The a16z Show

AI is moving finance from reconciling what happened last month to helping decide what the business should do next. Figma CFO Praveer Melwani argues that the best finance teams are becoming builders themselves, automating repetitive work so they can spend more time understanding customers, running experiments, and shaping strategy. Praveer joins a16z’s Seema Amble and Ivan Makarov to share what that shift looks like inside Figma, from collections and expense analysis to M&A diligence, where the corp dev team now uses AI to prototype products and simulate how Figma leaders might challenge an investment memo. They discuss why AI “slop” is a real risk, how Figma decides what to build versus buy, and why successful internal experiments eventually need a centralized systems layer to turn one-off agents into reliable infrastructure. They also get into what this means for hiring the next generation of finance leaders. Praveer’s bar isn’t simply whether someone can use AI. It’s whether they can understand the business, interrogate the output, communicate clearly, and use automation without outsourcing their thinking.

Will we have one AI assistant that does everything, or an entire network of agents that know different parts of our lives? David Pawlan, creator of Assistant Benchmark, returns with Anish Acharya and Josh Elman to take stock of how quickly the agent landscape has changed. David has now tested more than 140 AI assistants, and they unpack what separates them, from memory and judgment to trust, shopping, and social experiences. They also explore what happens when agents start talking to each other, how they could create new kinds of social networks and serendipity, and why the most compelling agents may ultimately do more than save time. They could become a kind of secret superpower.

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.