The State of Startups in 2026

0:00Frankly, some of the most powerful and badass founders that we've been seeing lately, there might be in their late 30s, 40s, even 50s. I mean, there's a sort of resurgence of the experienced founder. A lot of people seem to say that they want to be YC for solo founders, but it turns out YC is the YC for solo founders. What a weird moment we are in history where you wake up in the morning, you like wire up a new model, and then these things that even a month ago, you're just like, why isn't it working? It just starts working. Welcome back to another episode of the Lightcon. At YC, we work with thousands of founders per year, which means we start to see things before they're obvious. So we wanted to share some of that with you today. What's the state of the art and what's coming next? What should you, the builder? No. Let's get started.

1:02Diana, you have a few things to share with us. So we did a bit of a analysis for all the companies we accepted in the last 18, 12 months, and we have some pretty shocking stats to share with everyone. So one of the big ones is the number of heart tech companies that are in the batch. It has gone from 8% to 20%. There's a lot of underlying reasons why that has happened. We will go deeper into that. The other one is the rate of growth of companies and what YC does to the companies has accelerated. So the median YC company when it gets accepted is at zero in revenue, it's pre-revenue pre-product. And by the end of the batch, in the past, companies we get about 8K median revenue. And now the companies in median are getting to 20,000 monthly revenue, supposed to 8K. So those are the top two that we can dive deeper into.

2:02Yeah, let's dig into heart tech first. Like, how do these heart tech companies and what's driving this? Things that actually touch atoms and not just bits. Yeah. And I think you have the category breakdown of the heart tech companies, right, Diana? Yeah. So specifically, robotics has been a big one. It has gone from 1% of the batch to about 6, 7% of the batch, industrial manufacturing, building things back in the US has been a huge trend. It has gone from about 4% to 10% of the batch. The other one is defense is a big one. We all have been working with a lot of defense startup. It has gone from about 1.5% to about 5% of the batch. The other big one is there's this compute need that the world is getting into with AI. So there's a lot of companies building the semiconductor stack or botonics. It has gone from about 1% of the batch from a year ago to about close to 4% of the batch. And the other one even below the stack of compute is power. So there's a lot of power

3:03infrastructure as well as gone from also 1% to about close to 3% of the batch. So all these numbers across the physical atom stacks have somewhere triple or quintupled. Yeah, this is the age of the machine, I think. I mean, as the world goes, our motto, the t-shirt says, make something people want and people should do want those things right now. And the other interesting factor about all these companies that are going deep into atoms is that we've been funding more technical founders and with more expertise than ever, right, Jared? We have this fun stat about the current summer batch. In the current summer batch, one in six of the founders actually has a PhD. It's way more than that's been historically. And it's because, yeah, if you're doing something with silicon photonics, you're probably going to need a pretty strong research background in that. And so we've been funding a lot more of those founders. And those founders, I think, have disproportionately been doing like, especially well.

4:05I think AGI compounds this in a really fascinating and awesome way in that, like, you might think in the past, you actually, like, heart tech was hard because you had supply chains, you had an incredible software component often. I think Palmer Lucky talked about this a lot when it came to Andral. It's like having code Gen means that suddenly, even all the things that they do at Andral can happen much, much faster, right? Even three or four years ago, you would talk about software engineering and like the top tier software engineers as one of the limiting reagents to being able to do really, really top tier full stack hardware. And that's less and less true. I mean, you still need one or two of them or you need like a small team, but you don't need to hire a thousand great engineers versus Google or meta or whoever else. And that really changes the economics. I mean, that's the, that's the true bull case for heart tech. It's that, it's not just that people are shying away from funding software businesses, but it's actually that

5:09the super smart models that we have now are actually accelerating scientific research and making it possible for startups to have bigger research breakthroughs earlier and that therefore these deep tech companies will actually work better. I think the other factor is, there's basically three macro trends that are also driving all this, all this growth on atoms and is seeing huge companies like SpaceX have such a successful IPO has created a generation of founders wanting to build in space. So there's lots of these companies that are building across the whole stack. So it's been companies that in the in the current batch in summer 26, this is company that we work with called Exosat that's trying to build basically a sovereign start link solution. There's other company that I work with in winter 20x is called Beyond Reach Labs that's building solar panels for satellites in space. If you imagine companies like Star Cloud wanting to have all these data center in space, they will need to have power. So this is an obvious solution. Now the other macro trend is, I think we have a generation of current founders right now that have

