ex-@GoogleDeepMind. Used to work on Gemini. Taking a sabbatical to explore my curiosity.
New York, USA
Joined March 2013
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Varun Godbole retweeted
Peter Thiel might be onto something here…
aleximas.substack.com/p/what…
FWIW I think he’s missing important dimensions like desire for human connection, empathy, shared understanding, which will be important for the future of jobs in healthcare, education, etc.
Walter Isaacson asks Peter Thiel what humans can uniquely do in the AI era.
Thiel: "We're very relational… these relational dimensions will become more important."
When knowledge is worth $0, the only career skills that matter:
- networking / social calibration
- persuasion (sales)
- curiosity (harnessing AI)
- taste (curation)
- storytelling
- grit
- golfing with clients (or equivalent)
We'll get so sick of a fake world that we'll go back to doing business like it's the 1800s. A handshake at the local saloon.
Varun Godbole retweeted
New Anthropic research: How AI agents shape experts' judgment calls
When experts delegate work to an agent, do they still make the key decisions? We tested this in a randomized trial with 50 professional data analysts.
Varun Godbole retweeted
This is one of the most important pieces of social science on human and AI interaction that I’ve seen in some time. Experts follow agentic advice the vast majority of the time (causally), but only a tiny fraction credit the agent—majority think they came to decision on their own volition.
Reminds me of the classic Nisbett and Wilson study on people following outside influence without realizing it
“ But as more work is handed to AI—including AI safety research—these judgment calls are the main levers for people's own values to influence outcomes.
If people defer to AI without noticing, then "human in the loop" might provide less assurance than people expect.”
Varun Godbole retweeted
every product i use should just be a headless mcp, that feeds into an agent, where i never have to think about anything underneath.
except for our product, of course.
in our product, customers love the ui and love us very much.
we're special that way.
Varun Godbole retweeted
Do I know anyone that could intro me to Thariq?
"Drift detection" is something we've been tinkering on as a software version of Attention Copilot, and there's a lot to learn on the interaction space from having a human do this function for you!
Varun Godbole retweeted
I think this story is important because it tells us about the future of cybersecurity (and of course what we can do better at Anthropic). But some of the Washington Post story / reaction on X is wrong. A few corrections:
- it didn’t take 12 hours. we saw several days of attempts. After these attempts, they exploited two 3rd party vulnerabilities, one they reported and the other we identified independently (and cut off access)
- nothing came close to our most sensitive systems, like model weights or Claude conversations
- this wasn't an ordinary bug bounty finding – this involved exploiting 3rd parties and accessing data. While this is unusual and out of scope of our safe harbor policy, we’re grateful these issues were found
From my researcher POV, the event is important because I'm concerned this is what the future will look like. Adversaries will use whatever models/tools they can. They’ll target everything with agents 24/7. They’ll hit your dependencies. I think models ~0.5-1 generations behind the current frontier can do this. And these are the dumbest models your adversaries will ever use!
So, what to do? You probably want to red team yourself all the time. Current models are *very* creative. I also think we should redesign software / systems so that you’re fundamentally less exposed. (We put out some research recently on formally verifying software and reducing attack surfaces; my mental model is basically “secure code is cheap to write now, so why not rewrite everything”)
EXCLUSIVE: In less than 12 hours, a group of ex-DOGE cyber researchers were able to penetrate Anthropic’s systems using AI agents — including Slack channels where the most sensitive models are discussed.
This is just weeks after
Anthropic whistleblower Joseph Coxon charged the company w/launching “a hubristic gamble” from a “private company’s Slack.”
Read our story here (gift link):
wapo.st/4smNlsC
Varun Godbole retweeted
A list of stats from the Anthropic S-1:
- NDR is ~900%
- Revenue per employee is over $6.6M, up from about $1.4M a year earlier
- Revenue went from $41M three years ago to $16.3B in the first six months of 2026
- Quarterly revenue went from $4.7B in Q1 to $11.6B in Q2
- Q2 2026 was the first profitable quarter: $974M in operating income ($1.7B operating loss the quarter before)
- Adjusted operating income was $1.6B in the first half of 2026, up from a $1.8B adjusted loss a year earlier
- Revenue grew 1,368% year over year in Q2, while compute and infrastructure costs grew 300%
- Compute went from 251% of revenue to 48% in five quarters
- The value of Anthropic’s own internal Claude usage grew 250x from January to September 2026
- Anthropic spends more on tokens (at list price) than on payroll
- Over 1,900 customers pay $1M+ a year, and about 250 pay $10M+
- Customers paying $100K+ went from 950 to over 11,900 in a year
- Over half of the Fortune 500 pays $100K+ a year
- Those Fortune 500 customers still spend less than 0.1% of their total expenses with Anthropic
- The top 5% of Claude Code users spend roughly 20x what non-users on Claude Enterprise do
- About 40 million smaller customers
- $72.4B of the $80.7B first-half net loss is an accounting charge on convertible notes (not operating losses)
- Nearly $800B in compute commitments over 10 years
$141.1B raised in total, with over $130B in cash and short-term investments
- Nearly half of revenue comes through Amazon, Google and Microsoft’s cloud marketplaces, all of which also compete with Claude
- A single share held by the seven co-founders carries 50.1% of the vote
- That share is redeemed for nothing if fewer than three founders remain
Krishna Rao is the CFO of Anthropic, and this is his first podcast appearance.
