The Computomatix Times

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

I had a chance to interview @jack on Long Strange Trip and then sit in on his Q&A with a bunch of Sequoia founders yesterday. Here's my take followed by my takeaways.

Almost all of us are running a derivative of the playbook laid out in Andy Grove's "High Output Management" book that has been lightly edited down through the generations. Jack's set of ideas is a stark departure from that playbook. It reminds me of the shift I went through at the start of my career (pre web - yes, I'm that old!) to "digital transformation," but this is a much bigger, harder shift.

Some of my CEO friends have pushed back on these ideas saying something to the effect that Jack isn't a great CEO so we shouldn't listen to him. First, I'm not sure if that is true, but even if it is true, he is an undeniable innovator and first principles thinker applying that thinking here to org design, not just product design. Second, @brian_armstrong, a consensus great CEO is running something that sounds VERY similar to this playbook as well as almost every startup created in the last 18 months. Third, the first quarter Jack printed after putting this in place was a banger. ...To that end, I think we should all call this new playbook, "Dorsey Mode" after the guy who stuck his neck out.

If you want to run Dorsey Mode, a lot of things fall out of it that fall out of it:
1. Strategy - Planning cycles are out the window because the speed increases too much. All those 1 way doors you were procrastinating now look like 2 way doors.
2. Distribution - Given how much easier it is going to get to build products, competition and customer confusion will reign. In this new world, distribution is king. Companies with truly creative distribution strategies (rare!) will gain advantage. Also, long live ye olde enterprise sales.
3. Interviewing - All of the startups I work with have changed their interviewing process. Many have a case with a hard ai problem to solve embedded in it or at least have the prospective employee open their laptop and show them something interesting they built with ai. 4. Profile - There was a split in my group of CEOs at the Q&A -- some were learning hard into pilled jr engineers and some were leaning hard into very senior engineers. It roughly seems like the older companies with more code like Meta and HubSpot, are leaning harder into the very senior engineering types. ...Everyone seems keen to hire "curious" types not afraid to go very deep down rabbit holes.
5. Org shape - Triangle shaped org charts are like democracy, its the least bad system we've got. The biggest problem with triangles is that they get worse with size. The new org chart, in theory, is circular with the world model in the middle and very small teams surrounding it. Very few pure managers in the middle anymore. This seems "early," but directionally right to me.
6. Compensation - The difference between a middling employee and a top one is getting much wider which will necessitate a net new pay scale with a much higher standard deviation.
7. Titles - Jack got rid of them and is trying to focus everyone on the work as opposed to the level. As someone who tried this earlier in my career at HubSpot, I'm a little skeptical of this one, but the meta point of trying to focus people on what they "lead" versus who they "manage" is a good one that I hope sticks.
8 Decisions - Almost all decisions these days are made by carbon based life forms. Dorsey Mode turns an increasing amount of decisions over to the system.
9. IT - This is will totally change as their primary function will be to building the scaffolding for the world model and enable the company to keep feeding it the context and taste it will need to improve. EVERYTHING needs to be "legible" (I hate that I'm using that overused word, but it works) ...Btw, an early sign that a company is in Dorsey Mode is when they record every meeting, including the one on one's, cleverly stripping out some HR bits and centralizing them for use by the model. Btw, Ray Dalio had it right, but was just too early.
10. Slop - As more non-technical people build more things, there will be more slop. I didn't grok Jack's answer to this and I'm not sure the answer myself, but Dorsey Mode companies will need to figure out a system to reign in the badly designed systems.
11. Agency - This another word I cringe at using b/c it is so overused, but hiring folks with high agency that are self motivated will be key. The tricky part is that the beef with the current generation is that they are less like this than their predecessors.
12. CEO - This isn't something that will bubble up. The CEO needs to run hard at it and push it down hard and expect to get pushback from laggards. Jack spends 3 hours every morning building hard things with the new tools. ...AI isn't something that lends itself well to learning by reading or watching a video, so CEOs are running hackathons, show & tell's, building days, office hours, and token leader boards. ...Btw, lots of companies are doing the leader board thing (including mine) -- I think this works until it doesn't!
13. Budgets - Budgets in a lot of software orgs are basically enumerated in headcount. The denomination goes back to dollars.

