Chris S. @ChristosSchnabl

Technical judgment gets more valuable as generating code gets cheaper

Veee @vikktorrrre

2 days ago

Sam Altman: coding is no longer the safest skill to bet your future on. “Learn to program was so obviously the right thing over a recent period of time, and now it’s not.” “Become high agency.” “Get good at generating ideas.” “Be very resilient. Be very adaptable to a rapidly

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@vikktorrrre Technical judgment gets more valuable as generating code gets cheaper

Most overnight successes and years in the making

Ben Cera @Bencera

2 days ago

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@Bencera Most overnight successes and years in the making

Important work

Kevin Bass @kevinnbass

2 days ago

I have conducted an audit of Anthropic's finances. What I have found is so shocking that I am calling for a Congressional investigation. Anthropic is not just seeking regulatory capture. It has built a regulatory capture machine that cannot be turned off. Structural financial

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@kevinnbass Important work

Product Management is still about telling stories

Josh Elman @joshelman

2 days ago

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@cb_doge I think this is worth doing

I think this is worth doing

DogeDesigner @cb_doge

3 days ago

ELON MUSK: AI competitors should peer review each other’s models before release. “I would recommend that we at least have some sort of informal weekly or biweekly call and that there’s maybe a week or two weeks of early access by competitors. This is why I think the incentives

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open source won’t pace

@DarioAmodei Dario is right👀

Dario is right👀

Dario Amodei @DarioAmodei

4 days ago

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our

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$1.1B for the Machine Age.

a16z's David George says AI's power law is becoming more extreme because dollars alone can compound a company's advantage: "Right now, clearly the power law is more extreme than it has been in the last 10 to 20 years of technology investing, probably going back to the emergence of the network effect-driven consumer companies." "Increasing returns to scale have always been a dynamic in our business... Brand reputation in the market, the accumulation of resources, all provide competitive advantages." "That all still is the case. But right now, especially with the labs, for the first time in my career, you can take capital and throw it at a company, and it compounds their advantage." "How do you screw up a startup? Throw too much money at it and have them hire 1,000 people, and then you create all these coordination issues and overhead issues and dueling priorities... because you can't hire enough people to do enough things fast enough." "Now that's not the case. You can throw dollars at compute, and compute can make products and the businesses better. So to me, it's not terribly surprising that the power law is more extreme. Right now, economies of scale are a very real thing in the AI market, and I think it'll continue to be the case." @DavidGeorge83

a16z @a16z

5 days ago

Accolade Partners' Aram Verdiyan with a16z's Jen Kha and David George on AI's extreme power law and where the next trillion dollars gets made: The classic way to blow up a startup was throwing too much money at it. Hire a thousand people, create dueling priorities, and kill what

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Trillions of dollars in value has been accruing in private markets: - A 75th percentile tech IPO lists at $3.5B - The ten companies on this chart cleared that by 12-500x in private rounds Full piece from a16z's @jkhamehl on why most portfolios have no exposure to this: a16z.news/p/catching-the…

Jen Kha @jkhamehl

5 days ago

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a16z's David George says the real economy has barely begun adopting AI, while the top 1% in one dataset already spend $7,000 per employee per month: "Part of the thing that we're monitoring, which makes us extremely bullish about AI, is just actual diffusion into the real economy." "The median company in the US is spending $12 per employee on AI per month. The top 1% of the dataset that we've seen is spending $7,000 per employee on AI per month." "Not only have we had limited diffusion beyond coding, but if you just look at the shape of who is consuming tokens and actually getting real value out of AI today, we're super early. The most cutting-edge banks are probably doing 1% of headcount cost on AI tools." "The reason this makes me very bullish is these are the fastest-growing companies we've ever seen, of all time. They're adding more revenue per month than the mega-cap tech companies." "And yet it's probably on the back of adoption of 10 million users, maybe 20, maybe 30 max. And I think it's going to transform the way we do a lot of work." @DavidGeorge83

a16z @a16z

5 days ago

Accolade Partners' Aram Verdiyan with a16z's Jen Kha and David George on AI's extreme power law and where the next trillion dollars gets made: The classic way to blow up a startup was throwing too much money at it. Hire a thousand people, create dueling priorities, and kill what

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The SpaceXAI IPO produced more exit value than the previous five years of venture exits combined 2022 raised: $222 billion 2025 raised: $75 billion 2026 YTD exits: $2.18 trillion Full piece from a16z's @jkhamehl on why venture outcomes are changing the math for allocators: a16z.news/p/catching-the…

Jen Kha @jkhamehl

5 days ago

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"The day SpaceX went public, historical asset allocation went out the window. Technology is the dog that caught the bus." "What was once success in venture (a unicorn) is now your average Wednesday and private companies are generating $1B in revenue on a timeline measurable in quarters." "While we don't invest with that expectation at the outset, the majority of the portfolio can go to zero and we can still generate outperformance from a small handful of power law winners." "It's not just a smaller number of companies generating the returns. It's a smaller number of funds with exposure to those companies." "Winning begets winning: a fund that lands one behemoth gets the follow-on rights, the founder referrals, and the information edge that make it more likely to land the next one. Access compounds the same way outcomes do." a16z's @jkhamehl on the case for resizing venture: a16z.news/p/catching-the…

Jen Kha @jkhamehl

5 days ago

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Accolade Partners' Aram Verdiyan says less than 1% of venture firms have delivered consistent 3X net returns over the last two decades: "If you as an allocator have not had access to the top five to 10 companies over the last five to 10 years, you're significantly behind in terms of returns." "We've looked at the data of 3,000 venture capital firms in the US. Only 20 have achieved consistent 3X net returns over the last two decades." "20 companies. Less than 1%." "What's interesting is the consistent ones consistently had access to the category-defining companies every vintage. And by the way, just having the logo is not sufficient. If you're early stage and you have a large fund, you need to own enough of it." "Venture-like returns are possible in late stage, but your best company should be five, 10% plus of your fund. That way, you can actually return the fund on a single company. Fund-returning math in late stage didn't exist before. It now does." "The ones that consistently have gotten access are in that top 20 out of 3,000. So if you don't have them, there is a huge dispersion of returns. And if you don't have those, you're getting the average venture return." @aramverdi @jkhamehl @davidgeorge83

a16z @a16z

5 days ago

Accolade Partners' Aram Verdiyan with a16z's Jen Kha and David George on AI's extreme power law and where the next trillion dollars gets made: The classic way to blow up a startup was throwing too much money at it. Hire a thousand people, create dueling priorities, and kill what

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