California Pool Partners | Maple VC
Portland, OR
Joined January 2016
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Eric Johnston retweeted
Didn't exist 3 years ago, now employees ~30,000 people via M&A + AI 🤯
Today, Long Lake completed our $6.3B acquisition of Amex GBT.
Long Lake acquires and transforms generational businesses with AI across the American services economy.
Amex GBT is the travel partner for 17,500 businesses in 140 countries. Last year, Amex GBT booked 35 million trips for 10 million travelers.
This marks Long Lake’s 40th acquisition, and our family of companies now employs nearly 30,000 people.
We founded Long Lake three years ago with the thesis that AI is going to change every company, but there’s a large overhang between AI capabilities and how most businesses leverage AI tools.
We partner with strong, profitable, and growing businesses to help them deploy AI and improve their customer service.
Our first cohort of companies has doubled their EBITDA in less than two years through topline and productivity growth, all while increasing headcount. (We’re proud to say that we’ve never conducted a layoff.)
We’re excited to share a bit more about what we’ve been up to.
Eric Johnston retweeted
Very cool: Robinhood is underwriting the Oura IPO.
Robinhood’s IPO Access business previously just got shares from the banks underwriting an IPO and distributed them to retail.
Now, Robinhood is actually part of the underwriting syndicate alongside (though far smaller than) Goldman, Morgan Stanley, JPMorgan, BofA, etc.
Robinhood is helping sell the deal, taking underwriting risk (meaning they make a firm commitment to buy shares in the IPO), and will earn underwriting fees.
It’s cool because it very much aligns with their goal of democratizing investing… and they have something the bulge bracket banks can’t offer: direct distribution to 10s of millions of retail investors.
Historically you wouldn’t really want retail in the IPO, but RH makes it easier by saying “we’ll take a $100M block” and you don’t have to deal with 200k tiny investors.
Also notable: they were already investors in Oura via RVI, their closed end fund.
They are now investing in seed companies too via RVI 2, they could theoretically be a lifecycle capital partner to companies.
Eric Johnston retweeted
The new moats are the same as the old moats
Every few years, we fall in love with shiny new tech and forget the basic physics of consumer software.
We’re doing it again with AI.
The new moats aren't new at all. They're the exact same as the old moats: network effects, marketplaces, and platforms.
Right now, consumer AI is booming.
New agents like Instinct, Bot, and Tomo are dropping mind-blowing experiences. The underlying tech is incredible, but almost every product being built today shares the exact same challenge:
They are completely single-player.
Single-player products are 100% tied to value - and in this case mostly agent : model performance.
If a competitor drops an agent tomorrow that books travel faster, tracks habits better, or handles life admin more reliably, everyone can switch overnight because leaving is easy and has nearly zero friction. Especially when it is so easy to onboard with just a new message.
The legendary consumer tech giants didn't win because their underlying technology stayed marginally better forever.
They won because of structural lock-in:
Social Networks: You don't abandon WhatsApp for a prettier UI if your friends aren't there.
Marketplaces: Airbnb, Doordash, and Uber hold supply and demand in a tight loop.
Platforms: Apple and Android deliver you a complete device so you take advantage of the software on top of it (though this creates opportunities too)
Novelty gets you initial distribution.
Multi-user dynamics give you long-term retention.
If your consumer AI product doesn't become exponentially more valuable to User A when User B joins, you don't have a moat, just a temporarily superior feature set.
We are seeing this in the coding agents as people jump from tool to tool based on the best performance.
But… all is not lost. There are huge opportunities here. Agents will get better when more of our friends are on them and can help us coordinate and communicate to do more together. Agents that help us improve and strengthen our habits can get better as we add friends and hold each other accountable.
Data flywheels are great, but social and marketplace flywheels are what actually build enduring tech giants.
It’s time to stop building isolated AI tools and start building the platforms where people connect, transact, and coordinate together.
Eric Johnston retweeted
People often forget that Peter Thiel similarly ran a hedge fund during the dot com bubble era that ended up failing
He then turned around and started one of the most successful VC firms in history (Founders Fund)
I fully expect Leopold to make a similar comeback, whether it’s VC, another hedge fund or a startup
He is incredibly talented and still extremely young. Lot of room to run ahead
Leo sent a letter to the LPs last night, per the FT
“These were very expensive scars, but I am dedicated to ensuring they will be invaluable lessons for our organisation and for myself as we move forward,” Aschenbrenner wrote. “My core promise to you is that we will not waste the opportunity to learn from these events.” He added: “Over the past two years, we have delivered outstanding results, despite occasional sharp pullbacks. But our fund must always be structured such that we can take a loss and fight another day.”
There are few better learning experiences that a 25 year old investor could ask for. Excited to see what Leo does next.
Eric Johnston retweeted
The Swedish Model is a culture built on frugality, autonomy and a relentless focus on cash flow and small markets.
Eric Johnston retweeted
Databricks could have gone public in 2020 at a comparable scale to Snowflake.
Instead, it stayed private and raised an estimated $28B across seven subsequent rounds.
