Co-founder @huddle01com
San Francisco, CA
Joined July 2012
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Ayush Ranjan retweeted
Big personal news today: I have decided to leave @a16z, move to SF, and start a company.
It's time to build :)
It has been almost 10 years since I joined the firm. I met @cdixon, @bhorowitz, and @pmarca in 2017. At the time, I was an engineer at Google Brain working on robotics. I had a deep interest in open source. I knew nothing about investing. Chris meanwhile had already planted the @a16z flag at the frontier that was early crypto with investments in companies like Coinbase. But the crypto team at the firm consisted of only him, and he had the ambition to expand. His pitch to me was simple: "You should leave Google and come help me build the crypto vertical at the firm."
The work we've done together since then to build out our team and support our founders has been the most meaningful work of my life. I am grateful to have spent a decade working with everyone here, supporting our founders, learning from Chris, Ben, and Marc, and living the firm's culture. It is a culture that values integrity, life-long working relationships, and the belief that we humans have the power to build our own future.
Marc and Ben have built a16z into an incredible force for good in the world.
Before I joined the firm, I always thought that my inevitable path was to become a founder. The truth is that I wasn't ready for it then. Somehow, this year I've gotten the overwhelming feeling that this has changed.
As for what I want to build: It is early, but I care most about building infrastructure that enables open software ecosystems. I am starting with two core observations:
1. AI today is largely a single-player technology. Most uses involve one human talking with one agent in isolation from the rest of the world. That will soon change. Most uses of AI will soon be many-to-many: many humans and many agents working together. There will be at least one massive open network on top of which those uses will be built.
2. Software is now free. It can now be written just-in-time, on the spot for a single individual's hyper-targeted use case, and it can even be thrown out after a single use. This means that our entire software stack will have to change. In the limit, it will lead to a whole new kind of AI-mediated operating systems, which in turn will create an ecosystem of AI-native developers who build applications that actively rebuild themselves on the fly.
If you are working on related ideas, and especially if you are in the Bay Area, hit me up. Let's chat!
@bhorowitz , @pmarca, @cdixon, @eddylazzarin, @guywuolletjr, @jasonrosenthal , and our whole team — I want to thank you. Working with you has been the time of a lifetime. I am forever an a16z superfan and your ally.
Onward 🫡
Ayush Ranjan retweeted
Last month, we demonstrated high-rate alchemy: turning mercury into real, stable gold, beating CERN’s record by a factor of 10.
Last week, we enriched isotopes in the world’s most powerful plasma centrifuge, beating the Soviet record that stood for 40 years.
Now, we’re building a fusion reactor in San Francisco to achieve record power density.
Ayush Ranjan retweeted
Elon Musk says blaming difficulty of bringing massive AI compute online on a "lack of electricity" is an oversimplification because power, memory, networking, cooling and construction all need to come together.
Real advantage is shifting toward companies that can actually deliver working compute rather than just announce more data centers.
Ayush Ranjan retweeted
Working with robots has always been harder than it should be.
The intelligence was hard to access. The hardware was hard to afford.
Today, both change.
@makermodsai Maker Arm + Metal Arm, powered by @dreamlabs_ai 's Dream-1. Give your robot a task in plain language, right from your browser.
Try it: playground.makermods.ai
Ayush Ranjan retweeted
It's very very different, this time.
AI Hyperscalers Net Debt/EBITDA at 0.1x vs. Internet Backbone Providers at 3.9x in 2000, a 39x difference.
The dot-com companies were funding fiber rollout with debt and capital market issuance.
Today's hyperscalers are funding AI capex internally from operating cash flow.
Ayush Ranjan retweeted
Yesterday evening I had the pleasure of attending an interesting event hosted by @sfcompute and @jumptrading focused on the compute space. Some brief takeaways:
- There's an increasing understanding that greater liquidity in compute markets requires the construction of unifying benchmark indices, so that bespoke/OTC markets can be priced/quoted as a diff to a shared set of benchmarks, similar to what exists in the energy complex already (think crude grades and power). Part of the discussion is whether this will organically emerge if more traditional players (Citadel, Jump, blue-chip banks) expand their OTC offering for bilateral hedges (using their own prices), or require an independent party (S&P, CME, etc.) to validate and give credence for broader adoption.
- Massive growth in the compute space is largely underpinned by structured financing trades with hedging mandates (similar to what you see in the oil and gas space). If someone with a sizable balance sheet just lent you a lot of money, who's likely to give you more aggressive pricing than their sales and trading arm?
- Funding from life insurers has been a key part of the data center buildout (you could call it duration matching), with an increasing number of insurers considering hedging compute. Some of this exposure sits in mortgage books, while the biggest bucket is via corporate bonds ($ORCL, $MSFT, $META, and $GOOG comprise nearly 80% of Athene's IG software debt).
- Quite a few folks seem offered over on the backend of the curve, largely driven by:
* Concerns that distressed sellers could flood the market if the AI growth story slows down (as there's a lot of GPU-backed debt to unwind)
* Natural hedgers are mostly sellers, as operators need contracted revenue to borrow, so they sell further out on the curve; buyers mostly lock in near-term rates w/ marginal demand coming from a handful of labs whose spending is contingent on their ability to still tap into financing
* Software improvements are reducing GPU-hour needs, all the while new chips are depreciating the value of old hardware per unit of compute: $NVDA is releasing a new gen roughly every year (Blackwell Ultra, Rubin, and Rubin Ultra). That said, it does look like old chips are staying useful longer than most depreciation models assume, since inference and smaller models still allow sufficient monetization of older hardware.
