The State of Startups in 2026

0:00Harj Taggar: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 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.

0:41Harj Taggar:Welcome back to another episode of The Light Cone. 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, know? Let's get started. Diana, you have a few things to share with us. So we did a bit of an 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 hard tech companies that are in the batch.

1:22It 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 would get to about 8K median revenue. And now the companies in median are getting to 20 ,000 monthly revenue as opposed to 8K. So those are the top two that we can dive deeper into. Yeah. Let's dig into hard tech first. What are these hard tech companies and what's driving this?

2:07Harj Taggar:Things that actually touch atoms and not just bits. Yeah. And I think you have the category breakdown of the hard 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 U.S. 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 startups. 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.

2:48So there's a lot of companies building the semiconductor stack or photonics. 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 infrastructure as well. has 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.

3:14Harj Taggar: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 sure 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, you know, something with like silicon photonics, you're probably going to need a pretty strong research background in that.

3:59And so we've been funding a lot more of those founders. And those founders, I think have disproportionately been doing especially well.

4:05Harj Taggar:I think AGI compounds this in a really fascinating and awesome way in that you might think in the past, you actually, like hard tech was hard because you had supply chains, you had an incredible software component often. I think Palmer Luckey talked about this a lot when it came to Anduril. It's like having CodeGen means that suddenly even all the things that they do at Anduril can happen much, much faster, right? Even three or four years ago, you would talk about software engineering and the top tier software engineers as one of the limiting reagents to being able to do really, really top tier, full stack hardware.

4:47Harj Taggar:And that's less and less true. I mean, you still need one or two of them or you need 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 true bull case for hard tech. It's that it's not just that people are shying away from funding software businesses, but it's actually that the 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.

5:21I think the other factor is there's basically three macro trends that are also driving 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. There's lots of these companies that are building across the whole stack. So there's been companies in the current batch in summer 26. This is a company that we work with called Exosat, that's trying to build basically a sovereign Startlink solution. This other company that I work with in winter 26 called Beyond Reach Labs, that's building solar panels for satellites in space.

6:01If you imagine companies like StarCloud wanting to have all these data centers 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 grown with the war that's been very front and center and spoken a lot in social media and they want to do something.

6:23Harj Taggar: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 U-2 spy plane that gives overwatch and can also do comms, which is actually really important. The future of Drone War is 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.

6:56Harj Taggar: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 enemy lines. I mean, 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 protecting them from what could be like a commodity drone attack is actually really existential for the Department of War. So it's just really cool to see this new administration actually approach defense in a very different way. Like, you know, classically, there was just a lot of, frankly, capture from the big defense primes that are just doing sort of cost plus.

7:43Harj Taggar:They think of themselves as consultants. And, you know, 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. You know, that's a really powerful megatrend 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, building custom.

8:25I think you had this company, Knox Metal. Yeah, they're bringing metal manufacturing back to America. America has largely lost its metal industry. It got hollowed out over the last few decades and can't build stuff without metal. And so Nox Metals is rebuilding America's metal supply chain. And they're doing it in the heartland of America in Detroit, where there's all these empty factories that have basically just been sitting there.

8:50Jared Friedman:And their example of the trend where it's not just people are doing hardware companies, but the hardware companies themselves are growing faster than ever. I think I saw a PG tweet that Knox Metals is growing at software growth rates. 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 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 at.

9:25And it reminds me a bit of like when the Web 2.0 boom happened early 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 it's just 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.

10:04And there's a very interesting stat where GPUs from NVIDIA, let's say like an A100 GPU per hour is actually appreciating in cost, which is unusual. In the past, when you get a, 8100 by now are sort of old.

10:18Harj Taggar:They're pretty old, yeah. 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 the construction of the sites to the software to plan it, to actually doing the data center build out, to interesting solutions that have to do with how to power them and combination of energy, battery. So there's all these category of startups and even to the point of going down to the core compute silicons, there's a number of startups that are building new silicon for an alternative to NVIDIA.

10:57There's this company that Tyler worked with called Lam 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 ternary representation for models because what it turns out, which is a funny trend right now, if you look at all the NVIDIA architectures from A100s to H100s and now the B300s, each of these generations, they're actually going down in floating point precision in terms of what they were. They're going from FP32, 16, 8, etc. And it turns out that the LLM architecture doesn't need the full precision floating point.

11:42Harj Taggar:FP2 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 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 routing systems between different GPUs. If GPU A wants to talk to GPU B, they talk to each other through this device that'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 speed of the GPUs keeps going up, and the switches are actually the bottleneck for many data centers and many different workloads.

12:21And so Dipole Labs is building the first fully optical switch where it's like all photons from GPU A all the way to GPU B. And so it will actually be much faster than the electronic switches that we use now. Now, the last one that's driving all 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 in specific industries to the infrastructure to deploy 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.

13:05It's not quite there yet. And I think we're figuring it out a new scaling law around it. So there's a lot of that. And we had Quan here a couple episodes ago and we're believers that's going to happen. I mean, robotics.

