Elad Gil is a successful founder and prolific investor who has become known as the largest independent venture capitalist in Silicon Valley given the amount of money he has invested in recent years, including institutions reportedly including the Harvard endowment Home.
His track record largely explains his quiet rise. For example, Gill invested in highly valued payments software company Stripe’s Series A round 11 years ago and has invested in its subsequent rounds. He also snapped up stakes in note-taking app Notion, cloud collaboration platform Airtable, military technology contractor Anduril and design tool Figma, which agreed to be sold to Adobe last September for as much as $20 billion — despite Adobe e Efforts are still underway to sell the merits of the deal to the DOJ authorities.
In a conversation late last week, Jill, who blogs occasionally but maintains a humble website, declined to answer specific questions about how much or how much he manages part of the amount he invests in the company . But quant VC firm TRAC calls him a “superforecaster,” having funded at least 155 companies with a “success rate” of 0.671, meaning 67 percent of his early-stage investments raised at least one round of follow-on funding, according to TRAC data. . (It says at least 30 startups in Gill’s portfolio have become “unicorns,” though, as Gill himself points out, many valuations will shift in the next 18 months or so. “Really tough times are coming coming,” he said.)
When we spoke to Gil, we asked what founders should do if things went from bad to worse. We also talked about his ongoing fascination with AI, and some of the early checks he wrote to startups that are now raising a ton of VC funding, including Character. AI, backed this year by Andreessen Horowitz, Perplexity.AI, backed by NEA and Harvey, backed by Sequoia Capital.
Recently, Gil shared how he is using AI to amplify his own work. You can listen to our full interview; in the meantime, below is an excerpt from that chat, long edited .
TC: A few years ago, you wrote a book called “The High Growth Playbook” on how to scale a startup from 10 to 10,000 people. Do you think there’s too much focus on growing so fast right now?
EG: If you catch the product magic moment, my book focuses on market fit, what do you do next. . . I think this mantra of growth for growth’s sake came mostly during COVID. As capital became very cheap and available, people started to scale when they were not a good fit for the actual product market. They start scaling before they have a lot of customers, or before they clearly have a moat that creates some sort of defensibility for their business. I think where things go off track is people start raising money years in advance where they are. Then they started hiring based on the money they raised, not based on the business they owned.
We heard many stories from employees who were eager to talk about mismanagement within their company as things progressed. Do you have any advice you can give the company on how to scale down without completely breaking it?
A lot of the assessments that people are actively doing are correct now is asking: where do I think this is going to happen in a year or three or five years ? What should I do if it doesn’t work? These are very difficult choices. People have to decide whether to shrink the team and possibly change direction, or try to sell the company because that’s clearly not going to work. Will they close and refund the money? If you look at when people have raised a lot of money over the past few years, that’s mostly happened in 2021. If people have raised money for three to four years and raised it when [they] have nine months left, that means a lot of people are going to have to start fundraising at the end of the year. So I think the real tough times are coming. I think it’s still kind of a warm-up period or an anticipation period.
In terms of your own investments, can you talk about how much? You raised money in recent years, how many companies are in your portfolio now? You raised $620 million in 2021 according to SEC filings. . .
I haven’t really talked about that much [and] I don’t actually know the exact number of [portfolio companies] right now. Traditionally, I would only invest my own money. Then things started getting bigger and bigger in terms of allocations that I could invest in, so in some cases I did what’s called an SPV, or a single purpose vehicle or investment.
Right now, my models are a bit of a mix, anything small, or if people just want me to be an angel, I can do it myself. I can use the fund if things get bigger. If things get really big, I can have a mix of personal money, foundation money, and SPV. I try to maintain a flexible approach so that as I work with different companies at different stages, I can adapt what I do based on what they really want and need. I want to avoid a situation where I have a ton of money and feel the need to invest a ton of money, pass it off to someone else, and start behaving badly.
You are more concerned with generating AI than anyone else. Has anything [at Generative AI Frontiers] released to the world in the last 6 to 12 months surprised you?
For me, in a sense, the biggest moment is seeing some really early GAN-based generative art [this is a class of artificial intelligence and machine learning algorithms]; it’s astounding what non-artists can do. And then a little while later, when GPT-2 and GPT-3 came along, that was obviously the moment when there was such a big step between them, it was obviously a sea change.
Are you an investor in OpenAI?
I’m not involved at a basic level with most of what’s going on at OpenAI, but I don’t want to talk about any particular company or anything.
Earlier this month you were on a panel in Los Angeles with Ashton Kutcher, whose Sound Ventures just raised a growth fund explicitly backing six There are a few foundational modeling companies out there—three of which it has invested in: OpenAI, Anthropic, and Stability.AI. How do you feel about this strategy?
There are a handful of companies that are really far ahead in developing these underlying models. And I do think they will have some scale and capital effects, at least for the bleeding edge models. So, for example, you know, GPT-4 still feels ahead of everyone else, and obviously, Google is capable of building something. Anthropic has been iterating on its cloud model. And some other players. There are Cohere and A121 [Labs] among others. But at least for now, proprietary models seem to be a generation or two ahead of open source models, and if you assume that each model will be significantly more expensive than the previous generation, then you can assume that this trend may still be there for at least a few more years.
This means two things. One is that when there’s GPT-7 or something, open source might be equivalent to GPT-6 or GPT-5.5. The performance of GPT-6 can be incredible. It could do all sorts of amazing things. So that begs the question of what is really cutting edge stuff, you need state of the art models, and that’s where I think there’s going to be a lot of value in this industry – but I think a lot of it also just involves falling behind by a couple of years generational things. This is where I think open source will also come into play.
So I look at it as a world where we’re going to have some really big, closed, proprietary models and an oligopolistic market kind of like the cloud world where we There are Azure, AWS, and Google Cloud as the three major players. I think the model might naturally converge there too. But then we’d have a bunch of open source that people would use at the same time to do all sorts of things.
Again, Gil has more stuff, including why he thinks more founders should consider closing and returning while they still can Capital, you can listen to our longer talk here.