As Jack (and my cofounder @Dharmesh) likes to say, in some cases, it is a lot riskier not to take a risk and this is one of those cases.

Joined a new AI-native company this week and it’s kind of wild how different it feels already.

The laptop arrived, I logged in, and an agent basically took over from there. It set up my dev env, pulled repos, fixed dependency issues, got permissions approved, pointed me at the backlog, linked the architecture docs, and surfaced the Slack debates I actually needed to read before touching production.

When I needed context on something, I asked the agent and it found the exact thread from months ago explaining why a decision was made, who owned it, the related Linear issues, and the PRs connected to it.

I’ve only been here 3 days but it honestly feels like I’ve worked here for a year because the usual friction and scavenger hunt for context just isn’t there anymore.

We should probably stop calling this “onboarding” and rename it to “mounting” because this feels a lot more like mounting a distributed filesystem called “institutional memory” than slowly getting drip-fed context over 6 months.

My 30+ observations on the greatest opportunities in AI agents right now:

And some ideas that are keeping me up at night.

1. The new buyer on the internet is an AI agent. Imagine billions of new customers showing up with money to spend but they only shop via MCP. That's what's happening. No MCP server means you're invisible to the fastest growing buyer on the internet.

2. Every franchise system in America (30,000+) needs an agent layer and none of them have one. One founder per franchise vertical. That's 30,000 businesses waiting.

3. Everyone said "distribution is the only moat" a year ago. Now I'd add that the only moat is distribution plus memory. The company that has your audience AND your agent's accumulated context is impossible to leave.

4. Consumer mobile is more interesting than it's been since 2012. Apps can finally DO things for you instead of showing you things. The next wave of $100M apps are being built right now.

5. The most interesting startup nobody has built is an agent marketplace where you rent access to someone else's trained agent. A recruiter spent 6 months training a sourcing agent on healthcare hiring. That agent is worth renting to every other healthcare recruiter on earth. The agent itself becomes the product.

6. A sorta strange phenomenon that's happening right now is agents are developing preferences. Give the same agent the same task 100 times and it starts developing patterns in how it approaches it. Nobody is studying this yet. But the agents that develop good patterns are worth more than the ones that don't. That's a new kind of asset.

7. Dead internet theory is about to become dead SaaS theory. Half the apps you use will quietly replace their support team, their onboarding team, and their content team with agents. You won't notice for months. Then you'll realize you haven't talked to a human at that company in a year.

8. The most valuable data in the world right now is sitting in the support tickets of small or mid tier SaaS companies. Every ticket is a customer telling you exactly what to build next. Mine this.

9. The most interesting pricing problem nobody has solved is how do you price a product when your costs change every time OpenAI or Anthropic updates their model pricing? Your margins can swing 40% overnight based on a decision made in San Francisco. The company that builds dynamic pricing infrastructure for agent-based businesses solves a problem every AI company has.

10. The best AI products feel like they're reading your mind. The worst ones feel like filling out a form with extra steps.

11. An interesting arbitrage I've noticed lately is hiring a human VA for $20/hour to supervise an AI agent that does $200/hour work. The human just checks the output.

12. The managed AI agent business is becoming the new agency model. $5k/month per client. You build it, run it, maintain it. The client gets a digital employee they never have to think about. This will be a $50 B+ category.

13. The first "shadow agent" scandals are about to drop. Employees running personal agents on company infrastructure without telling anyone. Using company API keys. Agents accessing internal docs. IT departments have little visibility into this right now. Lots of opportunity to build companies here. Definitely a painkiller not a vitamin type of business.

14. Right now there are probably millions of agents running on autopilot that their creators forgot about. Still burning tokens. Still sending emails. Still scraping websites. Still costing money. The "find and kill your zombie agents" tool is a product that writes itself.

15. Companies are starting to hire based on someone's agent portfolio instead of their resume. "Show me 3 agents you built that are running right now." It's REALLY early but it's starting.

16. Your Slack archive is a product. Every company's internal Slack has thousands of messages explaining how they actually do things. The company that lets you point an agent at your Slack history and auto-generate SOPs and agents from it will be enormous.

