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Benchmark Breakfast #1 | Jack and Ev

October 29, 2026 · 56 min

Show notes

Benchmark Breakfast is a recurring conversation between Benchmark partners Jack Altman and Ev Randle. It’s a window into the firm’s Monday no-agenda partner meetings, where five partners sit around and talk about whatever came up that week.

In this inaugural episode, Jack and Ev dig into the Anthropic S-1: what the revenue-to-compute chart actually shows, why growth volatility and consumption-based revenue complicate the public market story, and whether code gen is the most impactful PMF moment in the history of technology. They steelman open source vs. closed source, run the numbers on what the inference cloud market actually looks like, and get into AI’s emerging cybersecurity threat — including “abliterated models,” open-weight models with safeguards removed that adversaries are already using. They close on why bio and robotics may ultimately matter more than all the software gains combined, and what Manhattan Project-scale investment in the physical world could actually unlock.


TIMESTAMPS:

(0:00) Intro

(0:45) Introducing Benchmark Breakfast

(2:09) Anthropic S-1 drops

(3:59) The revenue vs. compute chart

(6:19) Growth volatility and consumption-based revenue

(7:11) The race for the best model

(10:21) Code gen saturation and software factories

(13:39) The AI-bottleneck trade

(17:39) Code gen as the most impactful PMF in history

(21:27) Durability is hard to call

(23:36) Investing in the trend vs. calling the next one

(26:09) Circular revenue vs. outside customers

(28:15) Open source vs. closed source steelman

(34:25) Own your intelligence

(36:29) Open source as a % of frontier spend

(40:52) AI and cybersecurity

(44:35) Abliterated models

(48:08) Bio, robotics, and physical abundance

(51:52) Why physical feedback loops are slower

(54:12) Ev’s dad and the promise of bio

(55:13) Halloween plans and the iPhone Duo


LINKS:

https://x.com/jaltma

https://x.com/everettrandle

All episodes of Uncapped | Benchmark Breakfast

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