Yang Tran

Partner @ZeroPrimeVC | prev. @Speedinvest | AI, Data & Infra | SF 🌁

[Yang Tran @YTR4N_]

@nichochar @arnestrickmann

[Yang Tran @YTR4N_]

@DominiqueCAPaul @Hetzner_Online Hetzner is 🐐

[Yang Tran @YTR4N_]

Another portfolio company with crazy revenue velocity. Congrats @modal!

[Modal @modal]

Today we're announcing that Modal has crossed $1B in annualized run rate, as well as raised a $750M Series D at a $15.75B valuation, led by @Accel.

Since our Series C, usage has tripled and we’ve grown more than 15x year-over-year.

We are deeply grateful to the developers and companies building on Modal. There's still so much more to build, and we can't think of a better time to be building software.

[Yang Tran @YTR4N_]

@gokulr it's @modic123

[Yang Tran @YTR4N_]

@iamsebdeb 💯

[Yang Tran @YTR4N_]

Excited for the launch of Qontext! Congrats team 🚀

[Lorenz Hieber @lorenz_hieber]

Today, we’re launching the Qontext platform.

Over the past few months, we’ve been working alongside some of the most AI-native companies on a problem that becomes more obvious the further you go with AI: every agent needs to understand the company it works for.

That understanding lives across your products, customer relationships, processes, and past decisions. It changes every day and rebuilding it for each agent costs time and tokens, while outdated or conflicting information makes results less reliable. As more agents work across the business, keeping that knowledge current and making it available with the right permissions becomes an infrastructure problem.

We built @QontextAI to make sharing company context with agents scale across an entire business.

Qontext connects to the tools you already use, organizes company knowledge into a shared context repository, and maintains it automatically. Agents read the context they need and write new knowledge back, so what one learns can inform another’s work, while you control access and review changes centrally. You can use it with the models, agents, and tools you choose, through API, CLI, or MCP.

Building this takes serious engineering. I’m proud of the team of database, AI, and product engineers we’ve brought together from Snowflake, Databricks, Neon, Stripe, and others. They’re tackling the hard problems behind shared context: resolving conflicting information, evaluating permissions quickly, and handling many agents reading and updating knowledge at the same time.

Thank you to our team for building with such care, and to the customers who have helped shape the product over the past few months. Your trust and feedback have made Qontext what it is today.

If you’re building with AI across your business, we’d love to talk. Link in the comments.

[Alex 🧩 Scaling Video GenAI @alexmashrabov]

Arrived to DevDay with my security.

[Erik Bernhardsson @bernhardsson]

A lot of the long-running persistent sandbox stuff today feels like lift-and-shift. I suspect sandboxes will evolve from being “devboxes in the cloud” to something much more ephemeral. One environment for every _command_. And snapshotting in between so you can pause/resume/clone.

[Yang Tran @YTR4N_]

@modic123 @chrija you should come!

[Christoph Janz 🕊 @chrija]

Looking forward to the German founder mixer tomorrow with @YTR4N_!

https://t.co/AAdKM1FxU1

Registration is officially closed because we're at/over capacity but if you'd like to join, LMK and we'll see what we can do!

[Christoph Janz 🕊 @chrija]

Looking forward to co-hosting this event with @YTR4N_ in SF next week!

https://t.co/eFVkeq9dMG

In true Oktoberfest spirit, we're going to meet at a brewery to bring together founders and people who are thinking about starting a company.

PS: We're calling it "German founder mixer" but we're not going to check passports at the door. All nationalities are welcome. 😉

[TBPN @tbpn]

SF Compute CEO @evanjconrad says if there's an AI bubble, VCs funding AI labs at massive valuations are the ones holding the risk.

"If you're looking for a bubble, it's held currently by the venture capitalists."

"The AI bubble works like this: the cloud itself doesn't deploy the GPU cluster until they have the contract in hand from the customer."

"Then they force the customer to pay them a massive deposit upfront so that they can give it to the OEM, who then gives it off to Nvidia."

"But the AI lab itself doesn't have that capital yet because they need it for the future. So they go off and they raise money at massive valuations."

"And all the VCs look around and say, 'Well, I guess we missed out on OpenAI and Anthropic. Maybe these people will be OpenAI and Anthropic too. We'll go with the big valuation.'"