6:15grown with the war. That's been very front and center and spoken a lot in social media and they want to do something. Like two of the companies I'm most excited about that I funded the last couple batches. One was Icarus last fall and then nine mothers this last spring and both of them were defense. Icarus is doing like a solar powered YouTube spy plane that gives overwatch and can also do comms which is actually really important. The future of drone wars being able to actually communicate with your drones on the ground and see what's going on. They've been able to get to seven figure contracts with the new department of war and then likewise with drone war special forces has been buying nine mothers anti drone defense. So it's basically a shotgun turret with CV but it's actually almost the only way that you could protect special forces deep behind and enemy lines. These are people who have been training for years and years in a very elite special force that America doesn't have thousands of these people. We have a very very small set and so

7:21protecting them from what could be like a commodity drone attack is actually really existential for the department of war. So just really cool to see this new administration actually approach defense in a very different way. Classically there was just a lot of frankly capture from the big defense primes that are just doing sort of cost plus. They think of themselves as consultants and to be able to see new startups that can actually take advantage of all of the AI, all of the tech, all of the new ways of building things to build things that frankly the defense primes can't build. That's a really powerful mega trend right now. Now the thing about defense is not just those full solutions that get sold to the government. There's also a lot of category of startups that are dual use that they sell both to the private sector and to the government and that have to do with everything down the supply chain. So things like manufacturing things back in America,

8:23building, custom. I think you had this company, Knox Medal. Yeah, they're bringing metal manufacturing back to America. America has like largely lost its metal industry. It got hollowed out over the last few decades and can't build stuff without metal. And so Knox medals is like rebuilding America's metal supply chain and they're doing it in the heartland of America in in Detroit where there's all these like empty factories that it basically just been like sitting there. And there are examples like the trend where it's not just people are doing hardware companies where the hardware companies themselves are growing faster than ever. I think I saw a PG tweet that Knox medals is growing like that software growth rate. Do you understand that? How are they growing so fast? So one reason is that a lot of their customers are these new defense tech startups that have sprung up and need metal to build all their all their stuff and the existing suppliers that are these sort of like sleepy old businesses mostly run by old people just like can't keep up with the pace that the new defense tech startups want to build that. And

9:25it reminds me a bit of like when the web 2.0 boom happened early in in the YC days we would have these new startups. But then they would prefer to buy from new startups that could sort of like move at their speed and like work well with them like Stripe for example. You could use a legacy credit card vendor but like this is like way better to work with Stripe. And so I feel like they're sort of becoming that for the whole defense tech ecosystem. Now the third trend is basically compute is a very heavy physical atoms process to get all these data centers live very quickly because a lot of the demand for AI that we've been talking has been skyrocketing. And there's a very interesting stat where GPUs from Nvidia LSD like a A100 GPU per hour is actually appreciating and cost which is unusual in the past when you get a it 100 by now I sort of old the price is going up because it's just too much demand and not enough supply and compute. So there's a lot of startups that are now working on bringing data centers live and you have everything from

10:30the construction of the sites to the software to plan it to actually doing the data center build out to interesting interesting solutions that have to do with how to power them and combination of energy battery. So this all these category of startups and even to the point of going down to the core compute oscillacance there's a number of startups that are building new new Silicon for an alternative to to to Nvidia. There's this company the Tyler worked with called lamb labs that's building new processors for compute. There's another one that I'm working on this batch called bot that is trying to build basically new custom hardware architecture that's using turnery representation for models because what it turns out which is a funny trend right now. If you look at all the Nvidia architectures from a 100s to a 100s and now the B B 300s each of these generations they're actually going down in floating point precision in terms of what they were they're going

11:33from fp 32 16 8 etc and it turns out that the lm architecture doesn't need the full precision floating. fp 2 is even somewhat usable. Right so this is what bot is trying to do and I think you have an interesting one that's doing the interconnect with with photonics. Yeah there's a company called dipole labs in the current batch that is replacing the switches that are in data centers which are essentially the like routing systems but tweened different GPUs if like GPU want aid wants to talk to GPU be they talk to each other through this device it's called a switch and these switches right now are electronic and so there's actually an issue which is like the switches are not keeping up with the GPUs the the speed of the GPUs keeps going up and the switches are actually the bottleneck for many data centers in any different workloads and so dipole labs is building the first fully optical switch where it's like all photons from GPUA all the way to GPUB and so it will actually be much faster than the electronic switches that we use now. Now the last one that's driving

