The contrast between hanging up the last phone call of the day of high-stakes decisions and then a minute later walking in the door to the pure love of small children who want to laugh and play and show you every discovery they made that day is the strangest and best thing I have ever experienced in life.
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Since 1830, technology has cut the American workweek from 69 hours to 38 while raising real income per person roughly 20-fold.
Properly managed, A.I. can do the same.
My
@nytopinion Chart:
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Proud of this. Open is the way.
“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.)”
This is, to a much greater extent than most people realize, how progress in AI will play out. Companies everywhere are taking the productivity gains from AI and using them to be way more ambitious. Grow faster and ship more!
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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.
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Its easy right now to confuse the person with the era
When I started in venture, I read
@eladgil's High Growth Handbook
Picked it up again after 7+ years in VC, and it's still the best single resource on how startups actually work
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When I shared
@harvey’s model strategy a few months ago, there were two parts:
1. Build our own model
2. Use that to help customers do the same
We’ve done the first. Now we’re hiring for the second: Harvey’s Private Model Program.
We’re seeing huge demand from law firms to own their own intelligence leveraging private data.
This will enable them to become frontier firms that get smarter with every client matter.
You’ll:
- Partner with law firms to build these systems.
- Build the team that delivers this at scale.
- Work with our technical org to define the platform that powers this team.
We’re looking for a technical PM or founder type to own Harvey’s Private Model Program.
DM me if this sounds interesting.
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Applies to some of todays extrapolations as well
Generally reason founders burn out - working on things you feel obligated to do but hate vs things you love
A few thoughts on the current state of venture capital.
When the Music Is Playing
In July 2007, a few weeks before the credit markets seized up, Chuck Prince, then the CEO of Citigroup, gave an interview to the Financial Times. The line everyone remembers is this one: "As long as the music is playing, you've got to get up and dance." He was mocked for it for years afterward, and he lost his job a few months later. But I have come to think he was saying something honest. He wasn't claiming the music would play forever. He was admitting that he couldn't sit down while it was still going, and neither could anyone else in his seat.
I've been thinking about that quote a lot lately, because right now is the most disorienting period in venture capital I can remember, and I have been doing this for a while.
Here is what makes it disorienting. It's not that things are bad. Some things are spectacular. We have companies in our portfolio growing faster than anything I have seen in my career, and I don't say that lightly. At the same time, we have companies with no revenue, no product, and a founding team you could fit in a conference room raising billions of dollars at valuations of $10 to $50 billion. Both of these things are true at once, and if you try to reason about them with the same framework you will drive yourself crazy.
Two ideas have helped me make sense of it. Neither is mine.
The first is reflexivity, which George Soros has been writing about since the 1980s. In most of life, perception follows reality: the weather is what it is, and your opinion of it changes nothing. In markets, it runs the other way too. Prices change what participants believe, and what participants believe changes the prices. The feedback loop can run for a long time, and while it's running it looks exactly like progress.
Here is how reflexivity is playing out in AI. Full disclosure: Menlo is an investor in Anthropic, so read the following with that in mind. People watched a frontier lab go from a $4 billion valuation to $18 billion, then $60 billion, then $180 billion, then $380 billion, and now something close to a trillion. They drew the obvious conclusion: that is what a neo lab looks like. So the next neo lab gets priced off that path, not off anything it has built. Then it gets marked up in a subsequent round, and the markup itself becomes the proof. Look at Thinking Machines. Look at Reflection. At that point valuation has stopped being an output of the metrics and has become the metric. Nobody is discounting cash flows. They are discounting the last round.
Soros is very clear about one thing, and it's the part people skip: you cannot know when or how a reflexive process ends. You only know that it does. Every one of them has.
The second idea is Chuck Prince's, and it explains why smart people keep dancing even when they can see the loop for what it is. As far as I can tell, there are two groups on the dance floor.
The first group got in early. Firms like ours were in some of these AI companies before the numbers got silly, and the paper gains are enormous. When you are sitting on gains like that, you start to feel like you're playing with house money. I have been around long enough to know that house money is the most dangerous kind, because you don't respect it the way you respect money you had to earn.
The second group missed the early rounds and knows it. Their LPs know it too. So they are trying to make up for lost time by writing very large checks very late, which is the one strategy almost guaranteed to turn a missed opportunity into a real loss.
