The a16z Show

a16z General Partners Martin Casado and Erik Torenberg are joined by Board Partner Steven Sinofsky to explore what recent breakthroughs in AI and mathematics tell us about where the technology is headed, and whether some of the basic assumptions that have governed computing for decades are starting to break. Martin and Steven debate whether AI's progress in mathematics represents a genuine leap in reasoning or simply a new tool for solving problems at a higher level of abstraction. From the four-color theorem and early computers to graphing calculators and today's models, they trace how new technologies have repeatedly changed which problems humans need to solve themselves, and ask what makes this moment different. The conversation then turns to one of the biggest shifts in AI: problems that were once constrained by engineering talent can increasingly be attacked with capital and compute. They discuss what that means for startups versus incumbents, venture capital, the coming wave of AI applications, and why pouring billions into increasingly capable models may force us to rethink what these systems can ultimately accomplish.

Daisy Wolf and Eva Steinman are joined by Engy Ziedan, co-founder and Chief Scientific Officer of Protege, to discuss why medical AI has a measurement problem, and why scoring well on a benchmark doesn't necessarily mean a model is ready for the hospital. Engy explains why healthcare AI needs independent evaluations that go beyond static exams and measure how models actually perform in real-world clinical workflows. They explore the risks of subtle bias and misalignment, why the same model can rank differently depending on how it's prompted or tested, and what happens as AI becomes more personalized and changes faster than traditional healthcare quality systems can keep up. The conversation also gets into Protege's role as an independent evaluator, how contaminated training data can undermine benchmarks, and why the future of medical AI may require continuous monitoring rather than occasional testing.

Martin Casado joins MTS hosts Theo Jaffee and Sophia Dew to unpack where value is actually accruing in AI, why this technology cycle looks fundamentally different from previous waves, and whether the frontier labs will ultimately capture most of the market. Martin explains why AI has turned venture into a scale-up capital game, where small teams can productively deploy extraordinary amounts of money, and why the relationship between capital, innovation, and growth has never been tighter. He lays out the case both for and against the frontier labs dominating AI, the role of open-source and specialist models, and why applications are increasingly capturing more value. The conversation also explores model routing, AI economics, founder-market fit, and why Martin believes this may be the biggest unlock of wealth he's seen since the 1990s.

a16z's Joel De La Garza is joined by Aaron Zollman, Deputy CISO at Microsoft Gaming, to discuss how security teams can embrace AI agents without losing control. Aaron shares Microsoft's experience with OpenClaw, from the initial instinct to ban it to figuring out how to make it safe to use. They unpack what agents mean for identity, permissions, containerization, and monitoring, as well as how AI is shifting the CISO's role from saying "no" to safely enabling new technology. They also explore whether AI could help defenders patch vulnerabilities as quickly as they're discovered, and why new AI threats don't make the old security problems go away.

Elena Burger is joined by a16z’s Angela Strange and Gabriel Vasquez to discuss the rise of the "borderless founder": entrepreneurs who bring the networks and insights of their home markets together with the talent, capital, and speed of Silicon Valley to build global companies. Angela and Gabriel trace how a16z's international investing efforts grew from early work in Latin America into a broader global network, and why AI has accelerated the flow of founders and talent between Silicon Valley and startup ecosystems around the world. They explore the advantages borderless founders can bring, from differentiated talent networks and early customers to strong local brands and communities that help open doors across markets. They also discuss how founder diasporas can function like powerful alumni networks, why spending time in Silicon Valley can help founders recalibrate around speed and ambition, and how the next generation of global companies may increasingly be built across multiple countries from day one.

a16z General Partner David George is joined by Grant LaFontaine, co-founder of Whatnot, to unpack how a marketplace that started with collectibles evolved into one of the world's leading live shopping platforms. Grant traces the company's origins from selling Pokémon cards online as a kid to discovering live commerce by watching Whatnot's earliest customers hack together sales on social media. They discuss why Whatnot thinks less like a traditional e-commerce marketplace and more like a digital shopping mall, where discovery, entertainment, community, and commerce all happen at once. Today, users spend roughly 95 minutes a day on the platform, and most aren't even buying something on a given day. They also explore how Whatnot is enabling small businesses to reach global audiences, expanding from collectibles into categories like fashion, food, and golf, and using AI to make sellers more efficient without replacing the human connection at the center of the experience.

a16z's Joel De La Garza is joined by Nick Warner of Neo and Max Pollard of Cotool to discuss what happens when cybersecurity tools built to defend against humans and malware suddenly have to contend with AI agents. As frontier models become more capable of finding and exploiting vulnerabilities, many of the assumptions underlying traditional security are beginning to break. They explore why guardrails designed to stop AI-powered attackers can also prevent security teams from doing their jobs, why defenders increasingly need access to multiple models, and how agentic software creates an entirely new endpoint security problem. They also discuss why static signatures and even newer techniques like honeypots are struggling in a world where software can reason and act autonomously. Recorded around Black Hat, the conversation looks at how security teams are adapting in real time and why the same AI capabilities creating new attack surfaces could ultimately give defenders their biggest advantage yet.

a16z General Partner David George is joined by Will Gaybrick, President of Product & Business at Stripe, to discuss how AI is changing the way Stripe builds products, organizes teams, and thinks about the future of internet commerce. Stripe has evolved from a payments company into a multi-product financial infrastructure platform, while a new generation of AI companies is growing and monetizing faster than previous software cohorts. Will explains why Stripe sees AI productivity as an opportunity to build more rather than simply cut costs, including how its internal coding agents now generate thousands of pull requests each week. They discuss creating founder-like agency inside large companies, building smaller and flatter teams, and why Stripe believes dramatically more software will be created as the cost of building continues to fall. They also look ahead to agentic commerce, why checkout pages could disappear, the potential return of micropayments, stablecoins as infrastructure for a global economy, and a future where AI agents increasingly buy software and services from other machines.