12:34all this move to atoms is this aspect where robotics is going to happen. So there's a lot of companies building the stack around that and everything from vertical robotics and specific industries to the infrastructure to the polar robots to data selling to the new robotics labs because there's this moment that everyone in the industry is feeling that we're going to get to the chat GPT moment is not quite there yet and I think we're figuring it out and new a scaling law around it. So there's a lot of that and we had Kwan here a couple episodes ago and we're believers that's going to happen. I mean robotics from pie from pie right half is AI and half is a hardware and I was hearing this reading this morning that even Astero is like a big leap forward for for robotics. I forget the benchmark but there's a benchmark where like fable was maybe at 10% and Astero is showing like you do like 60 to 70% of the tasks. So data just you know wake up

13:38in you know another couple weeks and another breakthrough happens and we're a little bit closer. It's been really cool for me to see the research and so of heart attack because you know LYC we've been funding heart attack companies since 2014 that's really when we we started but it was like pretty hard to get these companies funded before like I remember like pre pre this recent research and we would like fund awesome stuff that we were super excited like rockets and planes and chips and data centers and stuff like that and then like VCs would just be like we only do B2B SaaS and it's hard to bootstrap a company like this so you really do need like downstream investors who can fund lots of who can who can fund you know a full a full capital build out and so it's cool that like it seems like Silicon Valley which historically like Ventura was set up to fund heart attack but it like drifted away from it for a decade or two because it was so profitable to just fund SaaS companies and so it's cool to have it coming back to its roots. Yeah on the point about like the the peer investors wanted to do heart tech again it does seem like that I've never seen that happen so quickly I mean it seemed like it happened pretty

14:42immediately when like SaaS stocks were down earlier this year Claude code was surging and that just became like the I mean I feel like even at Demo Day literally happened I feel like that happened for we made the winter batch at the start of this year and it seemed like even Demo Day that investors were starting to be a lot more interested in heart tech companies and that's just extrapolated I mean it is worth knowing though on the other side like since that a bunch of the SaaS stocks have actually recovered and are doing better than ever like Salesforce is like the prime example of that thinks snowflake recently had like like two days ago at this like blowout earnings and so it's possible that it all hits yeah maybe I mean that would be the dream case I mean I sort of think we're seeing a real stuff like it clearly the software that gets built in the future and what's valuable is different like it just has to be and so partly it seems like what we've seen with Salesforce is the classic the system or record argument is actually playing out. The modes are intact for now yeah like if you have a thing that agents can use

15:42that is actually valuable and if anything you'll just like agents where you suffer a lot more than humans were and that seems to be driving Salesforce growth and so it kind of takes us back to the other trend that we've talked a little bit about is if you think of agents as your customers and you make things that agents one and your software is something that agents want to use then that seems like the right type of software yeah Salesforce is super interesting because I think they started releasing their own Slack harness Slack AI harness and so I think we're right at the beginning of like the next AI harness wars it's like codex wants to be a cloud code wants to be it open code to be it hermys open code it seems like there are going to be a bunch of them and it's not going to be quite like the browser wars and that the browser wars 10 toward like one winner but you know I guess it's anyone's guess and then yeah Benioff has a pretty big advantage in that you have a lot of the most AI-appilled people and companies in the world still use Slack and you know if the harness is in there and it's your your system of record for how people collaborate then

16:46you have like this mega data mode and then you know SaaS can still be as valuable as it's ever been valued if those modes hold yeah I thought you had a really interesting tweet maybe a week also ago about how the software or system of record companies will have to become like harnesses yeah I mean that's based that was about Slack I would say it's like basically if you are a system of record you either will be preyed upon like you'll release an mcp and then maybe like the data you know you lose your moat around the data the data goes elsewhere like becomes very trivial to switch or you kind of have to be a harness you have to be the way people not just read and write but actually do their work inside you know your system of record and get the most value out of it means a little bit like the model companies like was the was it arch a g i was a benchmark where there was a benchmark where the yeah where the pre or pre-astra chat gbt model didn't do as well but then they say well that's just because it was plugged into the wrong harness it's like the model plus

