Scott Wu of Cognition AI on Devin becoming teams' top code committer and the coming golden age of software engineering

campaign by Tesla totally to go and work with the Kardashian that's sort of the final boss of influencer marketing right um and so I saw people speculating on that um but uh it'll be interesting to see where it goes uh well we have Scott l in the temple of Technology welcome to the show Scott there he is f good to see you guys how are you we're great how are you good good good busy couple days for us but oh yeah what's keeping you busy oh there's always I mean there's always so much stuff going on I feel like there's there's there's there's new products that come out every week There's new models that comes out every week and then you know we obviously have a lot going on with uh with Devon so well we appreciate you taking the time uh could you give us kind of just an over way real quick uh Scott and I talked on the phone I think it was maybe 5:30 or 6 Friday night and he was like yeah everybody will be here until probably you know what what did you say what's your normal you guys have a pretty intense we're usually we're usually still around past midnight yeah yeah busy schedules for us hopefully it's fun you clearly haven't put yourself out of a job yet uh but can you give us the update on kind of like where is cognition now obviously like massive launch huge like going direct moment uh great launch video uh and then you know you kind of went into build mode we kind of haven't heard that much from the company so can you give me an overview of where the products are where the company is uh and kind of set some uh some some ground rules for for Where You Are yeah yeah yeah absolutely so we had our initial U announcement about a year ago actually at this point um and uh and from then a lot of it was was basically just going through all the all the frictions of software engineering you know the the truth is engineering is just so messy in the real world if you think about um you know what has to get done obviously there's some pretty hard logical problem solving type uh work that has to be done but there's also a lot of practical stuff um and so you know figuring out how to to to to have a clean experience that slots in figuring out how to work with all these Enterprise customer code bases um um figuring out the the the capabilities and working with logging and documentation and tooling and things like that um and so you know for for a decent chunck of time our main work actually was with larger Enterprises um and so we would work with a lot of these these different groups you know um bigger tech companies um you know Financial Services uh or or things like that um and work with them on on a lot of these bigger projects and more repetitive projects and have Devon um basically come in and and speed up the job for a lot of this stuff um and then in December we uh we rolled out our our general availability um and uh you know it's a self-served plan where you can just put put down a credit card and get started and plug in your code base and have Devon um and we were super super excited about that obviously because it's uh you know really the the chance for for everyone to just get to try it out and see how it is and um it's it's been a fun last few months for us it's been a lot of iteration and a lot of growth and so on um we've had users talking about how how Devon's Now quickly become uh become the number one committer in their code base and so on and so it's it's very cool to see yeah c can you talk to me a little bit about the decisions you made early on on where to kind of put your AI efforts like as I understand it you didn't train a foundation model you didn't do one of the massive runs you you work with different model providers but what considerations were made in the early stage and are you still sticking with those or have those evolved over time yeah yeah yeah absolutely so so we had you know I I would say two two major bets that we really um started the company with and I would say the first one was um you know that that reasoning and and this whole RL Paradigm was going to work um and this is you know this is a it was a pretty controversial thing I think around the end of 2023 because most of what you know the first generation of AI was um or or you know the first generation of of of language models was was more like imitation learning right it was basically like read all of the internet you know read every Reddit post and talk like somebody on the internet right and and obviously I mean it was pretty incredible you know we passed the Turning test Chachi was a massive you know and for a while all of the work that was being done and all of the products that happened in particular vertical were much more um in that style which was basically you know I'll call it text completion basically right and so um you know you had had these you had product like that in marketing right you had a product like that for for customer support um and similar things for code where it's kind of like here here's the code so far and just predict for me what line comes next right um I I think we had a strong view that uh um yeah that that this reasoning was really going to work and was going to enable a lot of new use cases um and then the other thing that we felt really strongly about was that the product experience was going to shift from this kind of more Q&A text completion style product to um basically an agent you know and practically I think what that means is I honestly I think a lot of folks today still think of AI as kind of um you know a better Google call it like you have a question and you want to go search it up you know you ask your AI and your AI has a better answer which is Big obviously I mean Google's not a small company right but but I think the um I think the actual Vision that we're going towards with AI is actually even bigger than that which is basically you know your your buddy that does your chores for you right um and and the the the obvious difference between those two is the ability to actually interact with the real world and do real tasks and so on right and so you know there's there's a big difference between having a a a legal Q&A for example versus having a lawyer that can