Daily Brief

Ben Guo built the page listing every speaker in this session while he sat waiting to go on, then put a QR code to it on his first slide. He builds that way because his computer is a server in the cloud that he talks to in plain language. Guo cofounded Zo Computer after starting on the early Venmo team and joining Stripe as its 80th engineer, and his argument is that people used to feel at home on their machines and no longer do, because everything they touch is rented. He calls the arrangement technofeudalism. You pay a subscription to a software company, which pays rent to a cloud provider, w

Every employee at Two Sigma has a remote cloud agent, and it runs as them. Not a service account but their own identity, at a 25 year old quant fund in one of the most regulated industries there is. Shu Fang grew a mustache so the audience could tell him apart from his. His framing comes from the horror film Us, where the doubles are called the tethered and turn dangerous once they slip loose. The conventional design, where Shu has a Shu agent, collapsed fast. Permissions drift out of sync, licensing doubles, some systems refuse to let two identities touch the same data, and you inherit a boun

Jean-Denis Greze and his wife share an agent that can read both of their inboxes, including mail from before they were married, and neither of them minds. Greze is CTO of Town and spent seven years as CTO at Plaid. He opens by rejecting his own topic. Agent to agent, he argues, is not a useful concept. Every LLM system is really a search problem: what matters is whether the right information sits in the context window at the moment of the tool call. The ideal is a single agent with access to all the world's information. What blocks it is not context length but privacy, and he reaches for the C

Tanmai Gopal plotted the daily edits to his own company brain expecting the usual shape, a burst of enthusiasm followed by neglect. The line kept climbing instead, and it surprised him. His reading is that a system people trust gets taught more, not less: teach it to query the data, then to interpret the result, then to act on it, and each skill adds its own steady rate of correction on top. A rising edit count is what health looks like. Gopal cofounded PromptQL and before that built the Hasura GraphQL engine, and his team spent a year deploying an early company brain across 15 to 20 organizat

Karan Vaidya pointed his own OpenClaw at hiring outreach and it mass emailed candidates exactly as instructed. Some of the people in the room had received one. The thread that followed put his name on Twitter, and every check in the software engineering playbook would have passed. The addresses were real, the emails were valid, they reached actual people. Nothing tested the only question that mattered, which was whether the outreach should have gone at all. Vaidya, cofounder and CTO of Composio, turns his own disaster into a larger claim: coding agents did not race ahead because models are bet

Flock, Axon, and most of public safety tech grew by owning the input. Nick Noone on why Peregrine inverted the entire model, and why the problem was never how much data an agency had. #ai #flock #publicsafety

Full episode: https://youtu.be/X50zezLFWWI Me on twitter: https://x.com/dwarkesh_sp

An intern designed the sparse-attention architecture behind MiniMax M3. That detail comes after Olive Song explains the larger problem the team was trying to solve: short context windows aren’t enough when agents must work across long conversations, tool responses and complex environments. M3 combines a functional one-million-token context window with coding, agentic and multimodal capabilities, allowing it to understand text, images and video within the same model. Thomas Wolf and Olive Song unpack how MiniMax made that context window efficient, why the company trained M3 as multimodal from

Nick Noone was flying in and out of Baghdad. Ben Rudolph was working refugee crises in Africa. In 2016 they decided to come together to work backwards to a single answer: safety sits at the bottom of the pyramid. #ai #publicsafety

Full episode: https://youtu.be/X50zezLFWWI Me on twitter: https://x.com/dwarkesh_sp

What would a GPT-style foundation model for the **physical world** look like? Just days after emerging from stealth, Accelerated Understanding co-founders Anima Anandkumar and Benedikt Jenik, join us to explain their bet: that the universality and scale we’ve seen in language models can also emerge across physics. They’re building a single model designed to learn across very different physical systems—fluid dynamics, semiconductors, energy, and more—and they say their experiments are already showing something important: models trained across multiple areas of physics can outperform equally s