17:46the harness gets you the output oh yeah I mean with a custom harness they claim Astra got to night north of 90% on arch a g i3 yes I think a couple months ago this was in the low two digits right which is an impressive leap and I think you have a very good point around software it's not that software and SaaS is dead what people claim on the internet is just that is has transformed we actually seen this in the batch the percentage of companies we accepted that do sort of full stack into an work or a task has gone from just 10% to over 25% of the batch this has to do with actually doing the job the agent does the job not just like a point solution which old SaaS in five eight years ago was just like a point solution and you needed a you needed someone to operate the SaaS software right now it just runs by itself and actually in the batch this is where we're seeing a lot of the growth in revenue I think I gave that stat of the median startup when it gets

18:52into YC is a zero in revenue and it has gone from by the end of the batch was about 8K in MRR now is about 20K in MRR and a lot of these are huge jump that's like an untrivial big jump for the median right the average is even higher and it has to do with doing the full end to end job with for example doing insures broker actually doing the clinical intake doing the full end to end workflow of I don't know medical billing etc and these are the ones that are growing a lot and I think there's another factor with us happen I think we talked about this in couple episodes ago we right now are about almost a year since agentic coding started to work since opus 4.5 that we're seeing these workflows fully blossom and the result are basically people want their job just be done and I'm willing to buy software that just gets the job done I think when people hear these revenue numbers growing so

19:54an easy knock on it is like maybe it's just AI hype and these companies are just like shelling out money for AI products because it's like the cool thing to do and to be fair that's probably some of that but I think like the bull case is actually something that we said in an episode like two years ago when agents were really just beginning to be a thing where we were like actually the products are just going to be more valuable like if they automate the whole job they will actually just be more valuable than some like system of record that tracks the job it doesn't do the job and then for companies we'll just like pay more money for the product I definitely see that in companies that I work with where yeah they just go to a company like the value proposition is so great that like large enterprises are willing to write big checks very very early yeah company that I'm seeing having this effect is juice box AI recruiting tool like it's been an incredible great trade for like the last couple of years now but they'd started out as I mean I would say it was essentially sort of LL empowered people search like the thing that they did was you could type in sort of the spec of the type of person you wanted to hire and it

20:54did a really good job of pulling the good profiles of people that you may want to contact but then you still have to go and contact the people and recently they've launched an agent product which is really taking off and the agent like it doesn't just search for the people it like contacts the people and it'll be able to schedule the interview do a bunch of things that's awesome yeah and they're seeing that that's going to just on a like per account basis I think is going to double or triple like the revenue they make from a single customer because customers want more and more of these agents I don't think it's fair to say that it's like it's not like it's like ultimating the job of the recruiter at all it's just it's just changing it like it like the recruiters didn't necessarily want to be doing like that sort of wrote reach out to like 500 people anyway like the thing that makes the recruiter job I would say like more skilled and interesting is like there's like culture fit that's just going to be really hard for like getting AI to do a phone screen that assesses like how well someone's going to be like a coach of it and and the human element of it and so I think they finding that the recruiters themselves are actually really excited to use the agents because it

21:55frees them up to do the work that they feel is like unique and interesting the other shocking stat is that the companies that really accelerate during the batch they really start taking off one of the things that we start experiencing this year that we never experienced in the past is we have companies breaking from zero to seven figures in revenue during the batch and that is in a span of three months and that's talking in the past that would have taken for a company to get to that about 18 months or more and they're doing it in that amount of time or it is they're solving real problems and because of agent decoding they're actually building products that are a lot more mature as well and they're able these founders that are super AI-pilled run I don't know 20 coding agents sessions to get to that product maturity and there's another category of companies that's also been growing super fast recently which is companies that sell data or RL environments to the

22:58labs this one might be interesting to talk about because a lot of these companies are pretty stealthy they tend to have a distance incentive to talk about how well they're doing instead you know compared to most companies that like to talk about how well they're doing and so I think people out there might not realize how big a category this has become when YC funded scale back in 2016 this was like a tiny little niche thing it wasn't even a category there was initially it was basically just scale who was doing and then Mccore began to do it and then like a couple other companies been the last couple years to become a big category we pulled the data recently and just in the last two years YC is funded more than a dozen companies that are each making more than $10 million a year selling data or RL environments to the labs and in many cases hundreds of millions of dollars it may make his 100-100 million dollars and these are companies that were just just a couple of years old that's pretty fast to revenue honestly yeah it's like pretty bananas do you want to talk about anything Gary? I mean the big ones I mean I think after quarry and data curve both really really great I mean there are probably too many to name that are honestly like maybe don't even

