Scott Wu
San Francisco, California, United States
11K followers
500+ connections
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In August 2022, I witnessed the birth of a scrappy little AI startup with big dreams and a relentless focus on democratizing knowledge. Less than…
In August 2022, I witnessed the birth of a scrappy little AI startup with big dreams and a relentless focus on democratizing knowledge. Less than…
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Peter Thiel’s Founders Fund just doubled down on Icon. To celebrate, I'll give you $69,420 if you refer someone I hire. We’ve gone from $0 to $5M+…
Peter Thiel’s Founders Fund just doubled down on Icon. To celebrate, I'll give you $69,420 if you refer someone I hire. We’ve gone from $0 to $5M+…
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Excited to share that I'm joining the Enterprise GTM team at Cognition. Looking forward to working with Scott Wu, Russell Kaplan, David Morse, and…
Excited to share that I'm joining the Enterprise GTM team at Cognition. Looking forward to working with Scott Wu, Russell Kaplan, David Morse, and…
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Really great to see the progress that the Cognition team is making with Devin. Software development has been one of the primary beneficiaries of the…
Really great to see the progress that the Cognition team is making with Devin. Software development has been one of the primary beneficiaries of the…
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Big announcement from Scale AI today: Scale will be collaborating with the US DoD and the CDAO on a testing & evaluation framework for LLMs in…
Big announcement from Scale AI today: Scale will be collaborating with the US DoD and the CDAO on a testing & evaluation framework for LLMs in…
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Thrilled to finally be announcing our $43mm Series B, led by New Enterprise Associates (NEA) with participation from both Andreessen Horowitz and…
Thrilled to finally be announcing our $43mm Series B, led by New Enterprise Associates (NEA) with participation from both Andreessen Horowitz and…
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I’m excited to share that I’m joining Kleiner Perkins as a Partner to invest in the next generation of history-making founders, esp. those working on…
I’m excited to share that I’m joining Kleiner Perkins as a Partner to invest in the next generation of history-making founders, esp. those working on…
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*We're hiring!* Looking for product designers who are excited to build Lunchclub, where our mission is to create meaningful professional connections.…
*We're hiring!* Looking for product designers who are excited to build Lunchclub, where our mission is to create meaningful professional connections.…
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Gabriel Jarrosson
YC has quietly built a parallel tech ecosystem. Not just a network - an entire operating system for startups. Think about it: A YC founder can build their entire stack using only YC companies. Infrastructure, analytics, payment processing, marketing tools - it's all there. At friend-and-family prices. When you launch a product to the YC network, you get something priceless: A group of technical founders who actually understand what you're building. They become your first users, your debuggers, your evangelists. This is why PostHog is now used by 65% of new YC companies. This is why Brex dominated fintech... and why each YC batch makes the next one stronger. A true compounding advantage.
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Nick Mehta
A bit late to the party, but Brett Queener's post on the death of the schema from earlier this month is one of the best pieces of writing out there on the future of SaaS x AI. Paralleling, in a way, Andrew Karpathy's most recent YC Startup School talk on the future of programming, Brett talks about the nerdiest, yet most vital leg of the stool that traditional enterprise software stands on - the database schema. A schema is fundamentally a way to model a business process (e.g., CRM, HCM, ERP) into a data model (e.g., a database). Schemas are why we use terms like "Accounts" and "Opportunities" so fluidly. But they're also why SaaS can sometimes feel rigid. But with AI, schemas don't have to be fixed anymore. And because schemas aren't fixed, UIs don't need to be either. Brett hints at the big prize at the end of the post - Reinforcement Learning for enterprise domains. While RL has been optimized (through Human Feedback) for our general use of chatbots like ChatGPT and has been further tuned for technical fields like math and coding, it still has a ways to go in being optimized for vertical and domain-specific use cases. Dynamic schemas + contextualized UIs + domain-specific RL = software that will be more powerful than any of us can imagine. It's not coming overnight, but it will be here soon. Link to the post is in the comments. Definitely worth a read. Thanks to Brett for writing it!
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Anish Acharya
The big labs are expansive in their product ambition, especially since foundation models have largely improved in lockstep - in order to compete with them you have to do things they won’t which are: - building a very rich software ecosystem around a primitive - orchestration across multiple models - going insanely deep on product and growth for a narrow vertical domain
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Maggie Basta
So, it turns out there is actually no meaningful correlation between how quickly a generational startup gets to $100M in ARR and the magnitude of its eventual success. Decided to pull this data because every time you turn a corner in SF, there is another VC debating whether the "triple-triple-double-double-double" paradigm is dead because a handful of ripping AI startups are sucking the air out the room for everyone else. That would suggest that nuking to $100M overnight is the only way to win But if the past is any indicator, that’s probably… not true. There have always been companies that blow traditional growth benchmarks out of the water and ones that grow more steadily over time. (We’ve all seen the “Fastest to $100M” charts). But when you actually compare that speed to the size of eventual outcomes, there is really no correlation. In fact, if you look at the value of these companies at their respective peaks, there is actually a slightly inverse relationship between speed and success. So, a couple takeaways: (1) $100M is a milestone (albeit an important one), but it’s not the final destination. We are talking about truly generational companies. At that level of scale, the real north star looks more like ten billion than hundreds of millions, and in case you forgot, $100M is just 1% $10B. (2) Speed is not the only playbook. Time to $100M isn’t destiny, and some of the biggest outcomes took longer to get there while others around them grew faster. To be abundantly clear, getting to $100M that quickly is an extremely impressive feat and indicative of companies building incredible products. That should not be discounted, and we will 100% continue to look for these kinds of investments. Too far in the other extreme is also true (limping to 100M with decelerating growth is probably not… great). But none of that detracts from the fact that it is a long road to success in this industry. There are many ways up the mountain, and it takes time to build something enduring!
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