Lightcone: Consumer is back, What’s getting funded now, The vibes immaculate
Harj Taggar (host), Garry Tan (host), Jared Friedman (host), Diana Hu (host), Jared Friedman (host)
In this episode of Y Combinator, featuring Harj Taggar and Garry Tan, Lightcone: Consumer is back, What’s getting funded now, The vibes immaculate explores yC’s AI Supercycle: Consumer Revival, Dev Tools Boom, Crypto Cools Off The Y Combinator partners discuss why the Winter 2024 batch feels uniquely energetic, driven largely by an AI platform shift that’s resetting what’s possible in software and startups.
YC’s AI Supercycle: Consumer Revival, Dev Tools Boom, Crypto Cools Off
The Y Combinator partners discuss why the Winter 2024 batch feels uniquely energetic, driven largely by an AI platform shift that’s resetting what’s possible in software and startups.
Roughly 70% of companies are AI-focused, with major growth in developer tools and open-source infrastructure, and a noticeable return of consumer ideas after years dominated by B2B SaaS and tech‑enabled ops-heavy businesses.
The batch is far more technical (99% have technical founders), more U.S.-centric, and significantly earlier-stage, yet collectively tripled ARR in three months, reflecting how quickly AI products can translate into real revenue.
Meanwhile, categories like local marketplaces, international clones, and crypto have sharply declined, as founders and investors reorient around AI-native opportunities where every legacy SaaS dollar feels up for grabs again.
Key Takeaways
AI is now the primary startup frontier, not a niche.
Nearly 70% of YC’s Winter 2024 companies are AI-based, compared to 8% four years ago, signaling a true platform reset where new tools, apps, and business models are being invented rather than marginally improved.
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Consumer startups are back—but must avoid “tarpit” ideas.
Founders are increasingly pivoting into consumer, which can be powerful and fun, but YC cautions against easy, overdone ideas (e. ...
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Developer tools and open source are booming alongside AI.
YC funded about 30% more dev tools than four years ago and 5x more open-source dev tool companies; patterns like RAG, fine-tuning, and evals are still immature, creating big “picks and shovels” opportunities for tool builders.
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Highly technical founders now have a clear edge in AI.
With 99% of companies having a technical founder (up from 88%), cutting-edge AI work effectively requires deep technical competence, reversing the pandemic-era tilt toward domain experts in ops-heavy, tech-enabled businesses.
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Crypto enthusiasm has been displaced by AI, even in a bull market.
Despite Bitcoin’s new highs, YC is seeing almost no crypto companies this batch, due to both regulatory chill and the fact that ambitious engineers now see AI—not crypto—as the most exciting, high-upside space to build in.
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AI startups are generating real, fast-growing revenue—not just hype.
From start to Demo Day, the batch’s aggregate ARR grew from $6M to $20M, even though 80% started with no revenue, showing that AI products are quickly converting into paying customers and tapping into labor—not just software—budgets.
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We are still early in the AI cycle—comparable to web circa 2007.
YC partners compare today’s moment to the early web era: companies like Airbnb, DoorDash, and Coinbase emerged years after the platform shift began, implying that the biggest AI-native companies have likely not been started yet.
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Notable Quotes
“There’s a platform shift, and this is the moment where every single SaaS dollar in the world is up for grabs again.”
— Jared (YC Group Partner)
“This batch has felt like there’s more energy than for as long as I can remember for any YC batch.”
— Jared (YC Group Partner)
“In 2020, starting a US-based consumer idea was ill-advised. If you were doing it, you were probably working on a bad idea.”
— Harj (YC Group Partner)
“Dev tools is basically B2B SaaS but consumer style—you’re marketing to 20 million developers instead of a billion consumers.”
— Garry (YC Group Partner)
“If now is the equivalent of 2007 for the web, it was still three years until Airbnb, five years until DoorDash, six years until Coinbase. These trends always play out much longer than people think.”
— Harj (YC Group Partner)
Questions Answered in This Episode
How can founders distinguish between a genuinely novel AI consumer idea and a classic “tarpit” concept that will struggle to scale?
The Y Combinator partners discuss why the Winter 2024 batch feels uniquely energetic, driven largely by an AI platform shift that’s resetting what’s possible in software and startups.
Get the full analysis with uListen AI
What specific types of AI developer tools or open-source projects are still underbuilt and most attractive to YC right now?
Roughly 70% of companies are AI-focused, with major growth in developer tools and open-source infrastructure, and a noticeable return of consumer ideas after years dominated by B2B SaaS and tech‑enabled ops-heavy businesses.
Get the full analysis with uListen AI
For non-technical founders, what realistic paths exist to participate in this AI wave without being at a permanent disadvantage?
The batch is far more technical (99% have technical founders), more U. ...
Get the full analysis with uListen AI
How should founders think about competing directly with incumbents like Salesforce or OpenAI in an AI-native way rather than just adding features?
Meanwhile, categories like local marketplaces, international clones, and crypto have sharply declined, as founders and investors reorient around AI-native opportunities where every legacy SaaS dollar feels up for grabs again.
Get the full analysis with uListen AI
Given the AI–crypto contrast, what lessons from the crypto boom-and-bust should founders apply to avoid building overhyped but low-utility AI products?
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Transcript Preview
It feels like there's more energy around this batch than there has been for- for as long as I can remember for any YC batch. Like, w- what do you think is happening?
There's a platform shift, and this is the moment where every single SaaS dollar in the world, uh, it's up for grabs again.
The batch 3X'd ARR in three months, which is pretty cool.
That's a great growth rate.
(laughs)
Yeah.
It's a fun time to build. It's the best time ever. Even as a, as a builder. Because, like, the technology just does such a different thing than what you expected before it.
Welcome back to another episode of The Light Cone. We're four group partners at Y Combinator, and we funded hundreds of companies, many dozens of which have gone on to become unicorns. This is Jared, I'm Garry, this is Harj, and this is Diana. We just finished the Winter 2024 batch of Y Combinator, and it feels really, really different, doesn't it?
It does. Let's talk about how this batch is so different from the batches that we've funded in the past.
Some of it is, you actually need to know where we've been and where we are right now in order to actually figure out where we're gonna go, and a lot of people watching right now are trying to figure it out. Like, "How do I go to where the hockey puck is going? How do I get there before everyone else?" The best way to figure that out is what happened in this batch.
We're gonna connect the dots with actual numbers that I don't think we ever shared before, by stats of batches from four years ago, and contrast them with the numbers for this batch.
So you can see the actual trends, the way they're playing out, here in the center of Silicon Valley.
Yeah, I'm curious, like, what are some of the trends that we've seen? What's made this last Winter '24 batch different to previous batches?
Well, the strongest trend, the one that everyone is writing about, is AI. That's definitely, like, the big mega-trend in the past year.
Yeah, I was surprised, uh, when we were pulling up some of the numbers. It's just under 70% of the ideas are AI.
70% of the batch.
Yeah, that's wild.
That's wild.
Yeah.
It's about 170 companies.
Yeah.
Versus Winter '20, we only had 8% of the companies. Maybe one of the notables from Winter '20 that you worked with, Jared, was, uh, Replicate.
Yeah, those Replicate founders, they were into AI before it was cool, which was really awesome because they got to then ride this wave. But the first three years of Replicate was slow-going 'cause there weren't a lot of people working on AI. They were building tools for people working on AI, there weren't many customers.
And we didn't call it AI as much back then. We called it machine learning.
Machine learning, totally.
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