About a year ago, Alphabet's growth-stage venture arm, Capital G, named partner Laela Sturdy as its new head, just as the division's founder, David Loewy, stepped down.
Few were surprised by Sturdy's promotion to the post. She joined Google in her marketing role in 2007 and was pulled into many departments over the next few years, and in 2013 she was hired by Rowley when CapitalG was launched. Ta. Lowry told CNBC in 2021, Laella's name came up a lot when it came to figuring out who the stars were within Google. ”
Of course, for many investors, the past year has been the toughest of their careers. We wondered if the same was true for Sturdy, a former college basketball star. She quickly realized that 60% of her team had diverse or underrepresented backgrounds. To find out more, we caught up with her earlier this week at CapitalG's bright and airy offices in San Francisco's Ferry Building. Below are excerpts from the chat, lightly edited for length and clarity.
I would like to congratulate you on your appointment. How does your management style differ from that of your predecessor, David?
I still lead investments and serve on many boards, but I also loved being able to bring more focus to the team and think about how we can continue to grow the company.There is 1708154134 CapitalG has many more great investors.
There are about 50 people on the team. How many of these are investors and how many are not?
Our model is to find ways that Google and Alphabet can help our portfolio companies. So we can contribute ideas, not just to the individuals on this team, but to you as well. [of what I mean]Over the past several years, more than 3,500 diverse senior advisors within Alphabet have helped partner with portfolio companies. [to help with] Pricing analysis, infrastructure expansion, marketing, and setting up sales incentives. Growth-stage companies come up with all kinds of technical and business questions, and that's our area of expertise.
Access to 3,500 different senior advisors! How does it work?
As an example, over the past few years we've partnered with the Google Training team to train Google engineers in AI and ML. We said, “This training is really effective and is very well received within the company.'' And many of our portfolio companies are asking, “How can we level up our engineering and organizational talent to take full advantage of the AI trends?” So we partnered with our training team to give our portfolio companies access to the exact same training, which is now available to hundreds of engineers in our portfolio. Before coming to CapitalG, I worked at Google for a long time, and one of the amazing things about Google's culture from the beginning is a true culture of knowledge sharing.
The market for AI talent is highly competitive. What can you say to portfolio companies who are concerned about the information flowing in and out of Alphabet through you?
From a portfolio company perspective, everything is opt-in. we don't share anything. We operate completely separately. We do not share our portfolio companies' data with Alphabet, nor do we share Alphabet's data with our portfolio companies. We exist as an intermediary to find where there is a win-win.
As an example, [Google Cloud] Continues to be a great market development partner [and] We don't impose anything on anyone, as all other cloud providers are important and great partners as well. We can help you facilitate the right introductions, marketing partnerships, and relevant product discussions.
How are decisions made within CapitalG? Who has the final say on who sees the check?
We have an investment committee [composed of] Me and the other three general partners are really great investors. For example, my partner Gene Franz, who I've worked with for the past 10 years since pretty much the beginning of CapitalG, is a long-time investor who previously was at TPG and elsewhere. [joining the outfit]. So we've built a very strong GP bench and these GPs bring deals to the investment committee and we make decisions as a committee.
How many bets do you make per year? And what size checks do you write?
Typically, we invest between $50 million and $200 million in each company. We're very papers-driven, so we spend a lot of time digging deep into sectors. .We invest in about 7-8 new companies a year and typically [many] Further updates [rounds] to our existing portfolio.
How much equity in the company do you aim to own?
We will respond flexibly to ownership percentages. What we're looking at is the money-on-money rate of return in these companies. For example, I led his Series D round for Stripe in 2017. I think his valuation was $9 billion. [We closed] Recent AI investments have been around for some time and were valued at less than $500 million. So we're very focused on the market, how differentiated the business is, and whether we can invest significant capital to scale. .
What is cash-on-cash return?
We don't share them publicly. We do not share returns publicly.
At $9 billion, the investment in Stripe will likely pay off. Stripe's valuation rose to $95 billion before being reset to $50 billion last year. Do you think the valuation changes were in response to market trends and performance?
Stripe is a great company and [tackling] This is definitely one of the biggest market opportunities, so I'm very bullish on its performance to date and everything that's going to happen. If you look at public and private valuations over the last 18 to 24 months, all of them are based on some sort of reset due to the impact of COVID-19. . .So I don't read anything about the company's performance.
Does Alphabet allocate you separate funds each year?
Yes, we are investing from separate funds, so it is an annual fund.
How big is it?
We manage $7 billion in assets [dating back to 2013].
That means you have a lot of money in a market where others don't have much. Are you buying up secondary shares because the IPO market is stagnant and other late-stage investors are reducing their investments?
We are very focused on partnering with CEOs and executive teams. We only invest when we have engagement with the CEO and data directly from the company. Our model is that we want to be the best partner for these founders and ensure that they can introduce us to the next best company in the future.Therefore, we are always directly involved
Which secondary shares did you purchase?
I won't mention specific companies. [publicly disclosed by the companies]. And many secondary sales end up being structured as primary sales. But the broader trends you mention are interesting because it's the early stage investors who are looking for liquidity. And I think that's right in line with our strategy of finding companies in their best growth stages at what we think are the very early stages of long-term compounding. [trajectory]So I'm very excited to be on the cap table for these types of companies. . . Our strategy is to partner with these companies early and then hold them for the long term.
However, the shares will ultimately be distributed to Alphabet.
We do have distribution, but I would say we have a long-term orientation.
Does Alphabet really care whether it delivers returns? Are these bets primarily strategic?
We are focused on delivering profit and leveraging the expertise and experience of Google and Alphabet to focus on our mission to be a world-class partner for this generation of technology companies.
It's clear that Google is working hard on AI. Please tell us a little about your unique AI strategy.
We're just as excited about AI as everyone else. We have a really great team within CapitalG focused on this space, another area where we have some very good advisors within Google, and they're allowing us to lean into even more technical bets. He gave it to me. Cybersecurity is a good example. We were in the Series B when CrowdStrike was making his $15 million or so in revenue. A big part of the early cybersecurity bet was a differentiated technology perspective. So we're bringing the same rigor to the AI field.
One of the things that we think is really interesting in the AI space is that if you look across the enterprise use cases, we actually think that a lot of incumbents are in a very good position. Because they have distributions, they have customers, and they have workflows. . . So what we've been looking at a little more closely is where there's real technical differentiation and where workflows and existing distributions are less important. One company we support and believe has strong technological differentiation is Magic. The company focuses on training his AI software engineers.
You're also on the board of Duolingo, which parted ways with 10% of its contractors last month. A spokesperson said at the time that the company doesn't need as many people to do the kind of work it does, thanks in part to AI. Is that a phenomenon you see across your portfolio companies?
I won't comment specifically on Duolingo, but I will say that our entire portfolio of companies is focused on how AI can improve the customer experience and enhance other systems and processes. I think there will be a lot of surprise and joy there. There's been a lot of overhauling of the marketing stack. There have been a number of changes to customer support and service. We're still in the early stages. But just as enterprise customers are excited to experiment with how they can leverage AI in their workflows, startups and growth-stage companies are also excited to use AI to improve their organization. We're seeing a lot of excitement about rethinking how we build and experimenting with ways to get results. All employees focused on the highest value opportunities. There's a lot of interesting work going on there.