Josh Davis

“When you go from consumer to B2B, the number one mega-challenge that you must master is LTV:CAC.” - @travisk "Yes, you can make that argument on consumer, but when you have a sales funnel that starts with 'I'm going to talk to customers, and I have to make LTV:CAC work' — versus 'My LTV:CAC is the App Store' — it's a whole different ballgame." “LTV:CAC with a sales machine, especially if you go [after] small businesses, is life on hard mode. Anybody who’s crushed it on SMB, those guys are special individuals who've made that happen. Because life in the SMB B2B world is no joke." From his appearance on the show in March.

@sama @TheStalwart Unsolicited advice: start articulating how AI will improve the human experience. Let other OAI leaders talk about models and specifics while you uplevel your talk track. You’re competing against Dario talking about wiping out entry level jobs. The bar is currently underground

This podcast will make you smarter than Leopold Aschenbrenner at an AI investing conference. - Anthropic Raises $45BN but Falls Short on Compute - Are OpenAI Back in the Game with GPT5.5 & Codex? - Why Google is a Bigger Buy Than Ever Before - China Blocks Manus $2BN Deal to Meta - Thoma Bravo Hand Back Medallia Keys to Creditor I sat down with @rodriscoll and @jasonlk and my notes below: 1. Why does Dario at Anthropic have such a hard job predicting the compute demands? The capital intensity of building an AI leader is unprecedented; every $1 of run-rate revenue requires approximately $4 to $5 of CapEx to support it. A CEO must forecast demand two years in advance, which is incredibly risky. Underestimating demand leaves you with insufficient compute to serve users, while overestimating it results in billions of dollars in "stranded capacity". 2. What the public markets are getting wrong about the SaaS-pocalypse The market currently believes specific coding vibes or models are the primary threat, but the true danger is what AI agents decide to pick. Agents will ultimately choose the vendors and LLMs for most workflows, rendering tools like project management software useless because agents have no need for them. Companies like OpenAI are racing to win the "agent wars" to ensure their APIs are the default choice for these autonomous systems. 3. Why Google is a mega-buy on the back of the Anthropic investment Google is positioned as a primary winner because it benefits whether users choose Gemini or Anthropic. They possess "infinite capacity" compared to other players, allowing them to route compute surplus between their own needs and their various customers. This massive cash flow and infrastructure flexibility make them a "win-win-win" in the current AI arms race. 4. Multi-year contracts don't matter. Deferred churn is still churn. Multi-year contracts are often a place where "mediocre" management hides to mask underlying business problems. While a customer might be locked into an eight-year cycle through standard upfront terms and renewals, they are essentially just taking that time to find a better enterprise solution. If a customer eventually leaves, the churn was merely deferred, and the terminal value of the company remains impacted. 5. What happens to the distributions from Manus? Do the investors have to give the money back? When a regulatory body like China attempts to "unwind" an acquisition like Meta's purchase of Manus, there is a near-zero chance that venture investors will return the capital already distributed. The real pressure point is on the acquiring corporation and the technology itself, rather than the VC funds. Such rulings are primarily designed to prevent similar deals from occurring in the future. 6. The two great wars that no one is talking about Two subtle but massive "battles" are currently unfolding: the US vs. China AI war and the resulting social dislocation. We are seeing a rise in "social unrest" expressed through billionaire taxes and penthouses taxes as layoffs from AI automation begin to impact the workforce. These themes of geopolitical competition and internal inequality will be the defining political stories of the decade. (links below)

hey @sama can we normalize models just saying "i dont know" ? eliminates 99% of hallucinations

Jack Dorsey, co-founder of Twitter (now X) and Block, on why treating AI as a "copilot" is a losing strategy: @jack argues that most companies are approaching AI in a way that will make it nearly impossible for them to survive. "I think most of the industry is thinking about AI as like a co-pilot, as something that is augmented onto, rather than like how do you just rebuild our whole company with this as the core." His concern is that bolting AI onto existing structures produces companies that look indistinguishable from each other, and from the AI labs themselves. "If it doesn't make sense for your business to do that and you end up being or looking very similar or rhyming too closely with the frontier labs, then I think it's going to be very, very challenging to differentiate and survive." This thinking has been driving his decisions since early 2024, when these tools "really came to bear." That's when his team began building Goose, an agent coding harness, as part of a broader effort to rebuild around AI rather than layer it on top. The core insight? Speeding up old workflows with AI is a short-term gain every competitor will match. Real differentiation comes from rebuilding the company itself around intelligence.