13:19Jared Friedman:From Pi. From Pi, right? Half is AI and half is hardware. I was hearing this, reading this morning, that even Astra is like a big leap forward for robotics. I forget the benchmark, but there's a benchmark where Fable was maybe at 10 % and Acero is showing you can do 60 % to 70 % of the tasks.

13:36Harj Taggar:So Data did just wake up in another couple weeks and another breakthrough happens and we're a little bit closer. It's been really cool for me to see the resurgence of hard tech because NYC, we've been funding hard tech companies since 2014. That's really when we started. But it was pretty hard to get these companies funded before. I remember pre this recent resurgence, we would fund awesome stuff that we were super excited, like rockets and planes and chips and data centers and stuff like that. And then VCs would just be like, oh, we only do B2B SaaS. And it's hard to bootstrap a company like this.

14:12So you really do need downstream investors who can fund a full capital buildup. And so it's cool that like, it seems like Silicon Valley, which historically like venture was set up to fund hard tech, 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.

14:33Jared Friedman:Yeah. On the point about like the peer investors wanting to do hard tech again, it does seem like that. I've never seen that happen so quickly. I mean, it seemed like it happened pretty immediately 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 it literally happened i feel like that happened probably mid the winter batch at the start of this year and it seemed by even demo day that investors were starting to be a lot more interested in hard 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 sas stocks have actually recovered and are doing better than ever like salesforce is like the prime example of that i think snowflake recently had like like two days ago had these 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 still think we're seeing real stuff though 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're seeing with salesforce is the classic the system of record argument is actually playing out the moats are intact for now yeah like if you have a thing that agents can use um that is actually valuable and if anything you're just like agents will use software a lot more than humans will and that seems to be driving salesforce growth and so 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 want and your software is something that agents want to use then that seems like the right type of software yeah

16:04Harj Taggar: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 it, Cloud Code wants to be it, OpenCode could be it, Hermes, OpenCode. 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 tend 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 a lot of the most AI-appealed people and companies in the world still use Slack.

16:39Harj Taggar:And, you know, if the harness is in there and it's your system of record for how people collaborate, then you have like this mega data moat. And then, you know, SaaS can still be as valuable as it's ever been valued if those moats hold.

16:54Jared Friedman:Yeah, I thought you had a really interesting tweet maybe a week or so ago about how the software or system of record companies will have to become like harnesses.

17:01Harj Taggar:Yeah, I mean, 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.

17:27Jared Friedman:And get the most value out of it. I mean, it's a little bit like the model companies. Was it RKGI was the benchmark? Or there was a benchmark where the... RKGI V3. Yeah, where the pre-Astra chatGBT model didn't do as well. But then they said, well, that's just because it was plugged into the wrong harness. So it's like the model plus the harness gets you the output.

17:47Harj Taggar:Oh, yeah. I mean, with a custom harness, they claim Astra got to north of 90 % on RKGI 3. Yes. I think a couple months ago, this was in the low two digits, 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. It's just that it has transformed. We've actually seen this in the batch. The percentage of companies we accepted that do sort of full stack end-to-end 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.

18:29which old SaaS in five, eight years ago was just like a point solution and 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 into YC is a zero in revenue. And it has gone from by the end of the batch, it was about 8K in MRR. now is about 20K in MRR. And a lot of these -

19:03Harj Taggar:That's a huge jump. That's like non-trivially 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 insurance broker, actually doing the clinical intake, doing the full end-to-end workflow of, I don't know, medical billing, et cetera. And these are the ones that are growing a lot. And I think there's another factor where that's happened. I think we talked about this in a couple episodes. 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.

19:43And the result are basically people want their job just be done and are willing to buy software that just gets the job done. I think when people hear these revenue numbers growing so fast, an 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.

20:17Like if they automate the whole job, they will actually just be more valuable than some like system of record that tracks the job and doesn't do the job. And therefore, companies will just like pay more money for the product. And I definitely see that in companies that I work with where, yeah, they just go to a company. And like the value proposition is so great that like large enterprises are willing to write big checks very, very early.

20:38Jared Friedman:Yeah, a company that I'm seeing having this effect is Juicebox, an AI recruiting tool. Like it's been an incredible growth rate for like the last couple of years now. but they'd started out as i mean i would say it was essentially sort of llm powered 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 did a really good job of pulling the good profiles of people that you may want to contact um 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 doesn't just search for the people it like contacts the people and then you'll be able to schedule the interview do a bunch of things that's awesome yeah and they're seeing that that's gonna 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 automating the job of the recruiter at all it's just like it's just changing it like it like the recruiters didn't necessarily want to be doing like that sort of rote 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 an AI to do a phone screen that assesses like how well someone's going to be like a culture fit and and the human element of it and so I think they're finding that the recruiters themselves are actually really excited to use the agents because it frees them up to do the work that they feel is like unique and interesting.

22:00The 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 shocking. 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. Part of 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.

22:41And they're able, these founders that are super AI pilled run, I don't know, 20 coding agent 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 labs. This one might be interesting to talk about because a lot of these companies are pretty stealthy. They tend to have a disincentive to talk about how well they're doing 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.