Apple’s Big Reveals, OpenAI’s Multi-Step Models, and Firefly Does Video

If you could do only three things for your health, what should they be? Andrew Huberman’s answer is surprisingly straightforward: get bright light shortly after waking, resistance train, and make the sleep you can get as high-quality as possible. Andrew joins a16z General Partner Daisy Wolf to walk through the protocols he actually follows, from exercise and nutrition to meditation, supplements, and locking his social media phone in a box. He also explains why optimizing every health protocol can be counterproductive if it gets in the way of the rest of your life. And for founders, Andrew makes a different case: identify the hours when your brain does its best work and protect them. They discuss cognitive performance, meditation, sustainable workloads, and emerging neurotechnology that could help us control transitions between sleep, focus, and recovery.

What does it take to build robots that can actually work in factories and warehouses? Tutor Intelligence CEO Josh Gruenstein argues robotics is a systems problem spanning AI, hardware, manufacturing, and the work itself. Josh joins a16z General Partners Martin Casado and Raghu Raghuram to explain Tutor’s approach: deploy robots into real businesses, use human “tutors” when needed, and turn that work into training data that makes the robots more capable. They discuss Tutor’s 100-robot data factory, robots starting at roughly $16 an hour, advances in spatial reasoning, and what flexible robotic labor could mean for American manufacturing and the physical economy.

Can relentless optimization create as much value as breakthrough invention? Bending Spoons CEO Luca Ferrari argues that radical innovation can produce extraordinary outcomes, but systematic improvement can be more dependable, especially when paired with a model designed to compound over decades. Speaking with a16z General Partner Anish Acharya at Wave by Vento, Luca explains how Bending Spoons acquires technology companies, integrates them onto a shared platform, improves their economics, and reinvests the resulting cash into new acquisitions. They discuss the tradeoffs between growth and profitability, how to use debt without putting the company at risk, and why long-term thinking can create an advantage. They also debate whether AI really threatens SaaS, why moats like brand, proprietary data, network effects, and switching costs still matter, and how Bending Spoons is already using AI across coding, customer support, and data analysis.

What if finding your next job, co-founder, or collaborator depended less on a resume and more on who is willing to vouch for you? Cosign is building a professional network around those signals, with the longer-term goal of giving AI agents access to the relationship and reputation data that traditional networks keep locked away. a16z New Media’s David Booth and Dhruv Gupta join MTS to introduce the Cosign Awards, which recognize standout operators, companies, and products based on nominations from the people who know their work. They also unpack the bigger idea behind Cosign: mapping the people and relationships that rarely show up in public data, then making that graph accessible to both humans and agents. Looking ahead, they imagine professional networking where your personal agent can talk directly to a company’s agent, determine whether there’s a potential fit, and only bring the opportunity to you when there’s a genuine “coincidence of intent.”

What happens when AI makes legal work cheap enough to take cases lawyers couldn't afford to touch before? Eve CEO Jay Madheswaran argues that AI won't just cut costs for law firms. It could expand access to legal representation by making an entirely new class of cases economically viable. Jay joins a16z General Partner Alex Rampell to explain how Eve is automating plaintiff law from the first client call through settlement, and why some firms are already using it to increase the number of clients each attorney can manage from roughly 100 to 500. They also discuss how AI could shift lawyers toward higher-value advocacy, why agents may eventually negotiate with other agents, and what happens to the legal system when bringing a case becomes dramatically cheaper.