Alex

@alstras

Oct 20

Encode Club

@encodeclub

Oct 20

Meet the judges for Encode London 2026!

We have judges joining us from...
@CoreWeave, @GoogleDeepMind, @MongoDB, @FlywheelOS, @GeniusTerminal, @droid_run, Tenor (YC S26) and Penelope Health.

The judges will be deciding bounty winners and selecting our finalists, who will demo e Hub!

A few tickets left ↓

Alex

@alstras

Oct 16

Raunak

@raunakdoesdev

Oct 16

hello we need some more b200s/b300s for training

looking to get ~4-12 more nodes (ik not a ton)

happy to lock in for 1-3 years if the price is good

pls feel free to dm what price you can do based on commit length 🙏

Alex

@alstras

Oct 10

Satya Nadella

@satyanadella

Oct 9

Introducing Microsoft-Decision-1, our new model for fast decision-making.

It delivers top performance on structured decision tasks, outperforming both LLMs and other decision models in latency and quality.

We’re already testing it across Microsoft for everything from incident ntrol to scientific discovery.

Alex

@alstras

Sep 23

Garry Tan

@garrytan

Sep 23

The ceiling on what we can do is so much higher now!

Alex

@alstras

Sep 23

Ornn

@OrnnExchange

Sep 23

Can the rental price of GPUs predict stock prices?

Ornn's A100 GPU rental index has led Astera Labs's stock price by about 5 weeks.

- The index's 20-day moves line up with ALAB's 20-day moves 25 trading days later (r = 0.74).
- Moved forward 5 weeks, the index tracks ALAB's removing the shared upward trend.
- It holds across the year, and it holds even after stripping out the chip sector's own moves or NVDA's.

Astera Labs makes the connectivity chips inside AI servers. GPU rental prices show how tight AI capacity is right now. The companies that sell into AI server build-outs are priced on that tightness after it shows up in orders.

Ornn prices compute where it actually trades. The signal shows up here before it shows up anywhere else.

data.ornn.com

Alex

@alstras

Sep 23

Venky Ganesan

@venkyganesan

Sep 20

A few thoughts on the current state of venture capital.

When the Music Is Playing

In July 2007, a few weeks before the credit markets seized up, Chuck Prince, then the CEO of Citigroup, gave an interview to the Financial Times. The line everyone remembers is this one: "As long as the music is playing, you've got to get up and dance." He was mocked for it for years afterward, and he lost his job a few months later. But I have come to think he was saying something honest. He wasn't claiming the music would play forever. He was admitting that he couldn't sit down while it was still going, and neither could anyone else in his seat.

I've been thinking about that quote a lot lately, because right now is the most disorienting period in venture capital I can remember, and I have been doing this for a while.

Here is what makes it disorienting. It's not that things are bad. Some things are spectacular. We have companies in our portfolio growing faster than anything I have seen in my career, and I don't say that lightly. At the same time, we have companies with no revenue, no product, and a founding team you could fit in a conference room raising billions of dollars at valuations of $10 to $50 billion. Both of these things are true at once, and if you try to reason about them with the same framework you will drive yourself crazy.

Two ideas have helped me make sense of it. Neither is mine.

The first is reflexivity, which George Soros has been writing about since the 1980s. In most of life, perception follows reality: the weather is what it is, and your opinion of it changes nothing. In markets, it runs the other way too. Prices change what participants believe, and what participants believe changes the prices. The feedback loop can run for a long time, and while it's running it looks exactly like progress.

Here is how reflexivity is playing out in AI. Full disclosure: Menlo is an investor in Anthropic, so read the following with that in mind. People watched a frontier lab go from a $4 billion valuation to $18 billion, then $60 billion, then $180 billion, then $380 billion, and now something close to a trillion. They drew the obvious conclusion: that is what a neo lab looks like. So the next neo lab gets priced off that path, not off anything it has built. Then it gets marked up in a subsequent round, and the markup itself becomes the proof. Look at Thinking Machines. Look at Reflection. At that point valuation has stopped being an output of the metrics and has become the metric. Nobody is discounting cash flows. They are discounting the last round.

Soros is very clear about one thing, and it's the part people skip: you cannot know when or how a reflexive process ends. You only know that it does. Every one of them has.

The second idea is Chuck Prince's, and it explains why smart people keep dancing even when they can see the loop for what it is. As far as I can tell, there are two groups on the dance floor.

The first group got in early. Firms like ours were in some of these AI companies before the numbers got silly, and the paper gains are enormous. When you are sitting on gains like that, you start to feel like you're playing with house money. I have been around long enough to know that house money is the most dangerous kind, because you don't respect it the way you respect money you had to earn.

The second group missed the early rounds and knows it. Their LPs know it too. So they are trying to make up for lost time by writing very large checks very late, which is the one strategy almost guaranteed to turn a missed opportunity into a real loss.

House money on one side, FOMO on the other, and reflexivity feeding both. That's the whole story. Everyone has a reason to keep dancing, and the reasons are different, which is why nobody can talk anyone else off the floor.

So what do you do? The instinct in our business is to answer with company identification: just pick the right neo lab and you'll be fine. I think that's the trap. When price has become the signal, being right about the company is not enough, because you can be right about the company and still be wrong about the price by a factor of ten. The public-market investors I admire figured this out a long time ago. They spend as much time on how much to own as on what to own.

The winners in venture over the next decade will be the firms that treat portfolio composition and position sizing as seriously as they treat sourcing. How much of the fund is in companies whose valuation rests on the last round rather than on revenue? What happens to the portfolio if the reflexive loop breaks next year instead of in five? Those are not exciting questions. They are the ones that will matter.

The music will stop. It always does. Dance if you must, but know where the chairs are.

Alex

@alstras

Sep 22

andrew chen

@andrewchen

Sep 20

curious if Jev-like models might accelerate us towards on-device AI native functionality on mobile devices

strong LLMs are a long way from running on phones:
- slow memory bandwidth
- only highly quantized MoE models will fit
- lots of issues with power/heat/etc

Folks are building NPUs for the next gen of mobile but targeting pretty modestly sized LLMs

There’s lots of mobile UX that would benefit from fast/cheap AI decision models - from notifications, typing/texting, to in-app experiences like inboxes/calendars/etc

I always figured the other solution would be a model-on-a-chip that would encode an older-yet-useful model into the actual phone hardware itself, but maybe this will move faster?

Alex

@alstras

Sep 8

Craig Weiss

@craigweiss

Sep 8

funding is pretty cool, but have you heard of revenue?

Alex

@alstras

Sep 6

Paul Graham

@paulg

Sep 5

Unexpected benefit of AI: Tantalizingly vague clickbait no longer works. Instead of clicking on the link to learn the new theory that explains x, I just ask ChatGPT what it is.

Alex

@alstras

Sep 5

Gavin Baker

@GavinSBaker

Sep 3

AI was seasonal in 2024-2025. Growth decelerated during the summer (students/people work less is the theory) and reaccelerated after Labor Day.

This year, AI accelerated in July/August led by OpenAI, Grok and open-source.

And today is the first time I’ve ever seen this:

Alex

@alstras

Sep 5

Paul Graham

@paulg

Sep 4

A VC reports that YC startups' valuations are 79% higher than those of non-YC startups. This doesn't mean, of course, that a given company's valuation will be 79% higher if they do YC. The YC companies could also be better. But either way it's clearly not a bad brand to have.