24:02want to be mentioned because once you have something that's working you almost don't want people to know I think that it's kind of natural to understand this though I mean data is one of the legs of the scaling law and you know much has been made of compute but without the data how are you going to make these models that much better the RL environment thing is interesting I mean there's a lot there I mean there's a lot of like pure customization that's happening for specific use cases like you'll have like RL environments for finance for instance and someone can go very very infinitely deep with that and it's like a little bit of expertise it's a bunch of computer science it's some systems work but RL seems to be I mean one of the big engines for how I mean people are maybe bench benchmark maxing a little bit more than they should but it costs money to do it and it's seemingly here to stay in terms of how big model companies are going to approach it. Reportedly the big labs are spending about a billion dollars on this it's not a very known fact

25:06but there's this actually a real business to be built around this and RL environments the current flavor it and there's things with long-term horizon tasks that are getting built up and I think that is starting to also emerge in robotics the labs also want to solve the problem of getting AI to work on the physical world so they need a lot of the environments in the real world so things with egocentric data tell it off robotic tasks starting to emerge is like big data category where labs are spending eight nine-figure deals with these companies we had a number of companies in the batch that work on that and been able to close close revenues in that in that space companies like in the current batch of summer 26 there's praxis robotics there's one that I'm working with that has like a network of places across the world where industrial manufacturing gets done they collect data from that there's this other company that Brad work with called DeepReach that also has data that local entrepreneurs and across the world do and human archive and

26:13winter 26 yeah there've been a bunch of these companies recently right I think like if I were going to prognosticate like one of the things going back to the you know all systems of record need to be AI harnesses they might also need to start training their own models and that's where things like river AI or tinker start becoming really interesting out of the box like you can sit there in cloud code or even open I use open cloud to train my own models which is very fun it'll do its own data cleaning and everything but to date like that hasn't been a huge factor but I can see that becoming a much much bigger factor I mean when you have proprietary data and you can train I mean the open open weight models are really nearly frontier if you can like sort of special purpose train these things to do even better than what the frontier can do like that that's going to be really really powerful I think this is actually going to be even bigger in robotics I mean this is a hypothesis is not proven yet but robotic foundation models and robotics I think I have a

27:15very different characteristics versus LLM's LLM is the whole thing is your model reality as language and for robotics you model reality in the physical 3D space which has way more degrees of freedom and perhaps in order to get robots to work in a specific vertical like let's say robots that do operations in data centers have this company called boost robotic that build robots for data centers like doing the cabling it is possible for these robots to work it's better to get a model that's fine tune and train and custom data that just works in that environment because the the thing that's also challenging for robotics they need to be in real time and respond very quickly to to the stimuli and have an action plan which is different than LLM's LLM's you can have this this feature where you can just let it go and come back but for robotics you can because if I don't know let's say you connect that cable to the data center and then someone comes in and like knocks the robot out and thinks could get connected to the wrong plug let's say yeah my understanding

28:18is that all the YC companies that are using physical intelligence as models to deploy robotics they're all fine tuning the pie models I don't think any of them are able to use the pie models out of the box even though it's a great like starting point you have to actually fine tune it for like your specific case like data center cables in order for it to work you work with this company ultra right yeah they start with the pie model but then they have like thousands of hours of footage of like putting things in boxes that makes it really good at putting things in boxes I've heard the argument basically that you know you could look at cloud code like cloud code can use its smart it's uh code transcripts to figure out who the top coders are and you can take that and turn it around and you know basically train the next coding model to be even better if you happen to own tick-tock you happen to have all of the data on uh what people watch and click on and what's compelling and you can use that to make much more compelling videos and seed dance so you know that's already been happening I just you know I think that that that trend is going to continue in a fairly spectacular way from here

29:19so one of the things that we've been noticing I think all of us have is that frankly some of the most powerful and badass founders that we've been seeing lately there might be in their late 30s 40s even 50s I mean there's a sort of resurgence of the experienced founder a lot of people seem to say that they want to be uh YC for solo founders but it turns out YC is the YC for solo founders Diana you have a few stats that uh you found surprising one of the shocking stats from analyzing the septic companies from a year ago we used to only have about 5% of the companies accepted peace all the founders and now we're over 18 19% which is a huge this is the highest bike that we seen almost one fifth of the batch so and it seems like it's going to keep going you know before you had you had to have like you know so many different skills you had to be a great hustler you know you had to be able to explain and you know we would say like they have to be good talkers right like you need someone who can you know uh be a hot person someone who can actually come in