Ben Horowitz, Travis Kalanick, and Erik Torenberg take the stage at Atoms' launch event for a candid fireside conversation about entrepreneurship, company building, and why Kalanick believes the next industrial revolution will be powered by AI. They revisit pivotal moments from Uber's history, including the decision not to acquire Lyft, lessons from scaling one of the world's fastest-growing companies, and how Kalanick has evolved as a founder. The conversation also explores Atoms' vision for industrial AI, why software is moving into the physical world, what it takes to build enduring company cultures, and why Kalanick believes the biggest opportunities of the next decade lie in transforming industries like food production, mining, and manufacturing.

Elena Burger is joined by a16z's Andy McCall and Joe Schmidt to break down two very different ways AI startups can go to market: the lighthouse and the landgrab. Should founders win a handful of marquee customers whose credibility unlocks an entire industry, or move quickly across a broad market where the ROI already speaks for itself? Drawing on Joe's Lighthouse or Landgrab framework and Andy's experience building sales organizations at Samsara and Meraki, they explore how founders can determine which strategy fits their market, when social proof matters more than math, and why the current rush to adopt AI has created a rare window for startups to sell big software again. They also get tactical on POCs, pricing and ACV, hiring early sales teams, moving from mid-market to enterprise, and why founders shouldn't spend too much time perfecting their GTM strategy before talking to customers. As Andy puts it: spend 1% of your time on strategy and 99% executing.

Anish Acharya is joined by Garry Tan, President and CEO of Y Combinator, for a conversation about how AI is rewriting the startup playbook, why founders should be more ambitious than ever, and what two decades of Silicon Valley booms, busts, and missed opportunities have taught Garry about building what's next. Garry reflects on turning down an early opportunity to join Palantir, why chasing what's "hot" is often the wrong strategy, and why the best ideas tend to begin with people pursuing strange, earnest obsessions outside the mainstream. They also explore how AI changes the economics of company building, why traditional SaaS may be losing its advantage, and how tiny teams equipped with hundreds of agents can build businesses at a scale that once required entire organizations. The conversation goes deeper into agentic companies, taste and agency, why "a markdown file is an employee," and how AI could remove layers of bureaucracy that have historically limited organizations. Garry and Anish also discuss the future of consumer AI, the coming "harness wars," why AI adoption may take longer than Silicon Valley expects, and what the next generation of founders can build with intelligence that was unimaginable just a few years ago.

a16z's Joel De La Garza is joined by Emilio Escobar, Chief Information Security Officer at Datadog, to discuss what it takes to secure a company where nearly every employee is using AI and more than 4,000 engineers are working with coding agents. Rather than trying to block new tools, Emilio explains why Datadog chose to embrace AI early and build the security infrastructure needed to use it safely. They unpack how AI changes traditional assumptions around data permissions, credentials, developer access, and software supply chains. Emilio shares how Datadog uses role-based MCP servers and ephemeral credentials, as well as an AI "judge" built by his security team to evaluate the intent behind code and agent skills before they enter the environment. They also discuss why security teams can't afford to wait for commercial solutions to every new AI threat, how the relationship between developers and security teams needs to change, and why Emilio is less concerned about an AI "escaping" than he is about the sheer volume of vulnerabilities AI could uncover.

Angela Strange and Gabriel Vasquez are joined by Alejandro Maza Ayala, Chief Product & AI Officer at Kavak, to unpack how the Latin American used-car marketplace rebuilt itself around AI agents, with 96% of customer interactions and 95% of transactions now handled by agents. Alejandro explains why Kavak decided that simply giving employees AI tools wasn't enough, and instead redesigned the company's systems, teams, and customer experience around agents. They discuss why Kavak spends as much engineering effort on evals as it does building agents, how its AI sellers outperform its human teams, and an experiment where an AI "CEO" increased profits in one city by 50% in its first month. The conversation also explores what happens to organizational structure when agents do most of the work, why Kavak trains everyone from executives to mechanics to build with AI, and Alejandro's argument that companies looking for incremental AI adoption may be missing the larger opportunity: redesigning the organization itself.

Joel De La Garza is joined by Dylan Ayrey, co-founder and CEO of Truffle Security, and Feross Aboukhadijeh, founder and CEO of Socket, to discuss one of the biggest shifts happening in cybersecurity: AI models are no longer just finding vulnerabilities—they're exploiting them. As frontier models become increasingly capable of hacking, software security, supply chain attacks, and cyber defense are entering a fundamentally new era. The conversation explores AI-powered hacking, software supply chain attacks, leaked credentials, zero-day vulnerabilities, package manager security, and why the path of least resistance for increasingly autonomous AI systems may also be the most dangerous. They also discuss what enterprises, developers, and the open-source ecosystem need to do to adapt as the gap between vulnerability discovery and exploitation continues to shrink.

Elena Burger and Matt Bornstein are joined by Simon Mo, co-founder and CEO of Inferact, the open-source inference engine powering many of today's most advanced AI applications. Together, they explore how open-source AI evolved from a research project into critical infrastructure, why inference has become one of the most important layers of the AI stack, and what it takes to bring frontier intelligence to developers around the world. The conversation covers vLLM's origins, the rise of open-weight models, why companies increasingly want control over their AI infrastructure, and how open-source inference enables the next generation of AI applications. They also discuss model licensing, the economics of open-weight AI, Kimi K3, distillation, AI infrastructure, and why Simon believes the gap between open and closed models is rapidly disappearing.