Benchmark’s view of AI racing: talking to Miles Grimshaw

At the end of 2020, Miles Grimshaw became — and still is — the most recent additions to the legendary joint venture company benchmarkstubbornly refused to change the basic way it operates, despite many of the changes the rest of the venture world has embraced — especially in terms of team size and assets under management.

With just five general partners, a few principals in its current 28-year history in Silicon Valley, and fund after fund under $500 million in size, the company has Disappointing report in turn must compete with competitors with increasingly large checkbooks. Of course, a lot of those 2021-era deals and funds today look like bad bets to the people who have backed them, while Benchmark – those who have placed bets in the past include Uber, Snap, WeWork, and Sorare — it’s smart to stick to the traditional early stage. invest.

It made us curious to know Grimshaw – a Yale graduate who was previously a general partner with Joshua Kushner’s Capital development — makes up the way Benchmark works. We’re also curious to understand Benchmark’s thoughts on another potential bubble: innovative AI.

To be sure, Grimshaw’s past and present companies appear to be taking very different approaches. Thrive dove right around a while ago, round 300 million USD in OpenAI at a valuation of $29 billion. Meanwhile, in early spring, Grimshaw led a 10 million USD round beads in LangChainhelp developers build more complex applications on top of large language models such as those built by OpenAI.

We spoke with Grimshaw last week about that and more in a conversation quoted below and lightly edited for length and clarity.

TC: This is the first time we met. Did you study at Yale, and was there a transition between college and joining Thrive Capital in New York?

MG: Well, my journey to work with the team at Thrive was by accident in 2010. In many ways, I’m probably a very classical liberal arts student, even though I’m technically a major. economy.

At the time, the question was: can you have a Silicon Alley? And the people on the East Coast found each other and banded together and said, Yeah, we can, let’s do it, let’s build. And so when I was at Yale, I met Will Gaybrick, who was actually studying at Yale Law School at the time – he became one of Thrive’s partners then CFO. [and now a unit president] of Stripe — and he and I became friends naturally because of our similar interests in application products and software, and he happened to know Josh from his college days, and I started I started hanging out with them in New York for the weekend and then said, ‘Let’s make a team,’ so I officially joined in 2013, which was when I graduated.

I am the fourth or fifth person; we had a total of eight people, I think at the time, including the head of finance and the EA, so we’re in the corner of what is now a very large office and you feel a bit like like bystanders are proving it’s possible and it’s a really fun time.

May I ask quickly: Are you Australian? Are you from New Zealand?

I am English. [Laughs.] It’s a very messy accent because I grew up in the UK until I was 12, then moved to Boston. I am the eldest in a family of seven children. You can move on to the next oldest – no stress – so I was right to withhold a few words.

I just read yesterday about someone described as having “can not be replaced voice.” How are Thrive and Benchmark different from an operational point of view?

At Benchmark, we keep it simple and consistent. There are only five of us. It is always an equal partnership, with somewhere in scope [traditionally] five to six partners, each focused on making one or two commitments per year. In many ways, a big part of it is not capital but commitment to serve to help amplify the odds and scale of founders’ success.

Has Thrive grown much yet? They have developed their property under management.

I don’t know the exact types of recent figures. But Josh and Karen [Zaki] and Vince [Hankes] and the team there, I deeply respect and admire their ambition to serve people in different ways. I know after I left, there was 2 billion USD fund and I think since then fund 3 billion USD. I’m not sure exactly how big the team has been lately, but I think they’ve continued to build a variety of functionality and support for the founders and so last I heard, it was big. several times more than when I left.

In terms of AI, you led the seed round in Langchain. What is the business model there? Is this a SaaS business?

Yeah exactly. In the space between the app experience to be built and the model at the bottom of that stack, there’s a lot of need to be met with great software. [Thanks to the large language models we’re seeing like GPT-4], standards are raised and what we expect in software is also raised, and no company wants to be a dinosaur after a meteor, panicking and wandering around, thinking that everything is real. happy. What LangChain is supporting is that app developers going to market will say: ‘Okay, great, there’s this language model that generates tokens — how do I bring that model? into a great product experience and workflow for your customers?’

Where do those developers find LangChain?

It is remarkable word of mouth in many ways. We are definitely not marketing. We started earlier this year and now have several engineers but no one but one engineer on the team, obviously very active in the open source community. I think its Discord currently has about 20,000 members. team is [also] at a lot of events where a lot of engineers and app developers come and try to learn, imagine and create. And so they are in the flow of all that energy.

I’d love to know that you led a $10 million seed round in this company and that, like a week later, Sequoia led the $20 million round. Is it right?

I forgot the exact time, but yes.

Is Benchmark an investor in any platform model companies?

We are a partner of Cerebrus, a company that manufactures GPU chips [off which AI models run] but we are not partners at the platform model level.

Do you have the opportunity to invest in these companies? Apparently, these outfits raised a lot of money. I wonder if that is a factor.

We don’t start decision making from a prism, we’ll limit ourselves to $10 million or $5 million or whatever. We started from the desire to be the first and most influential partner to the founders and served on their board for a decade and that is what the job is and if the money is worth it. start-up support may be larger than usual, we will solve that problem together.

But we found no confidence in imagining the long-term outsized market share that either of them might have. I think you see this in the open source coming out and quickly catching up. Can you imagine the input for some of these [large language models] obviously reducing costs over time, whether it’s the amount of compute available on a chip or the cost of any chip. It’s clear that knowledge is spreading, and more and more people know how to do it and don’t need a lot of money just trying to figure out how. And so you’ve even seen depreciation rates in some like OpenAI’s model. Like, think how quickly they used up all the spending they made on GPT-2 or GPT-3.

We’re certainly grateful for all the hard work and definitely think they could be good business, but instead we’re focusing on the developer layer above that. . .and is very focused and looks forward to meeting and collaborating with everyone on that journey.

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