House money on one side, FOMO on the other, and reflexivity feeding both. That's the whole story. Everyone has a reason to keep dancing, and the reasons are different, which is why nobody can talk anyone else off the floor.
So what do you do? The instinct in our business is to answer with company identification: just pick the right neo lab and you'll be fine. I think that's the trap. When price has become the signal, being right about the company is not enough, because you can be right about the company and still be wrong about the price by a factor of ten. The public-market investors I admire figured this out a long time ago. They spend as much time on how much to own as on what to own.
The winners in venture over the next decade will be the firms that treat portfolio composition and position sizing as seriously as they treat sourcing. How much of the fund is in companies whose valuation rests on the last round rather than on revenue? What happens to the portfolio if the reflexive loop breaks next year instead of in five? Those are not exciting questions. They are the ones that will matter.
The music will stop. It always does. Dance if you must, but know where the chairs are.
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Excited to welcome
@asadovsky as Harvey’s Chief Research Officer.
Before Harvey, Adam co-led post-training at Microsoft AI and Google DeepMind.
As a CVP at Microsoft AI, he helped build MAI-Thinking-1, Microsoft’s reasoning model.
As part of Gemini’s leadership team he helped train Gemini 1.0 through 2.5, including fine-tuning, RL, data, and evals.
His prior work as a Distinguished Engineer at Google spanned Assistant, Search Quality, and Search Infrastructure.
I met Adam three years ago when I sent him a cold LinkedIn DM and was surprised he responded.
At a time when most dismissed the application layer and legal, Adam was curious and generous with his time.
He quickly became someone I regularly turned to for advice on AI as we scaled Harvey over the past three years.
When we first met, we were too early to hire someone of his caliber and scale, but I always hoped we’d eventually work together.
As Winston and I got to know him better, what stood out even beyond his technical achievements was his character.
Despite his incredible technical career, he remains curious, humble, practical, and cares deeply about the teams he builds.
We couldn’t think of a better leader to help us build frontier intelligence for the professionals and institutions we serve.
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Jensen Huang pushed back hard against AI labs calling for tighter regulation and slower AI development, at Dreamforce.
"If you are not confident about the safety of the products, and you're not confident in its functionality, capability, or safety, then don't just release it.
We don't need any new laws. We don't need new regulations. we just need companies to decide that when it's time to run as fast as they can."
safety and speed are not mutually exclusive, and new laws are not required to make AI systems safer. Build fast, test aggressively, and pause only when you are no longer confident the product is safe.
---
From "Salesforce" YouTube channel, (full video link in comment)
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Very funny that xAI was created to stop Anthropic which was created to stop OpenAI which was created to stop Google which would've actually never developed ASI because it was afraid of cannibalizing its ads revenue from search.
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A few weeks ago, a company we invested in shut down.
The founder sent a very detailed email to the investor base explaining the situation.
I responded with three clear questions:
1. I am very sorry to hear this, are you ok? Losing a company is a very personal loss. I want to make sure that you yourself are okay.
2. Is there anything that I can do in the next steps with the investor base to help?
3. What are your thoughts on your next steps? Is there anything I can do to help facilitate those?
This is not the time to discuss lessons or negotiate for cents. This is the moment of peak pain. Be gentle.
The way you act in hard times is the way you will be treated in good times. People will always appreciate you for thinking long term and being there for them when it matters.
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We are simultaneously ramping into the singularity & seeing odd investor interest for non-exponential companies
NVIDIA compute is fungible, durable and highly rentable. It is a productive, revenue-generating asset.
I love Zach Dell's two notebook idea.
"I'm the kind of person who needs to write clearly to think clearly."
Two different colored notebooks to distinguish when you're working in your business vs working on your business.
Working "in" the business (red notebook, at the office): Handling day-to-day operational problems and near-term issues.
"When I'm working in the business I'm blocking and tackling and solving problems that are blocking us today. I'm trying to figure out personnel problems and product problems and acute issues that are near term."
Working "on" the business (black notebook, at home after hours): Strategic thinking, planning 6–12 months out, war-gaming, and imagining big ideas.
"When I'm working on the business I'm thinking six months out, 12 months out, and kind of strategic war gaming and chess playing."
Zach deliberately segments his day: office hours for operational work, then time at home (after his wife goes to bed) with no phone or computer, just the black notebook for focused strategy:
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