actually go submit things for you that can go and you know um um interact with all these different surfaces and the same is is obviously the case in code right where it's you know this is how we build software right it's is you you you you write code you run the code you see if it worked or not you run run the test you look at the documentation you know you click around on the product yourself um and this is how we this is how we iterate and build right and so the the ability to do that is is is a big step function difference yeah how do you think of getting Devon to go from sort of this reactive experience where you talk to Devon like you wouldn't uh you know a teammate or employee and say like hey can you help me sort of execute on this specific thing it goes into does it you know maybe comes back to get you know feedback at different points to I imagine longterm you want the sort of proactive sort of like high high agency agent and yeah how you know I'm sure you guys are already experimenting with that kind of thing internally but uh you know what are your plans along sort of that route yeah yeah for sure and so you know the way that we kind of think about it is um turning all the Brick Layers into Architects is almost you know as how I would describe it and um you know I think the the beautiful part of software engineering I would say is getting to do this core you know problem solving and decision- making around what do you want to build right it's it's like you know let me understand the problem let me understand what's exactly what exactly is going on and then let me figure out here's exactly the solution that I want to build for this right um the thing is you only spend about 10% of your time doing that you know as a software engineer in practice you probably spend about 90% of your time you know dealing with your kubernetes and fixing your unit test and upgrading your your thing to the new version and all of this other stuff you know fixing these bugs that come up right um and so a lot of it is the way I would kind of describe it is is working with Devon as um as the implementer that allows you to be a really great architect right and so um there's there's a lot of detail with that because naturally you have to be in you know all the same flows that that humans use for software engineering if you want to do that right and so you have your logs on data dog so like you know deon's got to go look at those logs right you're you're talking about issues on slack so de's got to be in slack right and a lot of it is is really kind of figuring out the work flow where um where it's it's very natural and very easy that as you're talking about this idea that you have or this new feature that you're trying to build or this bug that you're trying to fix or whatever you're able to just tag Devon and just say hey at Devon can you take a look at this and uh and and make this fix or do this thing yeah yeah talk about you know specifically I can imagine that Devin because it's so embedded in in in these different workflows uh you know there's every single day we see you know conversation on the timeline from somebody that says I'm switching from you know this code Editor to that code editor or that code editor back to this code editor how do you think about you know sort of long-term Moes and sort of lock in as you know you're You're Building Devon for yourself but then you're also you know trying to build a you know you're already a billion- dollar company eventually you know uh I'm sure you have uh much much bigger Ambitions but how do you think about sort of long-term Moes and and you know uh around the sort of like software engineering agents sure yeah you know I I I think in the the short and medium term it's um there's a lot of different experiences in code and and you know I think a lot of folks building kind of different different product experience for for for different verticals or use cases within code um I think in the short and medium turn it's you know things are just changing so quickly that the natural thing is just whatever is able to help folks the most is is what they're really excited to use right and and I think there's um um there's just you know when when the pace of development and also the pace of progress in AI is as high as it is um I think that's going to be to continue to be the case for a while um you know I think with that said in the long term I think these things naturally do kind of converge to a point and there are a few particular pieces I would say that that really kind of cause that and one of the big ones that I'll just point out is you know there really is a lot of um in most spaces you know we would call this personalization or something of that sort but but there's a lot of it in in code right I mean if you imagine you hire you know the smartest software engineer in the world uh and you know you get them to work on your code base day one it's they're not going to know a lot of these little details about here's why we chose to do this architecture here's what this function does and that function does here's how you do this database migration or whatever it is right so you know they have to learn all these things from the ground up as opposed to somebody who's you know just as smart but has been at the company for you know 10 years and built half The Code by themselves and you know they they wrote all of these files themselves and so on right then you know you get to a point where you really just understand the code base you're making the same decisions and trade-offs and you're working with it very tightly um it's the kind of thing where um and we see this already where it's you know a as as folks start using Devon more and more one of the really cool things is you know you can have one of your engineers ask Devon a question and Devon is drawing on the knowledge that it has from all of the previous sessions it has with everyone on your team right uh and it's able to learn all these things and you know if someone says hey you know we got to we have to go do this uh this version upgrade and Deon might say oh yeah I remember this I actually just did one just like this like last week um for this other part of you guys code base and so let's let's figure out this one and let's do this right