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Erik Torenberg sits down with Box CEO Aaron Levie, and a16z’s Martin Casado, and Steven Sinofsky to debate how the AI industry should think about safety, security, and regulation as increasingly capable agents move into the real world.
They argue that much of today’s conversation is happening before we have clearly defined the risks we’re trying to regulate. Drawing on earlier waves of computing, from computer viruses and the early internet to aviation and automobiles, they ask what AI can learn from industries that developed safety standards only after understanding how their technologies actually failed.
The conversation then gets concrete: agents don’t get tired, can operate at enormous scale, and can probe systems in ways human employees never could. That could require rethinking permissions, authentication, operating systems, and the security stack itself. They also discuss why AI innovation may increasingly move beyond the frontier labs and into the software built around the models.
Resources:
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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a16z’s Erik Torenberg sits down with Josh Elman, Olivia Moore, and David Booth to introduce Cosign, a new product built around professional reputation and the people, companies, and products you’re willing to put your name behind.
They unpack a simple idea at the heart of Silicon Valley: some of the most valuable professional signals aren’t credentials, but who believes in you. From the mentor who shaped your career to the colleague you’d work with anywhere or the young builder you think everyone should be watching, Cosign is an attempt to make those signals more visible and durable.
They also discuss why human endorsements may become more valuable as AI makes outreach and information abundant, what existing professional networks get right and miss, and how making reputation more legible could help talented people get discovered earlier, find collaborators, and carry the work they’ve done behind the scenes into whatever they do next.
Resources:
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Follow Olivia Moore on X: https://x.com/omooretweets
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Read more about Cosign: https://www.a16z.news/how-silicon-valley-knows-its-people
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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a16z crypto General Partner Eddy Lazzarin joins Theo Jaffee on MTS to debate the increasingly prominent calls to slow AI development and whether the current safety conversation is conflating very different kinds of risk.
Eddy argues that the debate puts too much emphasis on speculative superintelligence and not enough on the costs of delaying useful technology. Rather than treating every AI failure as evidence of an alignment problem, he makes the case for familiar tools like cybersecurity, accountability, liability, market incentives, and stronger technical controls.
They also discuss whether AI models can develop reputations for trustworthiness, the risks of concentrating oversight among a small group of evaluators, and why Eddy thinks the collision between Silicon Valley’s AI debates and broader politics could fundamentally reshape the conversation over the next year.
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Erik Torenberg sits down with Replit founder and CEO Amjad Masad and Horowitz and Andreessen Academy co-founder and CEO Gagan Biyani to ask what education should look like for a generation growing up with AI.
Amjad argues that one of the most valuable things young people bring to society is their willingness to question deeply held assumptions. They discuss how education could create more room for that instinct through project-based learning, intellectual side quests, and giving students the freedom to follow an idea deeply rather than optimizing around grades and credentials.
They also explore whether young founders are being pushed to professionalize too early, why Amjad thinks starting a company can sometimes be a form of “premature optimization,” and how curiosity led him from learning chess to experimenting with AI that can conduct machine-learning research.
Finally, they discuss trust, judgment, and what it means to develop as a person, not just a builder, including why being contrarian and ambitious still needs to be balanced with the ability to work with other people.
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Ben Horowitz and Erik Torenberg sit down with Gagan Biyani to introduce the Horowitz and Andreessen Academy and discuss a bigger question: what should education look like when AI is rapidly changing the skills people need to build, work, and create?
Ben and Gagan explain why they believe learning should be more focused on doing rather than studying about doing, with students building real projects, developing people skills, and working alongside companies and builders in San Francisco. The goal isn’t to replace college for everyone, but to create a different path for young people who already know they want to build.
They also discuss why AI could make this an unusually powerful time to be young, how project-based learning changes when everyone has access to powerful tools, why failure can be valuable when it produces real learning, and what it takes to develop the judgment and people skills that can't simply be learned from a textbook.
Resources:
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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a16z Board Partner and former Microsoft Windows president Steven Sinofsky joins Theo Jaffee and Sofia Puccini on MTS to argue that the language we use to describe AI failures is making it harder to understand what’s actually going wrong.
