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Garry Tan
CEO, YCombinator

The State of Startups in 2026

📅 Sep 17, 2026 Y Combinator 36 MIN 179474 VIEWS 79 SEGMENTS · 3 SPEAKERS
YC works with thousands of founders every year, which gives us an early look at how startups are changing. Right now, the shift is striking: startups are moving from bits to atoms, nearly one in five YC companies has a solo founder, and companies are reaching meaningful revenue faster than ever. In this episode of The Lightcone, Garry, Jared, Diana, and Harj dig into what’s driving these changes and what they mean for founders. They discuss how AI is making it possible for smaller teams to take on more ambitious problems, why experienced founders are having a resurgence, and why knowing wha...

What Garry Tan said

Written from the verified transcript and checked against it. Every figure links to the moment it was said.

Garry Tan, CEO of Y Combinator, discussed the state of startups, focusing on the shift from software to hard tech and the accelerating growth of startups. He noted that hard tech companies now make up 20% of YC's batch, up from 8%, with robotics, defense, and power infrastructure seeing significant increases. Tan highlighted that AI and agentic coding are enabling founders to build more mature products faster, with some companies reaching seven-figure revenue during the three-month batch, a feat that previously took 18 months. He also discussed the rise of experienced founders in their late 30s to 50s and the increase in solo founders, now at 18-19% of the batch. Tan emphasized that companies selling data or RL environments to labs have become a major category, with YC funding over a dozen such companies each making over $10 million annually. He argued that systems of record must become AI harnesses to survive, and that open-weight models trained on proprietary data could become increasingly powerful.

Key takeaways

  1. Hard tech companies now make up 20% of YC batches, up from 8% a year ago, driven by robotics, defense, and power infrastructure.
  2. YC-funded companies are achieving seven-figure revenue within the three-month batch, a process that previously took 18 months or more.
  3. Solo founders now represent 18-19% of YC's accepted companies, up from 5%, with experienced founders in their late 30s to 50s performing exceptionally well.
  4. YC has funded over a dozen companies selling data or RL environments to labs, each making more than $10 million annually.
  5. Systems of record must become AI harnesses or risk losing their data moats to competitors like Codex or Claude Code.

Numbers and commitments

FigureWhat it refers toTypeAt
20% Share of hard tech companies in YC batch metric 1:04
$20,000 Median monthly revenue at end of YC batch metric 1:04
6-7% Share of robotics companies in YC batch metric 2:16
10% Share of industrial manufacturing companies in YC batch metric 2:16
5% Share of defense startups in YC batch metric 2:16
18-19% Share of solo founders in YC accepted companies metric 29:49
$10 million Annual revenue for YC-funded data/RL companies metric 22:59
90% Performance score for Astra on RKGI 3 benchmark metric 17:47
60-70% Success rate for Astra on robotics benchmark metric 13:18

Chapters

  1. 0:00Hard tech growth in YC batches
  2. 6:23Defense startups and new administration
  3. 10:19Compute and data center startups
  4. 12:32Robotics and AI breakthroughs
  5. 14:33SaaS transformation and AI harnesses
  6. 22:59Data and RL environment companies
  7. 28:44Rise of solo and experienced founders
  8. 34:58Advice for new founders