um and so I think there's a lot of uh um that's kind of the shape I think of of of what we're going to see a lot in AI actually over the next couple years where you know this is this is a bit of a hot take but I would say a lot of the problem solving is actually good enough already you know a lot of the reasoning and the problem solving I mean AI has has been shown to be capable of solving some pretty hard stuff I I think actually what we have left to do is a lot more so just understanding the detail and the complexity of the real world right and you think about all these tasks that we spend our time on you know they they there there's some amount of problem solving but there's also a lot of just pulling in the relevant context and you know understanding what is the common sense what are the common sense considerations you're working with and and that's a lot of what we spend our time working on with Devon's capabilities can you talk a little bit about uh I like I have this take that we're almost in an AI winter for consumers even though AI feels feel like it's moving so quickly the chat GPT moment was so big because we passed the touring test that for most average people it's just Google search as you mentioned um but over the last year obviously if you're following this stuff there's been incredible break down models have gotten bigger context Windows have gotten way bigger uh has have there been particular milestones in in just AI research and development that have been more transformative to your business than others uh over the last year sure sure yeah you know I I think the uh at a high level you know I think all the the continued progress that we're seeing everywhere in AI actually is is primarily due to essentially like reinforcement learning RL that's that's really working and it is a very different Paradigm right where we're saying how in the past it was all just imitation learning and it's get as much of the internet as you could possibly scrape up and just train on all of it you know and hopefully you get something that that knows a lot of stuff right whereas this is kind of you know this whole reinforcement learning Paradigm is you know if you have a clear problem space where you can knew the problem 100 times and you know this was right this was wrong this was right this was wrong you know it's it's a little bit more like alphao you know this self-play learning um but in a language model right and and I think that's the the biggest Paradigm and you know folks like open AI anthropic and and and and lots of you know Google X and so on um have have have have shown a lot of real progress um through this whole RL Paradigm um to your point on consumer you know I actually think that uh I think that we'll probably see a Resurgence actually in consumer over the next uh the the next few months or so and I think one of the big things I think that will actually flip that switch is um is like a really great consumer agent experience you know it's there's talks about this we haven't had the we haven't had the moment of of just chatting with with a sort of generalized agent that can just book you a flight in a hotel and it's like super seamless and like that that's like what I feel like we've all been waiting for we've had that preview since Siri 1.

0 back in a decade ago and it still isn't here and we're still waiting for it but it feels like now it's actually just a couple months away yeah yeah exactly it's like I I want to buy this pair of shoes and just go and look on all those websites and find which one delivers and which one is the best price for that and just go buy it for me right like things like that where it's uh I I think that'll be that'll be a pretty big moment for folks because you'll really feel I think the difference of of how did you process the Deep seek moment uh obviously that that took over the timeline earlier this year uh it was it was very controversial in a bunch of ways but uh what was your what was your deep seek take away from that development yeah yeah no I mean I I think at a high level it's uh it's it's a competitive world out there you know I think there are a lot of a lot of really smart folks going after this problem and it's it's it's the kind of thing where it's you know if you think about like what what what people even not not just what was possible a year ago but what even people even imagined could even work one year ago or two years ago or three years ago I mean every year it's basically totally it's it's totally flipped right and now it's kind of like everyone in the space is talking about agents and the future of Agents you know when we were doing this like year ago no one really even believe that agents were like a thing you know and I think that uh um yeah no I mean it's it's it's the case I think everywhere in the stack and you know we'll see you know I mean there's the there's there's the GPU layer there's the hardware layer you know there's the foundation models and so on but but I I I think I think all throughout the space you know you have these these really really smart folks and really smart teams that are going after the problems and um and and basically pushing things forward you know I think we're in a very high velocity period where um it it really does feel like every month in AI is is like a year you know in a lot of these Tech Industries in the past and so um so yeah how is how is AI adoption what's been your takeaway from AI adoption within the Fortune 500 right you see all these companies are spending billions of dollars on like Genai Consulting contracts with Accenture it feels like the Consulting companies are probably doing more revenue from generative AI than like all of the software companies combined maybe ignore you know uh open AI um is it happening sort of Bottoms Up like an engineer sort of comes to their team and they're like you know it's they're they're in uh you know not not on not in San Francisco or New York and they're saying hey guys I got this like guy named Devin he's 500 bucks a month and like I think he can do you know what what you know our next 10 Junior Engineers can do or is it happening more so top down where execs are super you know kind of clued in and following the stuff or or or both like we need an AI strategy yeah yeah