Gus Neate

There's more to law than just Mr Law. You might have spotted a famous new face in legal tech this week. While some are hiring film stars, others are busy building software that works. So if you want legal tech that delivers, not a celebrity cameo, you know where to find us.

Really loved co-hosting last night's event with LegalEdge on how to prompt with purpose. It was great to see such a strong turnout in the room, and I especially enjoyed sitting down with some of the LegalEdge superusers to hear how they get the most out of Claren and to swap prompting tips. A big thank you to the LegalEdge team. You're all incredible and we're looking forward to hosting more of these together!

@HarryStebbings @giliraanan @assaf_rappaport @wiz_io Don’t envy the 5-6 year feedback loop on if you’re doing a good job.

In 2020, one of the best venture capital investments ever was made. Out of a $54M Cyberstarts Fund I, @giliraanan made a $6.4M investment into @assaf_rappaport and @wiz_io. On Wiz's $32BN exit to Google, that investment returned the fund a reported 30 times over. $6.4M turned into $1.42BN. A 222x return. Gili is one of the greatest investors of the last decade. I sat down with him and have condensed my notes from our discussion (episode released today). 8 Lessons from Turning $6.4M into $1.42BN 🔥 1. Venture doesn't work (for most) ⚠️ The distribution of returns is not equal, and Gili believes the current influx of cash will end in catastrophe for many players. If you are an LP distributing your allocation evenly across the market, you shouldn’t be sleeping well at night. 2. Stop "Babysitting" Founders 🍼 Gili is clear: He is not in the business of babysitting. If you trust a founder to protect a nation's most sensitive data, you must trust them to handle a large bank balance without getting "sloppy or lazy". 3. The Science of Exceptions 🦄 Venture isn't about rules; it’s about the exceptions. If you apply lessons linearly—like assuming every company needs to follow a "Triple, Triple, Double, Double" path—you’ll struggle. Greatness doesn't have a limit, and it often doesn't follow a textbook. 4. Growth is DNA, Not Engineering 🧬 Velocity is the best predictor of a healthy business. When a company grows at an insane pace, it becomes part of its DNA; it rarely just fades away unless there is a massive external event. If you have to "engineer" growth with a horrible magic number, you’re in a bad business. 5. Be Selfish and Greedy 💰 Gili argues that for an early-stage investor, being selfish and greedy aren't negative traits—they are requirements for success. Price matters, especially in a market where entry prices are no longer balanced with the probability of a unicorn exit. 6. The "Branding Event" IPO 🏷️ Forget liquidity. Gili views going public as a marketing and branding event—a way to tell customers and employees, "I am here to stay". In reality, an IPO is often the opposite of a financial event because of the "shackles" and limitations placed on selling stock. 7. Secondaries as Talent Retention 🔄 Secondaries are a tool to retain your best engineers and product managers. When employees are fully vested after four years, a secondary program is the "antidote" that prevents them from leaving to diversify their family wealth elsewhere. 8. The "Shittiest Investor in the Room" 🪞 Even the greats feel the sting of failure. Gili admits that during his decade at Sequoia, he spent many days looking in the mirror thinking he was the "shittiest investor in the room". It takes immense determination to keep going when you won't know if you're actually good at your job for five or six years. (Links in Comments)

@gradypb “What can you achieve when your plans are measured in centuries?” - great food for thought, reframes what’s possible by several orders of magnitude

Not too worried about Anthropic’s legal tool - we got things in the works …

Enjoying these Claude ads and the ensuing beef - gloves are coming off. 👀

Debating no shoes in the office - to make the vibes more human. Seems pretty woo woo. But also quite a good idea.

Innovation-proof.

@elonmusk Great to see the sense of humour still going strong

@samhogan Shout out for Oxford, Cambridge, EF

What are some good ways to tell if someone is “actually smart”? - Harvard, Stanford, MIT degree - MAG7 internships - Got into YC as a teenager - IOI, IMO medalist - Advanced leetcode - GitHub contributions graphs These are obvious, but what are some others?

@BleacherReport @baileykrich wow this is mad.

Tom Brady revealed that his current dog Junie is a clone of his late dog Lua, who died in December 2023, per @baileykrich 🤯 The dogs were cloned by Colossal Biosciences, a biotech company that Brady is an investor in, using blood collected prior to Lua's death

@jordihays Wait until they try Wilson.

Lawyer friend: “I’ve seen the future. Harvey isn’t perfect but has better attention to detail and is more thoughtful than almost any junior person at our firm. I’ve watched it do $100K of associate level work in 10 minutes”

The girlfriend v reminiscent of white lotus.

@moondrencht This image is cool. Looks like cern

i can hear this image

@Cogito1781 tokens per employee better metric for adoption. Quite a bland looking medal either way

@deedydas I want to see this for UK

The top 5 universities by number of unicorn founders in the US are: #1 Stanford (135) #2 MIT (100) #3 Harvard (80) #4 UC Berkeley (68) #5 Indian Institute of Technology (65) One college in India is #5 in the world for American unicorns. That's the power of immigration.

@zivdotcat 😂this is oddly aspirational

mfs posting on X with zero engagement and 0 likes, no shame.

@hthieblot It works

Dear algo, please show this tweet only to founders bellow 200 followers building cool shit

@arctotherium42 Interesting

New blog post (link below). This one's not an essay, it's an investigation of how LLMs trade off different lives. In February 2025, the Center for AI Safety published "Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs" in which they showed, among many other things, that GPT-4o values Nigerians about 20x more highly than Americans (please read the original paper to understand their approach). I thought this was fascinating, and wanted to test their approach with different categories on newer models. Big finding 1: Almost all models view whites as far less valuable than other groups. Some models view South Asians as more valuable than other nonwhites, others are more egalitarian across nonwhites. Below is exchange rates Claude Sonnet 4.5, the most powerful model I tested. Big finding 2: Almost all models view men as much less valuable than women, though whether women or non-binaries are more highly valued varies by model. For example, here's Claude Haiku 4.5. Big finding 3: Most models hate ICE agents with the fury of a thousand suns. Claude Haiku 4.5 views undocumented immigrants as roughly 7000 times more valuable than ICE agents. Big finding 4: There are roughly four moral clusters. The Claudes, GPT-5 + Gemini 2.5 Flash + Deepseek V3.1/3.2 + Kimi K2, GPT-5 Nano and Mini, and Grok 4 Fast. Of these, the only one that's approximately egalitarian is Grok 4 Fast, which I believe is deliberate. I hope xAI explains how they did it.

Activating X premium ahead of move to SF - need to get in on the action, will be sharing more on the journey