Questions asked in this interview

8
  1. 3:28And the other interesting factor about all these companies that are going deep into atoms is that we've been funding more technical founders with more expertise than ever. Right, Jared?
  2. 8:50Like, kind of how are they growing so fast?
  3. 17:27Like, was the... was it RKGI?
  4. 17:54I think a couple months ago, this was in the low two digits, right?
  5. 23:50Do you want to talk about any of them, Garry?
  6. 28:34You work with this company, Ultra, right?
  7. 32:47Garry, do you also want to talk about the trend towards, like, more experienced people starting companies?
  8. 33:37Like, you know, why are you not building something?
Garry Tan 0:00 ↗
Frankly, some of the most powerful and badass founders that we've been seeing lately 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 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 Lightcone. 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.
Diana Hu 1:04 ↗
So we did a bit of an analysis for all the companies we accepted in the last 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 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, is 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.
Garry Tan 2:02 ↗
Yeah. Let's dig into hard tech first. Like, what are these hard tech companies and what's driving this?
Jared Friedman 2:08 ↗
Things that actually touch atoms and not just bits.
Garry Tan 2:10 ↗
Yeah. And I think you have the category breakdown of the hard tech companies, right, Diana?
Diana Hu 2:16 ↗
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, which 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. So 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, which has gone from also 1% to about close to 3% of the batch. So all these numbers across the physical atom stacks have somewhere tripled or quintupled.
Garry Tan 3:13 ↗
Yeah, this is the age of the machine, I think. And that's, I mean, as the world goes, you know, our motto, the t-shirt says, 'Make something people want.' And people sure do want those things right now.
Diana Hu 3:28 ↗
And the other interesting factor about all these companies that are going deep into atoms is that we've been funding more technical founders with more expertise than ever. Right, Jared? We have this fun stat about the current summer batch with...
Jared Friedman 3:45 ↗
In the current summer batch, one in six of the founders actually has a PhD. It's way more than has 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. And so we've been funding a lot more of those founders, and those founders, I think, have disproportionately been doing especially well.
Garry Tan 4:04 ↗
I think AGI compounds this in a really fascinating and awesome way in that, like, 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, 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.
Jared Friedman 5:01 ↗
I mean, that's the true bull case for hard tech. 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. I think the other factor is there's basically three macro trends that are also driving all this growth on atoms. And seeing huge companies like SpaceX have such a successful IPO has created a generation of founders wanting to build in space. There are lots of these companies that are building across the whole stack. So there's been companies in the current batch in Summer '26. There's a company that we work with called Exosat that's trying to build basically a sovereign Starlink solution. There's another company that I work with in Winter '26 called Beyond Reach Labs that's building solar panels for satellites in space. If 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 about it.
Garry Tan 6:23 ↗
Like, two of the companies I'm most excited about that I funded in 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. 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, you know, in a very elite special force that, you know, America doesn't have, you know, thousands of these people. You know, 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 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. 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.
Diana Hu 8:01 ↗
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... I think you had this company, Knox Metals. 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 Metals is, like, rebuilding America's metal supply chain. And they're doing it in the heartland of America, in Detroit, where there's all these, like, empty factories that have basically just been, like, sitting there.
Jared Friedman 8:50 ↗
And they're an example of, like, the trend where it's not just people are doing hardware companies, but the hardware companies themselves are growing faster than ever. Like, I think I saw a PG tweet that Knox Metals is growing, like, at software growth rates. Do you understand that? Like, kind of how are they growing so fast?
Garry Tan 9:05 ↗
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. And 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 about has been skyrocketing. And 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 an A100, by now it's sort of old.
Jared Friedman 10:18 ↗
They're pretty old. Yeah.
Garry Tan 10:19 ↗
The price is going up because there's just too much demand and not enough supply in 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 plant to actually doing the data center buildout to interesting solutions that have to do with how to power them and combination of energy, battery. So there's all these categories 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 as an alternative to Nvidia. There's this company that 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 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.
Jared Friedman 11:42 ↗
FP2 is even somewhat usable.
Garry Tan 11:44 ↗
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.
Jared Friedman 11:51 ↗
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, like, GPU A wants to talk to GPU B, 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 speed of the GPUs keeps going up. And the switches are actually the bottleneck for many data centers in many different workloads. And 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.
Diana Hu 12:32 ↗
And 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 ChatGPT moment, just not quite there yet. And I think we're figuring it out and 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.
Garry Tan 13:18 ↗
I mean, robotics 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. Like, on, I forget the benchmark, but there's a benchmark where, like, Fable was maybe at 10%, and Astra is showing, like, you can do, like, 60 to 70% of the tasks.
Diana Hu 13:36 ↗
So it's just, you know, wake up in, you know, another couple weeks and another breakthrough happens and we're a little bit closer.
Jared Friedman 13:43 ↗
It's been really cool for me to see the resurgence of hard tech because, you know, YC, we've been funding hard companies since 2014. That's really when we started. But it was, like, pretty hard to get these companies funded before. Like, I remember, like, pre this recent resurgence, we would, like, fund awesome stuff that we were super excited about, like rockets and planes and chips and data centers and stuff like that. And then, like, VCs would just be like, 'Ah, 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 fund, you know, a full capital buildout. 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.
Garry Tan 14:33 ↗
Yeah. On the point about, like, the 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 then a bunch of the SaaS 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, two days ago had these, like, blowout earnings, and so it's possible that it all hits.
Jared Friedman 15:21 ↗
Yeah, maybe. I mean, that would be the dream case. I mean, I still think we're seeing real stuff, though. Like, 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 system-of-record argument is actually playing out.
Garry Tan 15:37 ↗
The moats are intact for now.
Jared Friedman 15:39 ↗
Yeah. Like, if you have a thing that agents can use that is actually valuable, and if anything, agents will use software a lot more than humans will, 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 want and your software as something that agents want to use, then that seems like the right type of software.
Garry Tan 16:04 ↗
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, Claude Code wants to be it. OpenCloud 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 in that the browser wars tend toward, like, one winner, but, you know, I guess it's anyone's guess. And then, yeah, Benoff has a pretty big advantage in that a lot of the most AI-pilled companies in the world still use Slack. 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.
Jared Friedman 16:55 ↗
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.
Garry Tan 17:02 ↗
I mean, and 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.
Jared Friedman 17:27 ↗
I mean, it's a little bit like the model companies. Like, was the... was it RKGI? Was the benchmark, Mark, where there was a benchmark where of the...
Garry Tan 17:36 ↗
RPGI V3.
Jared Friedman 17:37 ↗
Yeah. Where the pre-Astra ChatGPT 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.
Garry Tan 17:47 ↗
Oh, yeah. I mean, with a custom harness, they claim Astra got to north of 90% on RKGI 3.
Jared Friedman 17:54 ↗
Yes. I think a couple months ago, this was in the low two digits, right? Which is an impressive leap.
Diana Hu 18:00 ↗
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, which old SaaS 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 at zero in revenue, and it has gone from by the end of the batch it was about 8K in MRR, now it's, like, about 20K in MRR, and a lot of these...
Garry Tan 19:02 ↗
That's a huge jump. That's, like, non-trivially big jump for the median, right? The average is even higher.

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APA

Tan, G. (2026, September 17). The State of Startups in 2026 [Interview transcript]. Y Combinator. CEOInterviews.AI. https://ceointerviews.ai/interview/3001076/

MLA

Garry Tan. "The State of Startups in 2026." Y Combinator, 17 Sep. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/3001076/.

BibTeX
@misc{tan2026_3001076,
  author       = {Garry Tan},
  title        = {The State of Startups in 2026},
  howpublished = {Interview transcript, Y Combinator. CEOInterviews.AI},
  year         = {2026},
  month        = {sep},
  url          = {https://ceointerviews.ai/interview/3001076/},
  note         = {Speaker-attributed transcript with timestamps}
}