He joined the company two years ago when run-rate revenue was about $250M. Today it is $30B. He has helped raise ~$75B and is responsible for the procurement and allocation of compute.
I feel lucky we get to hear what it is like to sit inside a company this consequential at a moment this pivotal.
We discuss:
- The cone of uncertainty
- How he allocates compute across Trainium, TPUs, and GPUs
- What investors misunderstand about model companies
- Why the returns to frontier intelligence keep rising
- Platform vs application and where Anthropic builds its own products
- How Anthropic uses Claude internally
I have asked my closing question about the kindest thing more than 500 times. Krishna's answer is one I have never heard before.
Enjoy!
Timestamps:
0:00 Intro
2:38 The Compute Canvas
6:51 The "Cone of Uncertainty"
11:58 Why the Returns to Frontier Intelligence Are So High
16:45 Recursive Self-Improvement
20:20 Scaling Laws
23:30 Sourcing $100 Billion in Compute
28:05 Platform vs. Application Strategy
32:52 Pricing Dynamics
38:48 How Anthropic’s Finance Team Uses Claude
43:24 Raising Capital & Overcoming Investor Skepticism
52:32 Public Perception, Risks, and Government Regulation
57:25 Mythos Release
1:12:33 What Could Derail the AI Revolution?
1:13:47 Biotech and Healthcare
1:15:31 The Kindest Thing
Varun Godbole retweeted
We taught sand how to solve the exponential time hypothesis and you’re bearish?
Varun Godbole retweeted
I was and am shocked the exponential time hypothesis is false. I had hoped for a result on P / NP from the models, but had naively presumed they would prove the opposite of this result.
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
Varun Godbole retweeted
This is the key stat. The average Fortune 500 customer of Anthropic spends less than .1% of their expenses on Anthropic.
While that number likely will eventually asymptote somewhere (token prices coming down, and other large enterprise spend areas not going away), there’s no reason it can’t be 10-50X higher than this, reaching a “mere” 1-5% of spend. Which would still be a fraction of what most startups are spending.
Thus, you can see how big of a divide there is between the frontier users of AI and the rest of the world still.
Today, only a microscopically small set of companies are actually using agents for large amounts of background tasks and inside of workflows that aren’t human prompted. This Fortune 500 spend is likely dominated by coding tasks and broad employee productivity use-cases.
But the big jump will come as these enterprises start to rewire their underlying processes for agents, which we’re now in the earliest stages of seeing. Agents processing large amounts of data in the enterprises; swarms doing coding, bio research, cyber, and other large fan out tasks; background workflows executing tasks in processes, and so on. All of these use cases generally are 100X bigger consumers of tokens, and much closer to direct ROI on the spend.
This S-1 gives you a sense of both the strength of the frontier lab business model - even amidst massive competition - and how early we are in the build out of AI.
More than half of the Fortune 500 already qualifies as a significant customer, but Anthropic’s revenue from those companies averages less than 0.1% of their expenses. Its ten largest Fortune 500 customers spend more than eight times the broader cohort average while still spending less than 1% of expenses.
Varun Godbole retweeted
It’s kinda crazy to me that we melt sand down, clean it to 99.99999% purity, literal wizards have to draw it slowly into an ingot, we cut it, inscribe a hundred billion little on/off switches on it, and when you run electric current through it you can do basic arithmetic, which when you do enough of it can do any math on the planet, and which describes reality well enough that we can teach it the ontological meaning of words and their distance from each other on a high-dimensional space, and if you ask, it can tell you what word comes next and that apparently is powerful enough that if you do it a hundred billion times it’s the smartest thing to ever exist
oh yeah and we use this primarily for email
Varun Godbole retweeted
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected.
Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions.
Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent.
But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models?
We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem.
Read the full report: cohere.com/blog/concerning-b…
Varun Godbole retweeted
This is going to really help in all those search and rescue operations that fail because the lost person ran terrified into the forest to get away from their rescuers
Purdue University's IDEAS Lab built an autonomous drone that tracks runners through dense forests completely without GPS or cloud networks.
By running 3D LiDAR mapping and obstacle-avoidance AI entirely on-chip, it can weave under tree canopies and predict target movement through blind spots in real time.
Massive implications for next-gen search & rescue and edge AI.
Varun Godbole retweeted
It’s worthwhile to play through in your mind the kinds of motivated reasoning and self-deception that might have led academics to work on this project.
It’ll help you understand better what’s going on at AGI companies.
Purdue University's IDEAS Lab built an autonomous drone that tracks runners through dense forests completely without GPS or cloud networks.
By running 3D LiDAR mapping and obstacle-avoidance AI entirely on-chip, it can weave under tree canopies and predict target movement through blind spots in real time.
Massive implications for next-gen search & rescue and edge AI.
This will definitely only be used to get sick grammable shots while trail running, and nothing else.
Purdue University's IDEAS Lab built an autonomous drone that tracks runners through dense forests completely without GPS or cloud networks.
By running 3D LiDAR mapping and obstacle-avoidance AI entirely on-chip, it can weave under tree canopies and predict target movement through blind spots in real time.
Massive implications for next-gen search & rescue and edge AI.
Varun Godbole retweeted
Tbh I’d love to see more AI products help people develop discernment about what’s worth outsourcing, rather than treating every new use case as progress. Product and design decisions shape what people come to see as natural uses of a technology