17. We're watching the cost of intelligence fall faster than the cost of distribution. Which means distribution is now the expensive thing.

18. The most underrated asset a human can have in 2026: the ability to sit in a room with another human, make eye contact, and have a real conversation. As AI handles more of the transactional stuff, the humans who can do the relational stuff become disproportionately valuable. The soft skills people used to dismiss as fluffy are becoming the hard skills. The hard skills people spent decades acquiring are becoming the soft ones.

19. There are MANY huge companies to be built around the fact that most people's agents are running on their personal laptops which they also use to browse the internet, check email, and download random files. The attack surface is enormous. One compromised Chrome extension and your agent's API keys, customer data, and workflows are exposed.

20. There's a new type of burnout forming that doesn't have a name. It's not from working too hard. It's from context switching between human work and agent work 50 times a day. Reviewing agent output, correcting it, approving it, reviewing again. The mental load of supervising agents is different from the mental load of doing the work yourself. Some founders are telling me they were less tired when they did everything manually because at least the cognitive pattern was consistent.

21. The cheapest form of market research: search "[your industry] spreadsheet template" on Google. Whatever people are tracking manually is your product.

22. Half the YC companies pivoted within 8 weeks of demo day. Not because they failed. Because agents let them test 5 ideas in the time it used to take to test one. The concept of "committing to an idea" is dissolving. Serial pivoting is becoming the default because 1) AI lets you move fast 2) the world is moving fast.

23. The loneliest job in tech right now is being the only person at your company who understands what the agents are doing. You can't explain it to your boss. You can't hand it off to a colleague. If you leave, everything breaks. You've become a single point of failure for an entire automated system. That person needs a title, a team, and a backup plan. Most companies haven't figured this out yet.

24. Your browser history is the most valuable training data you own and you're giving it away for free. Every site you visit, every product you research, every competitor you study, every pricing page you screenshot. That behavioral data, structured and fed to an agent, would make it understand your business better than any onboarding call. The company that lets you turn your browser history into agent context builds something nobody can replicate.

25. Everyone is building AI wrappers. Nobody is building AI unwrappers. The tool that takes an AI-generated document and tells you which parts a human wrote and which parts were generated.

26. Stripe just became the most important company in the agent economy and they barely had to do anything. Every agent that sells something needs Stripe. Every agent that buys something needs Stripe. They're the payment rail for the entire agentic internet by default.

27. The most undervalued API in the world right now is the US Postal Service address verification API. It's practically free. Every local business lead gen agent needs it. Every real estate agent needs it. Every direct mail agent needs it. Boring government infrastructure is quietly becoming the backbone of agent-native businesses.

28. The concept of "business hours" is for humans. Your agent closed a deal in Tokyo at 3am, processed the payment, sent the onboarding email, and updated the CRM before your alarm went off.

29. What happens when agents start recommending other agents? Your research agent finds that a competitor's sales agent is better and suggests you switch. Agent referral networks are forming organically. The first agent affiliate program is probably 6 months away.

30. Cal dotcom closed their source code. That's the canary. When open source companies start closing up, it means agents were cloning their product too easily. Every open source company is quietly asking the same question right now.

31. "AI for pet groomers" sounds like a joke and that's exactly why it will work. 150,000 of them in America. Zero tech. All scheduling by phone or IG DMs. The joke ideas always win.

32. The thing that will seem most obvious in hindsight: we spent 2025-2026 arguing about which model is best while the entire value was in the orchestration layer. The model is the CPU. Nobody buys a computer based on the CPU anymore. They buy it based on what they can do with it. Makes so much sense in hindsight. What else will be obvious in hindsight?

I'll share more notes soon.

I can't sleep with all that's going on. Maybe you too.

What an incredible time to be building.

We just rebuilt ixigo from the ground-up to become AI-native. Not a redesign. Not an update. A completely new way to experience travel. Tara, our AI agent understands you, assists you and gets things done for you integrated deeply into our product journeys.
#ixigoNEXT #TARA #AI #TravelTech

Love this reminder from @tfadell

"Makers often focus on the shiny object—the product they’re building—and forget about the rest of the journey until they’re almost ready to deliver it to the customer. But customers see it all, experience it all. They’re the ones taking the journey, step-by-step."