Consider two scenarios based on public comps:
- A hypothetical 2020 listing, resulting in a public company worth ~$200B in 2027.
- The current trajectory, where Databricks goes public at a valuation of ~$200B in 2027.
The difference between these scenarios is the 7 years of private capital at a cost of around 18%, versus public capital at a cost of 12%.
As a result, 2020 shareholders have sacrificed ~$30B of present value in order to stay private, and venture capitalists expanded their fee income by ~$6B.
Even the carried interest from a much larger 2027 IPO is lower, if you factor in the time value of money.
Unfortunately, it's easy to grandstand with the TVPI on earlier investments and obscure the damage done to the company by injecting more capital.
Eric Johnston retweeted
When “disciplined” investors abandon their zone of genius, it’s usually a sign the cycle is peaking.
Benchmark launching a growth fund. Fintech funds leading defense co rounds.
Greed is a hell of a market indicator.
Scoop: Benchmark has raised $2 billion across two new funds, including its first growth fund, a big shift for a firm that spent decades defending a smaller, focused approach to venture investing. Details here:
wsj.com/finance/investing/si…
Eric Johnston retweeted
It begins:
The whole thesis I hear VCs say of “you will always want the latest frontier model” falls apart once unit economics come into question
We partnered with @FireworksAI_HQ to train open-source models for legal. Here's what we found:
1) Hybrid legal agents can beat frontier models on quality and cost by routing selectively to a frontier advisor.
We tested a hybrid setup where GLM 5.1 served as the primary worker, routing tasks to Opus 4.7 as an advisor when needed.
GLM invoked Opus sparingly, just 0.83 times per task on average.
The hybrid setup beat Opus on both quality and cost: 18% all-pass vs 14%, at $368 vs $954 across the same 100 tasks.
2) Post-training can push open models to frontier-level legal performance.
On a 100-task slice of our Legal Agent Benchmark (LAB), SFT moved Kimi 2.6's all-pass rate from 11% to 15%, beating Opus' 14%.
But the cost gap was even more striking: $84 vs $954 across the same 100 tasks, or ~11x cheaper.
We're excited to continue working with @FireworksAI_HQ on the next generation of open-source legal agents.
We need a new return metric for venture. IRR is overweighted to time. MOIC is better but ignores time altogether. The right metric is MOIC / year.
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Eric Johnston retweeted
A statement from Anthropic CEO, Dario Amodei, on our discussions with the Department of War.
anthropic.com/news/statement…
Eric Johnston retweeted
You only have 9 years to start an AI-native investment bank before all the big ones let their analysts use this.
Claude in Excel is now available on Pro plans.
Claude now accepts multiple files via drag and drop, avoids overwriting your existing cells, and handles longer sessions with auto compaction.
Get started: claude.com/claude-in-excel
Eric Johnston retweeted
IT’S TIME TO READ
ICYMI: Packy McCormick's 16,000 word deep dive on a16z
notboring.co/p/a16z-the-powe…
“a16z is a Firm. It is a business, a company. It is built with the goal to scale, and to improve with scale. There are many characteristics of a Firm that I believe do not apply to a traditional Fund, and we will cover them. I think this distinction solves one of the oddest things about venture capital’s self-image: that venture capital is an industry that sells the world’s most scalable product (money) to its most scalable companies (technology startups) but must not, itself, scale.
This distinction - Firm > Fund - comes from a16z GP David Haber, the most East Coast Finance of the bunch and a self-described student of investment firms as businesses. ‘The objective function of a fund is to generate the most carry with the fewest people, in the shortest amount of time possible,’ he explains. ‘A Firm is about delivering exceptional returns, and building sources of compounding competitive advantage. How do we get stronger with scale, not weaker?’”
More from David on Firm > Fund in today's Idea of the Week: a16z.news/p/firm-fund
@dhaber
Not an offer or solicitation. None of the information herein should be taken as investment advice; Some of the companies mentioned are portfolio companies of a16z. Please see a16z.com/disclosures/ for more information. A list of investments made by a16z is available at a16z.com/portfolio.
Eric Johnston retweeted
Canadian schools are massively underrated — yet they’ve produced some of tech’s biggest founders 🇨🇦. To your point, @chamath, I should add @rxin, cofounder of @databricks via @UofT to my list. cc @MapleVCFund
Eric Johnston retweeted
Many home service owners obsess over technicians, and they should. Ops matter.
But too often the brand gets ignored. And that’s the ceiling.
You can run a tight operation and still feel stuck competing on price if customers don’t recognize or trust your name. A strong brand is what turns you from “a contractor” into the obvious choice.
Brand isn’t just a logo. It’s the expectation people have before they call:
- how your phones are answered
- how techs show up and communicate
- reviews and reputation
- trucks, uniforms, website, ads
- the consistency of the whole experience
Operations get you in the game.
Brand is what creates lasting advantage.
Quick gut check:
If someone sees your truck, do they instantly know what you stand for?
If not, you’re leaving differentiation, and profit, on the table.