yeah I mean I think the interesting thing with the these times is um there's a lot of both you know and and Executives obviously and boards for example I mean everyone is thinking about how do we get AI native and how do we make sure we're on top of this wave and how do we make sure we're ready to to just accelerate as fast as possible uh and that we're ahead of the curve on this rather than being too late on it right because um obviously these things are moving so quickly and then at the same time you know it's like you have individual developers and and folks like that who who are are just really excited to use these things I mean it's you a lot of these painful tasks I mean if you're if you're doing a full code-based migration and your your your code Bas is you know 50,000 files and you got to do the same migration on every single one I mean it's it's not a fun task you know and and and figuring out how to H how to go quicker on those things so you could spend more time on um on the problems that you really care about and on uh you know figuring out what to build is is really exciting for folks as well but yeah I mean I I think it's an interesting time for us where it's you know it's it's buly I mean it's I think most of our waves and Tech you know there's always been kind of a a hype phase I'll call it and also you know a phase where basically you know this adoption really comes in and you saw the same thing with Cloud you saw the same thing with mobile I you saw the same thing with the internet itself right and yeah I mean I think it's an exciting one for us because I think with AI I mean I I think the um I think if anything you know I think the capabilities and I think what will be possible in AI are are are are just getting exponentially better and better every year but I I think what I would say is you know I think there's a lot of different uh the there's there's a lot of different areas um you know of generative AI where it seems very clear it's like you know this is getting better by the month this is you know this is uh uh this is clearly going to work soon and we want to be uh you know ahead of our time with this and get get ready for this and you know there are a few spaces I would say and and code is one of those where it's you know this is actively working right now I mean if your team is not using any AI code tool you are just heavily behind right and so it's it's kind of interest and I think we'll see each of these kind of come online at uh at different points in time and I think there are a few reasons why code is one of the first to really get there but but uh but yeah yeah it's going to be an exciting few months for us what what advice would you give the young Scott woo you know uh the younger version of you that's that's learning that's just starting to learn to code uh and and how do you sort of FastTrack to be kind of at the bleeding edge obviously you can learn from the models themselves they're great sort of instructors but um you know I think we went from this period where maybe a year ago everyone was like oh all the software Engineers are cook they sort of like made their own replacement to now it's very clear that if you're a software engineer today you have a massive you have more leverage than ever and you have this massive sort of edge because even if eventually all this work goes from you know code to natural language you know there there's still the sort of uh it's possible to be on the bleeding edge but but how would you if if somebody sort of uh 22-year-old uh coming out of college today what would your advice to them uh be yeah for sure no I mean really think I I really think we're coming up on the Golden Age of software engineering here and and I think the main thing you know as we're saying I mean I think it's always going to be up to us to decide what to build obviously right and a lot of the core of Computer Sciences I would just just say is that question of understanding and deciding what to build and so if anything I think the theory of computer science is going to be even more valuable you know understanding the the layers of abstraction and knowing you know the basic model of how computer works and how to break down problems logically and how how to reason with these um with these systems it's going to be you know even more valuable the other side of it I would just say is there's no shortage of demand for software you know and one of the things that I think about all the time is like um you know I I think today even still it's It Feels So outlandish but I think a couple years ago couple years from now this is going to be common place is single use software actually right and and you know you you can imagine a world where it's like hey you know I got to go look at these um these these 10 LinkedIn profiles today and I got to click through each of these and I'm looking for this and that and whatever and you know I got to go like search and get a bunch of data online and then put that into an Excel sheet and run some numbers you know a lot of these things are naturally code works just as well for these tasks if not better right but obviously it makes no sense at all to go hire some some some engineering team to go build you you know this this massive script that you're only going to run one time for this use case that you have today right um but I think I think we will get to a point where basically you can just ask Deon hey here's the thing that we need to do let's just go build this real quick right and and software will do that for you and will solve that problem for you um and I think there's just you know there's there's there's so many more products out there to build that's that's that's the main thing that I always index on it's it's crazy to think about but I think it's like um you know you can imagine all these products out there that are Niche products for for a thousand people or 100 people or even just for you but but you know they have the the level of quality and the level of execution as um you know the the the biggest products in the world today you know YouTube or Instagram or or whatever it is so yeah talk a little bit about you know there there's been a bunch of these uh sort of platforms apps that have popped up lovable.

dodev I think bolt. bolt.

