Chris Keith

We raised our $750 million Series D at a $20 billion valuation from @benchmark, @generalcatalyst, @nvidia, @salesforce, and @zoom. @mercor scaled from $1M to $3B in run-rate revenue in 27 months, the fastest in history to $3B. For 2 years, we've organized human intelligence to build evals and training data for every frontier lab. The labs are the leading indicator for AI startups, then the Fortune 500. Our growth has accelerated over the past 6 months as enterprises start evaluating and training their own models. For many, owning their intelligence is existential.

How soon should we see AI's impact in productivity statistics? With the PC, it took 14 years for aggregate productivity growth to show up. Economists didn't see it in their analysis for another five years. But work by @erikbryn and others showed individual firms seeing results by 1987 (although that work was published 9 years later.) With genAI, individual companies will report results well before we can see aggregate impact. And our data (and others) show that some firms are reporting exactly those early results. It shouldn't surprise people if today, four years after ChatGPT and three years after general availability of enterprise GenAI services from Microsoft and Google, we can't be confident that the strong productivity growth numbers released are really driven by GenAI. It's just too soon for big companies to show huge results and too soon for AI-native startups to be big enough to matter. If AI is more like electricity than the PC, and requires wholesale redesign of business operations, it might take even longer to show up in aggregate statistics. But this doesn't mean the corporate spending on AI won't increase as firms figure out how to get better results. These firms will face their own individual J-curves, where their total investment runs ahead of results, even as they become successful. (The reason is that once you figure out how to succeed in one domain, you'll apply that playbook to several others, all of which will need investment before payback). If AI is really boosting productivity, I reckon aggregate numbers might start to persuasively (but not unimpeachably) show that by 2028.

We’re moving from an era of AI where the output comes roughly at the rate that you can chat back and forth with the AI to work with you, to a period where you can set a problem for a set of agents to go off and do an arbitrarily large amount of work for you. This means productivity gains that are maybe 20-50% to gains that don’t really have an upper limit. Agent swarms and the ability to fan out complex work across many agents doing tasks in parallel provide a massive unlock in a lot of spaces. This will lead to qualitatively different outcomes in my fields. This has already been seen across the coding domain. Next, cyber is almost entirely a problem space where more agents reviewing more things will lead to far better outcomes. We’re seeing the same now in many scientific fields, and this almost certainly will change life sciences. But this will increasingly be true in any field where you can parallelize computer-based work to complete something faster or do something at a totally different quality level. Which is actually are some of the most valuable domains of knowledge work today. Our brains aren’t really wired for the new scenario we’re heading into where compute becomes the variable that we can flex to solve any problem that we want. We’re used to thinking that the amount of time that goes into a task is correlated to the output that we get from it. And most domains of knowledge work or science have generally always been correlated with this. That’s changing forever.

Having fun going deep on Elon.

Dont equate a brands success with some random employee who worked there. we had a department lead get poached this year. they were fine, department was functioning. but Ridge is crushing, the name meant something on a resume, and they got recruited. The department currently doesnt have a leader... AND IT IS FUCKING RIPPING. 2x the performance as before. A rising tide lifts a lot of boats. Inside and outside your org. Brand success can cover up for a lot of mediocre sins.

BREAKING: Goldman Sachs banned bankers and traders from using AI tools like Claude Code

.@dylan522p explains his position that the first trillion dollars of AI spend won't be used to replace white-collar work: "Replacing white-collar work is something that will happen, but that's not going to drive the first trillion dollars of AI spend. Those are not industries that are going to diffuse AI capabilities quickly. It's going to take them quite some time to reorder how their OpEx is spent. Because companies have a lot of inertia with regard to people's jobs, changing how their compensation works, how many people work on what, etc." "There are areas where we think that intelligence is very, very important, though. These include areas like chip design, cybersecurity, financial services, life sciences, materials science, software engineering. You can absorb unlimited intelligence [in these areas]. And there are two reasons for that." "One is that it's a domain where humans aren't anywhere close to the frontier and there's just so much to discover. Think materials science, chip design, anything in the scientific realm. We figure out new stuff, we deploy it, we make everyone's lives better." "And there's the other world which is adversarial. Specifically, finance and cybersecurity. It's human vs. human, and we're constantly going to be leveling up, either trying to arb each other like quants do, or trying to hack each other and then play defense. So there's this constant demand for intelligence because when you have more intelligence than the other parties in the market, you win."

BREAKING: Josh Kushner and Bob Iger are inviting investors to join their Lakers ownership group for minimum $250M commitments They expect investors to put significantly higher amounts into the deal

Databricks CEO Ali Ghodsi says if frontier models stopped advancing, it wouldn't matter for most orgs because enterprise AI is bottlenecked on context, not intelligence: "There's no agentic work that's automated the whole enterprise. That has just not happened. Why is that? The real reason is the models are smart enough, but they just don't have the context that exists inside of any organization." "They have not been in every meeting. They don't know what's in everybody's heads. They don't know all the processes. There's always a couple of employees who know everything in every organization. You go tap on their shoulder, and everybody's like, 'Oh my God, what would happen if he or she quits?'" "If you just fused that and gave that context into the AI models, just the frontier today, I think there's so much productivity gains you could get for any organization on the planet." "For that, we actually don't need smarter models... If the frontier doesn't advance, it doesn't actually matter for the vast majority of organizations on the planet. They're just so far behind in the adoption curve of actually automating things and getting value out of this stuff." @alighodsi Read the latest Profiles of the Future by @bhorowitz and @mikemcg0 on Databricks & the Future of the Firm: a16z.news/p/databricks-and-t…

Reddit call was absolutely fascinating. Everyone should listen to it as a bellwether for where the internet is going - AI Mode is increasingly default Google experience - AI Mode provides rich info and data in line, less incentive to leave search - AI Mose incentivizes dialog, Google wants to keep you engaged to serve more ads at each turn - Google will milk search for as much revenue as possible as they transition from a search company to a cloud service and chip company - As traffic from humans becomes more scarce this will put Google in an increasingly adversarial position to the rest of the internet - This is a massive headwind to all media type companies who are not destinations - This is a massive headwind to all content-driven go-to-market motions especially in the SMB. You have seen companies like HubSpot and Monday.com get crushed by this funnel collapse We are entering the end game - a knife fight for the remaining and dwindling volume of human traffic on the internet