WDW

Harvey just hit $100M+ ARR. $8B valuation. 50 of the top AmLaw 100 as customers. On paper, this is the textbook AI success story. But here’s what a VC partner noticed and what the tweet is hinting at: actual usage within firms appears low. We’ve seen this exact movie before. Microsoft cut Copilot sales targets by 50% last month after enterprise customers refused to move beyond pilots. Less than 2% of Office 365’s 400 million users have paid Copilot subscriptions two years after launch. The pattern is consistent: executives buy enterprise AI to look AI-native, employees don’t use it, renewal conversations get awkward. Harvey’s own data shows usage climbed from 33% to 69% over 12 months among their “all users” base. That sounds good until you realize that means at any given firm, roughly 30% of lawyers with access aren’t touching the product. The tweet identifies the real problem: law firms bill by time. AI compresses time. Consider the math. If AI reduces a 20-hour document review to 2 hours and you’re billing hourly, you just lost 90% of that revenue. The efficiency gain goes to the client. Partners watching their billable hours evaporate don’t rush to adopt tools that accelerate their revenue decline. Harvey’s CEO Winston Weinberg acknowledged this in multiple interviews. He argues certain legal work is increasingly billed via fixed fee and that “AI will increase work for lawyers.” Maybe. But BigLaw hasn’t changed its business model since the 1970s. The median AmLaw 100 firm still generates 85%+ of revenue from hourly billing. The founding story is legitimately remarkable. Weinberg was a first-year associate at O’Melveny when his roommate Gabe Pereyra, a DeepMind researcher, showed him GPT-3. They built a proof of concept using Reddit landlord-tenant questions, had three attorneys review the outputs, and 86 out of 100 got “send with zero edits” approval. A cold email to Sam Altman and Jason Kwon at OpenAI led to their first funding check. From there, the trajectory went vertical. $5M seed in November 2022. Allen & Overy rolled it out to 3,500 lawyers by early 2023. $21M Series A. $80M Series B. $300M Series D at $3B in February 2025. $300M Series E at $5B four months later. $160M more at $8B in December. $760M raised in 2025 alone. That’s not organic growth. That’s kingmaking. VCs pour capital into a company to signal solidity, which encourages enterprise customers to sign big contracts, which justifies the valuation. The flywheel only works if actual usage follows the logos. A former Harvey employee reportedly claimed retention hovered around 35%, though Harvey’s official figures show higher engagement. On r/legaltech, practitioners report that usage concentrates among junior lawyers and “return use” is low. A Harvard Business School case study from March 2025 explicitly states that “while Harvey had successfully focused on aggressive customer acquisition, retention was now the key challenge.” The structural tension: law firms need to demonstrate AI adoption to clients who increasingly demand it. 67% of corporate legal departments expect their outside counsel to use AI. But if firms actually deploy it effectively, they compress billables and hurt their own economics. Some firms navigate this by keeping AI efficiency gains as margin expansion rather than passing savings to clients. A 2025 study of 600+ legal leaders found that 79% of law firms using AI are pocketing the savings rather than reducing client costs. In some cases, they’re charging more for “AI-enhanced work.” That model works until clients figure it out. Corporate legal departments aren’t stupid. They’re watching bills carefully and asking firms in RFPs how AI reduces legal costs. The firms that can’t demonstrate value capture through efficiency face pressure from competitors who can. The bigger question for the $8B valuation: can Harvey grow into it?

My AI investment thesis is that every AI application startup is likely to be crushed by rapid expansion of the foundational model providers. App functionality will be added to the foundational models' offerings, because the big players aren't slow incumbents (it is wrong to apply the analogy of "fast startup, slow incumbent" here), they are just big. Far more so than with any other prior new technology, there is a massive and fast-moving wave that obsoletes every new app almost as fast as it can be invented. There is almost no time to build a company and scale it. There are two ways AI application startup founders can make money: - Make a flash-in-the-pan app that generates a ton of cash and bank the cash (my estimate is that you have about 12-18 months cashflow generation) - Make a good enough app that you get acquired by one of the big players for sufficient equity The situation is highly unstable - we don't know if it's going to crash or go to the moon but both scenarios make it very unlikely that any AI application startup will independently become a generational supercompany (baseline odds are low to begin with). The best odds are finding an application niche in a highly specialized field with extremely unique and specific data barriers, ideally ones relating to real atoms (hardware or world-related) data and not software/finance.

BREAKING: Stanford just surveyed 1,500 workers and AI experts about which jobs AI will actually replace and automate. Turns out, we've been building AI for all the WRONG jobs. Here's what they discovered: (hint: the "AI takeover" is happening backwards)

Financial Researcher/Analyst is now a prompt on Perplexity Labs

Maybe you can't control your IQ, but you can make decisions that are either extreme or midwit. And in my experience, life - health and fitness, socializing, investing, happiness, etc. - is better at the extremes. The middle is a trap - a place that breeds mediocrity and comfortable complacency. It's where dreams die and life passes you by. Living in the extremes is the spice of life. I grew up in a Texas cow town with less than 500 people, but went to Choate and lived in NYC, London, and Hong Kong. Of course, a Michelin-starred meal can be an experience that is, by definition, worth traveling out of your way for. But, at the same time, eating a $3 dinner on a milk crate in Cambodia is better than most midwit so-called fine dining. Don't count macros. Cook a steak. Seeing Kyoto on a bicycle or the Taj Mahal can change your life, but so can riding a horse at sunrise, where the wildlife doesn't care where you went to college or how many followers you have. The middle is thinking Audi and Louis Vuitton are nice. The middle will have you saying "IYKYK" on Instagram over some Carbone rigatoni. The middle is waiting in line to get into the Centurion lounge. The middle resides on LinkedIn. Drink your wine from a rocks glass. Take a trip with no luggage and buy what you need at a Walmart. Who cares? The real opportunities - the asymmetric returns - come from operating at the extremes. You can get full bloodwork done and adhere to some wacky Bryan Johnson regime, while at the same time, relying on basic intuition developed over hundreds of thousands of years of evolution. Take a walk. Watch the sun rise. You can accomplish everything you need to in a gym with some dumbbells and a bench. Or take pride and pleasure in manual labor. "Chop your wood and it will warm you twice." Equinox is midwit. The same is true with socializing. Trust me. Brunch with Ivy League bankers is vapid and tedious compared to beer and wings with rednecks and roughnecks. This also applies to investing. Keep it simple; allocate your investments across a concentrated portfolio of long-term holdings that you know, understand, and believe in. And, at the other end of the spectrum, add real estate, and a few 10-50x moonshots - startups, crypto, derivatives, whatever. Not only are they intellectually and financially fulfilling, it’s a great way to expand your professional circles, and open unknown doors of opportunity. You don't need apps to overcome boredom. Open a book. It's not rocket science. And of course... Go to bed tired.