths in like what can happen, you know, even if you've completely vibed it up and you haven't looked at the code, look at the behavior of your application, right? You click on a button, you do a dropdown, you do some user input. 00;25;07;00 - 00;25;32;26 Unknown And this happens instead of that happening. Right. Those are decision points. And if those decision points are deterministic as most decision points are in software, it's just like comparing a true and false or comparing, you know, whatever. Yeah, that's happening like a bazillion times of microsecond. That's great. But then do you need to branch on something that requires like some intelligence? 00;25;32;27 - 00;25;59;13 Unknown Do you want different behavior based on something that is harder to do with just arithmetic, something where it might be user input, semantic input, speech or or typing? Is it something that is, if you do, if you were to try to like sketch out like a, like a flowchart of behavior and for one of them you're like, well, this is more like a, it's like a gut feeling, right? 00;25;59;14 - 00;26;18;19 Unknown I can't define it mathematically. I can be like, what if it's, you know, if it's like this, if it's this vibe. But she goes, if should do that, and if it's this vibe, it should do that. That's probably a spot where Jeff could work, right? It's that. It's that. When do you need probabilistic, you know, vibes based logic switching. 00;26;18;19 - 00;26;49;21 Unknown And that's where to think about Jeff. Yeah, I really like the other examples. Well, that you told me about earlier, which was, the idea of speculative prompting. Yes, yes. Speculative prompting is it's one of the first things I ever wrote about in our documentation is actually the very, very, very first project I built with Jeff. I used that technique like it was intuitive to me, but I also understood that it's probably not going to be intuitive to people. 00;26;49;21 - 00;27;10;01 Unknown It's not intuitive to coding agents. They don't do it by default. You it seems inefficient, frankly, if you think about it from like in most traditional like uses of APIs and stuff, it's not how you would use them. You, you, you would call the minimum amount you need. You don't want to do extra work before you need it. 00;27;10;07 - 00;27;33;18 Unknown But and you're right. So this is a very it's a very unintuitive way of thinking about it. But speculative prompting is when you anything that you might need to know about. The thing about the the state that you're evaluating, which is like the input to to Jeff, ask it all at the same time, right. Even if you don't know if they're going to need those questions, you only need the answer to that question. 00;27;33;18 - 00;27;53;26 Unknown If your code branches down this path, which is going to be dependent on the answers of some of the other questions, ask them all up front because you want to get them all in one like round trip to our servers. You'll get that in like 150 milliseconds. Now you have all of those answers. Our costs are so cheap per token that it's almost certainly going to be worth it. 00;27;53;28 - 00;28;10;02 Unknown And now you have all of those in advance, and your code can do a whole bunch of interesting logic because you already have those answers. But if at each point in that branching logic, you're reevaluating, oh, okay, it's a billing ticket or it's yeah, it's a billing ticket. Now I need to know, is it a refund request on? 00;28;10;02 - 00;28;29;25 Unknown I got to ask Jeff again. It's like, no, no, no. Ask upfront to say is it a billing ticket? And then also ask is it a refund request? You know you're only going to care about the answer to that second one. If the answer to the first one is true, but ask them at the same time. It's a very small amount of additional extremely cheap tokens to ask that second one. 00;28;29;25 - 00;28;47;27 Unknown And now you don't have to do another round trip. And frankly, oftentimes if you do need to do another round trip and send the entire state again, might actually cost you more. So that is like it's such a it's such a powerful way of using it because you lose the speed benefit if you do a bunch of sequential calls. 00;28;48;00 - 00;29;13;18 Unknown A tip that I always, when I'm vibe coding up something with Jeff after like a first sort of pass on the project, I'll tell the coding agent, I'll say, hey, if we are ever sending the same state to the type safe API in different places, we should almost certainly be bundling those into one call up front. And pretty much always the the agent is like, oh yeah, we are doing that because we're doing it sequentially. 00;29;13;18 - 00;29;32;28 Unknown But now I understand and I should put them all in the same thing. So there's like, I think people are going to need to have to like really push their agents to do that less and less over time. As, as system one models, as decision models become, like ubiquitous in the way that we think about this, it becomes in the coding agents training data, they're going to be good at it. 00;29;32;28 - 00;29;50;06 Unknown But right now we really need to hold hold the agent's hands. Yeah. No, I think you're right. It is a paradigm shift and we have to adopt a new model. I guess that that's what comes when you open up a new category of of AI model. Let me shift focus a little bit and ask you one more question before I'm going to let you go. 00;29;50;08 - 00;30;12;04 Unknown Of course, we're here at the Jeff Hatton with the Air Collective at the hackathon Covid HQ. What are the projects you're excited about? What have you seen so far? What are you looking forward to seeing that demand? I haven't seen any projects yet. I've been I've been doing interviews since. Since the intro. I haven't seen any yet. 00;30;12;06 - 00;30;36;26 Unknown What I am, what I'm very excited about is that one of the judging criteria in today's hackathon is novelty is like coming up with something like, really new. And as I've talked about multiple times in this interview, like that's what gets me the most excited. Like I want to see people and I hope I gave enough. I think I gave enough in my introduction speech of how to think about Jeff, that it's going to spark some of these ideas in people's heads. 00;30;36;26 - 00;30;55;28 Unknown I, I hope we get some of the, the, what I call the drawing board ideas where people are going to be like, oh my God, I hope. I really hope that someone pulls an idea that they have had for a long time that always felt infeasible. And now that they learned about Jeff and they heard what I said, they're going to go, I think I could actually do that. 00;30;55;29 - 00;31;12;02 Unknown I want someone's old idea to come to life that was basically impossible before, infeasible before, and now they can make it today. That's that's what I want to see. And I'm, I'm going to I'm going to be coming back almost certainly for the, for the judging because I want to see I want to see what people built. Awesome. 00;31;12;03 - 00;31;25;15 Unknown Well, what a wonderful way to round it up. Thank you so much for taking the time and best of luck with everything you do. I think it's fair to say that we're all very excited to see. Absolutely. Thank you for having me on. Yeah. No, it's been great.