"But then the venture capitalist owns the risk."

[Nicolas Colin @Nicolas_Colin]

🇩🇪 I will keep making the case that there isn’t anything intrinsically anti-entrepreneurial in German culture, or in European culture for that matter:

• Germany is a surplus country specialized in manufacturing. It wants to export more goods than it imports.

• To do this means repressing wages and consumption to maintain competitiveness. The relatively weak euro, shared with indebted Southern European countries, helps to some extent, but much of the wage repression is the direct result of the 2004 Hartz reforms.

• This means there isn’t a compelling case for investing more in Germany. Because of wage repression, the domestic market is stagnant, with the situation made even worse by weak demographics, which means there is little need for additional investment to serve that market.

• This is compounded by two things. First, wage repression means that most savings end up trapped in corporate balance sheets and are therefore paid to shareholders, most of them US asset managers, rather than reinvested at home.

• Second, the government itself doesn’t invest because of its religious (and constitutional) commitment to balanced budgets. This helps explain the deplorable state of German infrastructure, which in turn makes the country even less investable. Why would you put money into a country where the trains are never on time?

• If you can’t invest domestic savings at home, those savings are invested abroad, notably in the US.

• And if the direction of capital flows is generally outward rather than inward, it means two things. First, whatever domestic capital is invested at home goes primarily into the safest assets, not VC or startups.

• Second, because Germany sends most of its own capital abroad, there isn’t a pull effect whereby foreign investors would be compelled to invest more in Germany. There is simply no relatively attractive yield, whether in VC or in any other asset class, and domestic capital is more than enough to cover what investment there is anyway. As a result, viewed from abroad, Germany is not even on the map as an investment destination, let alone as a place to allocate VC.

• Which is why a German version of Zuckerberg or Musk can’t scale their company at home: there simply isn’t enough capital, whether domestic or foreign, willing to fund the whole journey.

• The corollary is that those who really want to scale emigrate to the US and succeed because the US, being a deficit country, is the opposite of Germany: it is a magnet for capital! They then look back at Germany and say, in a condescending manner, “Oh, but it’s German culture and a lack of ambition.”

Germans want to build companies as much as any other people. The problem is that Germany has built an economy that sends the capital needed to build them elsewhere, betting the whole house on manufacturing and exports rather than startups.

And then China enters the room…

Cc @HMangesius @michaelxpettis @humanandtheloop @patrickc @SineadOS1 @lugaricano @robin_j_brooks @daveg @christianmiele @kofinas

[Bill Ackman @BillAckman]

The presumption that the Fed raising short-term rates reduces inflation is predicated on the belief that higher rates reduce demand and investment.

But what if higher rates don’t reduce demand and investment because the demand for intelligence and energy is unaffected by higher rates because winning the race for super intelligence has a near infinite ROI and the demand for compute will remain incalculable.

Why won’t higher rates at this unique moment in history therefore lead to more inflation as interest costs are embedded in everything?

And the problem is compounded as the more the Fed raises rates, the more inflation we will have and the more the Fed will need to raise rates further and so on.

But what if the old models don’t apply to the current paradigm and the Fed is wrong?

I think the Fed might have just made a mistake. Am I right or am I wrong?

[Yang Tran @YTR4N_]

Revenue velocity at its best 🚀🚀🚀

[Higgsfield AI 🧩 @higgsfield]

Today, 18 months after launch, our annualized revenue crossed $1 billion.

The platform now powers organizations across the Fortune 500. Enterprise adoption has grown 10x since June.

More than 30 million people worldwide now use Higgsfield.

Thank you to the creators and teams building with us.

[Yang Tran @YTR4N_]

Monday morning in SF

[Yang Tran @YTR4N_]

Diogo made the case at AI Council in May: https://t.co/itXfvoJF8l

[Yang Tran @YTR4N_]

Jev has blown a lot of people’s minds

In May, TypeSafe founder @CompleteSkeptic Diogo Almeida joined us at @AICouncilConf and explained why today’s LLMs are remarkable assistants optimized for output humans like but not to make reliable decisions software can act on

[Yang Tran @YTR4N_]

This also explains why it can be so cheap. Jev evaluates many narrow questions in parallel and doesn’t generate long answers token by token.

The bigger bet: It is less general than an LLM by designbut could become the decision layer inside a huge number of software workflows.