Looking back at our notes on SpaceX diligence call notes, two things stand out: 1) Almost nobody could see the economics working 2) Everyone was terrified of betting against Elon They have since: - Completed hundreds of launches - Put >10,000 Starlink satellites in space - Learned to catch rockets out of the sky - Equipped thousands of planes with Starlink Congrats @elonmusk @SpaceX.

happy 4th! 🇺🇸🇺🇸🇺🇸

GROWTH FOUNDERS: HIRE A NEAR-PEER A portfolio founder approaching $100M in ARR asked me about the single biggest and most impactful hire they can make. I thought for a bit tand said: "Hire a near-peer". In every generational company I've been part of, the founders hired a near-peer, who was essential to the company's success. - Google: Larry and Sergey hired @ericschmidt . - Facebook: Mark hired @sherylsandberg . - Square: Jack hired @rabois . - DoorDash: Tony hired @chrispa - Coinbase: Brian hired @emiliemc Characteristics of a near-peer: 1. They're so good that the founder will be fine reporting to them if the roles were reversed. (Mark has said publicly that he'd be fine reporting to Sheryl) 2. Their strengths perfectly complement the founder's strengths; however, they share many cultural attributes with the founder and pass the founder's airport test, since the founder will be spending a ton of time with them (example: Eric being a Computer Scientist, which was culturally very important at Google back in the day) 3. They're systems builders who have already operated at the scale you're growing into. Pattern recognition on $100M to $1B is not something you build in real-time. A near-peer lets the founder focus on what only the founder can do (product, vision, culture). The near-peer handles everything else. Also, near-peers stay for the long haul. Decade-plus tenure is standard. The reason this hire matters more than any other: after $50M ARR, the bottleneck shifts from product-market fit to organizational scale. The founder is still the visionary. But the company needs someone who has already scaled a company of that size. Most founders wait too long. They hire functional VPs first (Sales, Marketing, Engineering, Finance) and hope the collective covers the gap. It rarely does. A stack of VPs reporting into a founder who has never scaled a company creates coordination overhead, and the founder becomes the bottleneck. The near-peer absorbs that overhead. They turn the founder's vision into daily operating decisions. They give the VPs a leader who has actually run a company this size. Growth founders: if you're between $50M and $300M in ARR and every week feels like a coordination tax, the near-peer is the hire that determines whether you build a $10-100B company or top out at $1B. Start the search now, ideally through warm intros from your venture/angel investors and advisors.

Agent and Exa Connect are now live in our MCP! Find any data both on the web and from providers like Similarweb and Zoominfo directly within Claude and Codex exa.ai/docs/reference/exa-mc…

Bridgewater, one of the worlds largest hedge funds, a Tinker customer talks through how they've carefully fine-tuned a model focused on what makes interesting financial news. Their fine-tuned model is more effective and cheaper than any frontier model.

People sometimes ask why fine-tune when general-purpose models keep getting better. Bridgewater's work is a good reminder that with the right data -- here, expert judgements -- you can beat prompting-only approaches by a lot. @ddkang and the Bridgewater AIA Labs team are great -- glad to see them sharing this.

Bridgewater used their unique financial knowledge and partnered with us on @tinkerapi to fine-tune a model that helps their analysts focus on what's important. Experts improving AI that empowers experts. thinkingmachines.ai/news/lea…

my favorite type of CEOs

Atomic unit is a person, not a job spec.

A super long overdue (3 years?) post on scaling laws. Compute is expensive. Scaling laws are a way to help us reason about the optimal compute allocation between data and model size before committing to a large run. The post covers what scaling laws predict, how compute-optimal allocation works, why Kaplan et al. and Chinchilla disagree, and how data limits fitting details make extrapolation tricky. lilianweng.github.io/posts/2…

Absolute banger of an opener, new media nailed it with this one.

Really critical point from @pmarca on why founder-led comms are central to enterprise sales more broadly: "Are you important enough to meet with the CEO of your customer? Are you important enough to get in the room with the decision maker?" "The trick is everybody just naturally thinks inside out, 'me and my company and my product out into the world.' Don't think that way. Think in terms of, what are the most interesting things happening in the world, and then how do those things relate to us?" Absolute catnip.

Introducing Exa Connect: connecting agents to data beyond the public web. Available today with ZoomInfo, Crunchbase, Similarweb, and many other leading data providers. exa.ai/connect

Exa Agent is now available in Google Sheets! Generate huge lists, enrich data, and much more. Installation instructions below 👇

GLM 5.2 in Amp. Zero data retention, US and West-based inference. It's a good model. Try it now: amp update amp plugins add --auto-update @amp/glm-52-mode amp --mode glm-5.2

Why going direct is about telling a story much bigger than your company's: @pmarca: "The story of you and your startup is not inherently an interesting story, but there is almost certainly an interesting story that involves your startup, and this is sort of the cheat code of it." @bhorowitz: "The grand wizard of this is Alex Karp. If you watch his interviews, he never talks about Palantir. The only thing he ever says about Palantir, Marc pointed this out to me, is 'ontology' and 'orchestration,' two words that nobody knows what they mean." "Nobody knows what Palantir does as a result, but it doesn't matter because it's the future of the US military, Palantir. Superintelligence, Palantir. Whatever the story is that's really good, Alex will go tell that story. Neurodivergence." "Whatever is interesting, he'll just start talking about. And then because he's this founder of Palantir, the CEO of Palantir, like that just works." "When something happens in the world, something happens involving US military, AI in the military, or this or that, geopolitics with China, he's the first phone call, right? Because he's the guy who's been out there talking about that." @eriktorenberg: "Ryan Petersen... has done a phenomenal job of that." @pmarca: "The difference between talking about freight versus talking about 'the global supply chain is completely collapsing' during COVID, and 'we're all gonna starve to death.'" "And then therefore, he's the guy who literally goes on 60 Minutes to explain to the world that in fact, yes, we all are about to starve to death." @typesfast

A16Z New Media is the newest expression of this strategy. When you help founders directly with the work of being interesting constantly over time, that work compounds in value: in founder goodwill and portfolio outcomes, in follower growth and channel reach, and in tacit knowledge of how to launch a company really well. To make this work, you need quality and quantity. Writing one great essay every once in a while, or producing one charming video, isn’t going to cut it. You need to be relentless if you want a media asset to actually compound, not just make one nice launch video. To paraphrase Elon, “Anyone can make a nice car once. I’ll be impressed when you can make a million cars.” ^So many earned secrets in this write up by @eriktorenberg and our 🐐’ed New Media team. Happy 1y!

From the trenches of our CharacterAI days, @NoamShazeer is the 🐐 researcher and an even better human being. Few people have had a bigger impact on the history of AI. And there’s zero question few will have a bigger impact on its future. Huge congrats to Noam and the @OpenAI team!! ❤️💪

11x builds high-performing AI SDRs on top of Exa: "Exa helps us both find leads that are exhibiting these signals and do deep research enrichment on these leads". - Prabhav Jain, CEO @11x_official

Stockfish-level web search

AI will achieve Stockfish-level coding and generalized computer use