new or bolt I forget what it is where you know these sort of products that allow you to just generate an apps immediately and and they're showing this tremendous Revenue growth you guys seem to have focused on the potentially much harder problem of sort of building durable software products but is there a world in the future where Devon goes more Downstream and is actually you know somebody comes on and creates their very first you know application ever with Devon because you know I see a lot of these companies pop up and and I have no idea what their long-term road map is but I can see why it's easy to generate a lot of Revenue quickly to just generate apps or generate websites but then you know maybe that's not you know the you know it feels like potentially a good wedge but not a super durable business necessarily which is like do I need to generate a new app every month like probably not but maybe you know yeah yeah no I mean I I think a lot of different product experiences in the space for sure I think the way that we've always thought about it is you know I I kind of think of self-driving as the parallel where it's you know there was first it was all manual and then eventually there was you know there's automatic shift right and then there was cruise control there was Auto parking you know and and and basically I guess the the kind of the thing that I would point out here is you know up until the point where it was true full you know it could do every single thing you wanted it to do you still needed a driver's license for all of that middle era right and and you know there was a point at the end where it's kind of like yeah you could just sit in the back seat and and just have the car do everything for you right and and so I I think we kind of have this this similar Paradigm I'd say in code um where it's maybe maybe not so um uh maybe not as much of a of a kind of like single step function switch but you kind of have this gradual Spectrum where you know there are a lot of tasks I think where you know yeah like you said building a cool website or something like that where it's yeah you know you don't have to have any experience with code at all and now you can just do this right um and then I think there are a lot of these kind of like larger and more complex tasks you know working on a big code base or figuring out things with your existing product or you know building as you're saying like a lot of this really kind of these bigger uh projects where um you know you still want to be an engineer and you still want to be really deeply technical I think to be able to to to make the most out of these AI coding tools and to to use that but with that said I mean I think that uh every month the capabilities change right and I think there will be a time I think where you you you're able to it's it's just as easy as kind of looking at your product and talking and complain English about what you want and that's it do you like the innovators dilemma framework and uh do you think AI is more in the sustaining ad uh sustaining Innovation camp or disruptive innovation Camp there's been a lot of uh debate about this people comparing it to mobile where the really large companies were actually the best position to take advantage of mobile a lot of people are saying Google even though their product road map has been a little lumpy there're they still have amazing talent amazing Hardware amazing software lots of talent to kind of reap the benefits of AI over the long term yeah yeah it's an interesting one I mean I think there's going to be a lot of interesting second order effects and you know one of the the the maybe the most obvious ones to call out is is basically a lot of these um a lot of these switching costs you know that exists especially in these B2B businesses are just going to go way down you know and I'm sure we can all think of these these companies that you know they only really Thrive today because it is so painful to to to to switch off and to migrate off right and I think that's going to change a lot I think on the hand I think a lot of as we're saying you know this deep personalization and um you know the ability to use data and to to Really build customer experiences for um for your for your users or your customers I think that is going to um only become more and more powerful uh and and so I think long story short is you know I think that I think that a lot of the the existing great businesses are going to do very well um in the age of AI I think there will be um you know in the neighborhood I would say if kind of like um you know the 10 to 20 power LOB businesses of the new ones that come up from AI you know and I mean I think we already kind of see it's there's there's the foundation Labs themselves and then there's some of the you know each of the big vertical of the application layer right there's code there's law there's you know customer support there's sales and so on right um there's there's image and video um and I think there'll be kind of like yeah like a handful of businesses kind of from each of those categories I think that that really make it to the really massive outcomes but yeah I mean as is always the case with these things you know a lot of it is it's it's very hard to know in advanc which ones will will be the winners um I do think that uh um yeah I I mean I do think with the richness I think of the space of AI you know I think one of the big differences is is there's just so much um difference in technical execution um where it's you know you can in in AI you can be doing things that other teams or other products just cannot do right and I think that difference kind of means that I think really great really talented new innovators will have a a meaningful Edge and the best one will be able to create some what's your take on the various walls there's been this you know deep learnings hitting a wall scale might be not all you need now it's everyone's pretty scale pilled then we got in the reinforcement learning Paradigm as you mentioned are you worried about a data wall or an energy wall or just some sort of wall where we hit and we kind of stagnate and uh and we and we're not seeing the like the breakthroughs and the acceleration that I think people are kind