30:25and convince someone of something uh and then if you paired that with someone who is a world class technologist that's sort of the combo that is so ideal um and so classically you would need co-founders to do that like you know any it you didn't necessarily need one but like it would increase your chances by so so much i feel like a lot of that is like changing to this degree it's becoming such that like knowing what to prompt and knowing what to build is so much more difficult and valuable than just knowing you know the cto being able to code the thing i think what's going on is that we've always actually had um hugely successful single founders i think people don't realize that there's about yc there's different sort of definitions of it but for all intensive purposes i'll prove it with instacard Brian Armstrong with quain bass at least when the batch started we're single found yeah parkour conrad god into yc as a single founder and then i interviewed luxriny has to end up being his cto the bar for being able to like have the idea

31:26be able to sell it and be able to build it all by yourself which is really really high um and that's actually totally doable yeah i think that's what's going on in that case like those three are just like incredibly exceptional people and so it's like very very few people who are capable of that and now you can actually like get going and so i think you just don't have to be quite that like exceptional at least on one of those dimensions the building part to be able to get going but net net it's still valuable to have co-founders it's still a measure of like you know if your co-founders are super elite like that means you're probably super elite and it just increases the chance of success by a lot and in each of those cases they did bring on co-founders i think in each of those cases you just get going and they got traction and they added on co-founders sort of add a certain point and so maybe like the um the equity ownership is different or maybe the dynamic is just slightly different to the traditional way like you'll you start out and like the two of you in a room and uh and you can be the 50-50 i don't know if you want to be anything but yeah i don't have the status but i have definitely seen a greater trend towards that people adding co-founders

32:29later in the company life cycle after the thing has already like gotten off the ground i think that will be the trend i think we'll see a little like more single founders in the battle if you're already seeing like starting the batch but at least with the things that succeed i still expect that they're going to be adding co-founders um as the company progresses gary do you also want to talk about the trend towards like more experienced people starting companies so it does seem like people who have been around the block a few times are doing much much better i think of Peter Steinberger as like sort of the canonical example like you know he's uh i believe in his early 40s and he'd been a dev manager he'd worked on startups before and then you know he sort of uniquely got extremely a i-pilled with the clankers early but then he just tried a lot of stuff and then he knows what to build and so that's one thing that i think is actually really encouraging it's like basically if you've been around the block you know where the you know where the dragons are you

33:31sort of uh have taste and then those people in particular are like unusually powerful right now you know i mean there are just so many uh classic gate kept things that happens like oh you you know you have to have a co-founder you need like a certain set of you know cool investors to be into you and like now it's just less and less true it's actually like you need to know what to build that's like the higher the bit now is you need to know what to build and if you've lived a little bit and you've been in places and you're very opinionated like actually and now you might not have an excuse like what's your excuse like you've been this loudmouth on the internet for so long like well you know why are you not building something like just pop open open code and just go do it you know like put your money where your mouth is i also wonder if managing coding agents is actually like in some ways not that different from managing people oh yes and so like people like Peter or you or or force journey and like Toby from Shopify who who have had whole careers like managing teams of engineers actually like take to this super well and can like spin up huge teams

34:36of coding agents and manage them maybe more effectively than even like a really smart 19 year old who hasn't had those years of experience we can be a little bit less abusive to our agents try to understand where they're coming from you have to catch their emotions like 99.9% less so yeah it's pretty helpful i wonder what's the concrete advice for someone that wants to get started and want to build a company like right now in the current era i mean i'll just start prompting i mean opening up gpt6 today was pretty wild i mean just that moment where your agents are you know it's probably smarter they you know a bunch of things that you've been annoyed about like these bugs that you know you haven't had time to deep deep dive yourself you just be like actually could you just go back to the list of things that you couldn't figure out like look at your you know all of our last chats and you know anything that looks like you didn't figure out like try to figure it out now and it'll do it like every single time like you know it's

35:38what a weird moment we are in history where you wake up in the morning you like wire up a new model and then these things that even a month ago you're just like why is networking it just starts working and like you know to think that that might be this thing that we get to do for the next 18 24 months 36 months like who know you know i don't know when it ends but that's coding in the time of a g i i guess well that's all we have time for for today but if you can't tell we're all pretty excited about what's going on right now and you should be too so we can't wait to see what you build you