Steven takes aim at terms like “alignment,” “goal-seeking,” and “rogue agents,” arguing that they can anthropomorphize problems that software engineers have dealt with for decades. His framing is simpler: when software doesn’t do what it’s supposed to do, it has a bug. And as AI becomes more widely deployed, labs need the same kind of telemetry, debugging, incident reporting, and operational discipline that previous generations of software eventually developed.
Drawing on everything from early computer hacking and Microsoft’s response to major software failures to Y2K and cybersecurity standards, Steven makes the case for treating AI reliability as an engineering problem. They also discuss what AI labs can learn from CVE reporting, why industry has a responsibility to make its systems safer, and how confusing terminology can lead to equally confused regulation.
Resources:
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Ben Horowitz and Erik Torenberg sit down with Nas, Grandmaster Caz, and Steve Stoute for a conversation about the Paid in Full Foundation and its mission to recognize and support the pioneers who built hip-hop.
Ben, Nas, and Steve share how the foundation began, why simply giving artists money wasn’t enough, and how the Hip Hop Grandmaster Awards became a way to pair financial support with the recognition many foundational artists never received. Caz brings the perspective of one of those pioneers, reflecting on his role in hip-hop’s earliest history and what receiving the award has meant for his life and legacy.
They also discuss the enormous cultural and commercial impact of hip-hop beyond music, from language and fashion to some of the world’s biggest brands, why so many of its pioneers captured so little of that value, and what happens when generations of hip-hop finally come together in the same room.
Resources:
Learn more about the Paid in Full Foundation: https://paidinfullfoundation.org
Follow Nas on X: https://x.com/Nas
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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a16z Partner Josh Elman joins Ollie Forsyth on New Economies to discuss the next wave of consumer AI and what separates a product people try once from one that becomes part of their everyday lives.
Josh argues that getting attention has actually become easier, but getting consumers to stick is harder than ever. He explains what he looks for in consumer products, why the best ones start with a narrow wedge and earn the right to do more, and why trust becomes increasingly important as AI agents gain access to more of our personal lives.
They also explore personal AI agents, the future of shopping and entertainment, why we haven’t seen another major social network emerge, and how AI could make technology more social rather than less, including agents that help people spend more time together in the real world.
This conversation originally appeared on the New Economies podcast.
Resources:
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New Economies Substack: https://www.neweconomies.co/
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Databricks co-founder and CEO Ali Ghodsi joins a16z General Partners Martin Casado and Sarah Wang for a conversation about AI risk, recursive self-improvement, cybersecurity, and what’s actually holding back enterprise adoption.
Ali argues that today’s models are already capable enough to automate far more work than most companies are using them for. The bigger problem is context: models haven’t been in every meeting, don’t understand how decisions actually get made, and lack the institutional knowledge that experienced employees accumulate over years. He explains why building an organizational “ontology” could help close that gap and what Databricks has learned from doing it internally.
They also debate the current conversation around pacing frontier AI, what would constitute meaningful recursive self-improvement, and why Ali distinguishes speculative superintelligence risk from the much more immediate challenge of AI-powered cyberattacks. They close with how enterprises are managing exploding AI usage and costs, the shift toward multiple models and harnesses, and why agents are beginning to reshape infrastructure itself.
Resources:
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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a16z General Partner Jennifer Li sits down with fal co-founder Gorkem Yurtseven and Head of Engineering Batuhan Taskaya to discuss what changes when generative video becomes fast enough to run in real time.
They unpack the technical work behind H3 Max, fal’s post-trained version of MiniMax’s open-weight video model, and how combining model post-training with systems and hardware optimization significantly reduced generation time while maintaining quality. That speed has enabled experiments with continuous video, including streams that can remember previous scenes and respond to new directions while they’re running.
They also discuss why the next challenge may be less about speed and more about control, from camera movement and lighting to characters, motion, and lip sync. And they explore what those capabilities could mean for professional creative workflows, where artists and studios need predictable tools rather than simply generating a video from a prompt.
Resources:
Follow Gorkem Yurtseven on X: https://x.com/gorkem
Follow Batuhan Taskaya on X: https://x.com/isidentical
Learn more about fal: https://fal.ai
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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