It'll be quite exciting to see how the space continues to mature, especially as new marketplaces begin to emerge for financially and physically settled compute. Huge thanks to @affaan and team for organizing!
Ayush Ranjan retweeted
Neoclouds such as CoreWeave and Nebius are backstopped by companies with trillion dollar market caps and access to the cheapest financing in the world
NVIDIA has a 10% equity stake in CoreWeave and has committed to buy any unused capacity through 2032, up to $6.3B
NScale, Lambda, Nebius and Iren have equity ownership and preferential vendor agreements with NVIDIA
Microsoft has signed a contract and prepaid 20% of the value at Iren. NVIDIA has backed leases at both NScale and Lambda.
Google has backed both Hut8 and TeraWulf through guarantees on the lease. Amazon has guaranteed leases for Cipher.
Yet, people still believe that these companies are at risk of default simply from looking at credit default spread charts
Ayush Ranjan retweeted
modular compute is a bet on risk
traditional DCs concentrate integration and commissioning risk at the end. modular front-loads more of that risk into manufacturing, procurement, and financing.
it's not necessarily cheaper, but it can bring revenue forward. for leveraged operators like @CoreWeave, every month between capital deployment and revenue generation matters.
and as NVIDIA standardizes much of the hardware stack, differentiation shifts toward who can finance, integrate, and deploy capacity fastest.
the next advantage in compute is cheaper risk
Ayush Ranjan retweeted
CoreWeave's debt, explained simply, because I like to speak plainly:
Secured debt = the mortgage. Backed by the house. The GPUs and the contracts they serve are the collateral.
Unsecured debt = the credit card.
Backed by a promise.
Everyone is panicking that $CRWV UNSECURED yield to MATURITY hit 15%
But a credit card rate spiking doesn't mean the house (or in this case the GPUs/data centers) lost value.
The secured lenders or the ones who underwrote the actual GPUs and contracts aren't selling here.
Now zoom out, because this is analogous to the entire AI market in wrapped up in a single company.
Trillions in secured, asset-backed debt are loaned against GPUs, data centers, power contracts, and signed capacity deals with hyperscalers. This money doesn't care about stock prices or investor sentiment.
It gets paid if the contracts pay. (Sounds pretty similar to $next if you ask me…)
Below that in line is unsecured debt, a bet on the companies themselves.
On top of everything is the equity, a bet on the story.
So when you see scary headlines about "AI debt," ask one question: which layer?
Yields spiking on unsecured debt and equities dropping while secured debt sits calm simply means the market is repricing the story.
The assets are fine.
The buildout keeps getting funded because the secured debt holders still believes in the collateral.
The day that changes… well the day secured lenders start questioning GPU values and contract quality, is the day the AI trade actually breaks and we should run for the hills.
Until then, volatility at the top of the stack (unsecured, equities) is just the shock absorbers doing their job.
Ayush Ranjan retweeted
A billionaire literally explained how the entire economy works in 42 minutes better than most $200,000 MBA programs ever cloud.
Ayush Ranjan retweeted
When making money is no longer your goal, that is when you can start being truly effective.
Ayush Ranjan retweeted
The All-In Podcast is LIVE! 🚨
-- CoreWeave Tanks After Debt Selloff: Did the AI Trade Just Crack?
-- AI Deflation and the Future of Software
-- Anthropic IPO: Red Flags, Valuation, How Much to Raise?
-- Psyop Corner with Sacks
-- Bill Gates the Doomer: What’s Behind His AI Warnings?
Ayush Ranjan retweeted
David Sacks pushes back on the AI bubble narrative and says the Corweave crash is just volatility
"I would make the argument that this is just volatility, which you're going to get a lot of whenever you're underwriting to multi-trillion dollar outcomes in the future based on very rapid, exponential rates of growth."
"The market is going to be super sensitive to any data points we have in the present. And so everything's gonna be exaggerated. And that's why you get these big swings."
"That to me is the explanation of volatility. I don't think that something fundamental has changed. Has the demand changed? No. We know that the demand for compute just keeps growing by leaps and bounds. In fact, everyone is saying that they are compute constrained."
"I mean, you got the biggest model companies are saying their compute constrained. Startups are saying it. I mean they're asking their VCs, hey, can you help us get compute. I think you've got some VCs even trying to buy compute as basically a strategy for competitive differentiation so they can help their startups."
"Old GPUs, like even the H100s or the A100s, which are several generations old, they're still renting at premium prices right now. They were supposed to be fully depreciated, and they're not."
Ayush Ranjan retweeted
Pod up! Some good nuggets on lab revs, Nvidia supply unlock, AI capex & millions of Nvidia agents to employees as we enter the singularity & recursive flywheel starts spinning. 🧐🇺🇸🚀 @JensenHuang @BG2Pod
Ayush Ranjan retweeted
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