of expecting if you're W if you're following AI closely are you worried about any of those walls yeah I actually so I actually have the opposite take which I is in some ways optimistic some ways pessimistic but what I would say is stagnation is actually the default you know it's it's by default it's not the case that we're gonna have this you know the next and I think we've kind of like we we felt it for so long at this point that it's like yeah the next model is going to be even better and the next product is going to be even better and the next GPU is going to be even better but but but I I think more what it speaks to actually is is kind of the just yeah how how amazing the the the the kind of the flow of innovation is you know it's like and just to give simple examples I mean it's like you know gpt3 wasn't just more of gpt2 it was like uh you know it was a step function different and there there were a lot of things that that had to be figured out and gp4 wasn't just more of three it was like you know and the same is true I think with with reasoning the same is true with the advancements that we're making in Hardware it's the same as true with the advancements that we're making the application there so in some ways it's kind of you know I'm saying it's like there's there's no single kind of like force of nature that we get to rely where it's just like these things will get better all on their own at the same time it's it's it's it's it's truly remarkable I think that over the last few years you know we have we we we we haven't slowed down in figuring out the new Innovations and the new categories that will get us there so what is uh one thing that you learned from Eric and Kareem uh from your from your sort of ramp days that you feel like you you've really focused on uh making sure that you guys Implement at cognition yeah yeah you know it's a they they they've I've known them a long time I'm super super tight with both of them they they've given me a lot of incredible advice I'll share one which I think was hilarious which you know we were we were just getting started um and I I called Eric and I was like hey you know we're um we're we're starting this company um you know obviously like ramp is incredible I have so much respect for you and and what you built and I just want to get your thoughts on um basically yeah what what is the thing that I should really uh that I should really focus on today that I'm not thinking about right now and Eric said you know take a lot of pictures and it was it was I mean it was it was actually great advice it was funny because you know it's I would talk to these people and and all the you know they would say oh you know you really you got to really nail in on on hiring and you got to really like figure out these and all all these things are also true obviously and Eric has helped with all these other things but I I I found that funny that that was the first you know the day the companies founded don't forget to take those pictures and it's like the you know it's it's it's only been I don't know 15 months for us right but but it's uh I I am actually really grateful that that uh that we have those and that we did that and I I think there's a lot of things where it's just you know just just being in it and going through the experience and um and knowing what you what you miss and what you don't miss I I I think Eric and cre understand that better than anyone honestly well thanks for joining it's 1:30 uh we won't take any more of your time where can people sign up and and who should who who's kind of the Wheelhouse client right now yeah yeah for sure it's uh it's devon.

and um anyone who's you know I'd say engineering teams all over the world so so you know we have we have teams that range from uh one or two person startups all the way to to the biggest fin Financial Services firms in the world um and so um yeah would love to hear folks feedback on Devon as they're shying it out awesome thanks for joining for coming on Scott thank you guys so much for having me have a good one have a good one very interesting I always love talking to an AI founder there's so many things you can peel into we didn't even get into AGI timelines P Doom all the fun things that you can go from there you want a pen computer charger what oh charger here you go um and uh we're in we're in we're in demand today there are multiple guests trying to call in right now we can only let one in at a time or maybe we could do a debate between uh do we have two guest scheduled that would be cool I think we have yeah do we should we do a a VC and a car dealership guy at the same time I think there might have been some confusion over scheduling uh but let's try and in uh well there's two people in the waiting room right now we're we're not sure who joined but we want to let in the car dealership guy because that's who is scheduled next hopefully we can get him in the temple of technology and pick his brain about what's going on in the car World should be a fun conversation um but we got to figure out some some Zoom details yeah I love how the entire entire like stream infrastructure right now is melting down melting down yeah we're pushing this to the Limit folks we're building the plane as we're flying it but I think we're having uh I think we're having good streams back to back uh it's been a lot of fun and I I like these little conversations take us on a little tour go over into Finance land with Joe drone land defense Tech with saurin some AI with Scott woo now some car dealerships hopefully uh Ben how we doing with the car dealership guy is he ready to come on down to the Temple of Technology he left he left uh he says trying to join why don't you send him another message and uh I will I will pull up some info on this on this uh card deal oh he said uh he does a lot of these stuff so he says we didn't let in his main camera oh he has two cameras okay okay well let's see Nissan has a profitability problem that is determined to fix how a mix of product pricing and placement interesting Honda is sidest stepping some tariff uncertainties by reworking its battery sourcing strategy beginning in April Honda will Source hybrid batteries for nearly 400,000 vehicles from Toyota's 14 billion North