Marc Andreessen on Betting on America

Marc Andreessen on Betting on America

Marc Andreessen joins Navin Girishankar, president of the economic security and technology department at the Center for Strategic and International Studies (CSIS), for a wide-ranging conversation on artificial intelligence, productivity growth, national competitiveness, and America’s technological future. In their conversation, Marc argues that while AI has already begun reshaping the economy, the largest impacts are still ahead. He explores how AI could dramatically expand access to intelligence, improve productivity, and transform industries ranging from healthcare and education to law and software development. At the same time, he warns that many of the biggest barriers to progress are not technological but institutional, driven by policy choices and infrastructure constraints. The discussion also covers the global AI race, U.S.-China competition, export controls, energy, reindustrialization, and the role of government in fostering innovation. Along the way, Marc shares his views on technological progress and why he believes America still has an opportunity to lead the next wave of economic growth. Topics covered: 00:00: Introduction: acceleration, transition, and policy 00:02: The AI boom: optimism versus utopianism 00:04: AI as an intelligence equalizer 00:08: Education and institutional reform 00:13: Productivity by sector: blue sectors and red sectors 00:18: AI infrastructure constraints 00:22: Tariffs and behind-the-border constraints 00:26: Model export controls and the Mythos case 00:33: The technological imperative and policy tradeoffs 00:37: Lessons from Netscape and encryption export controls 00:43: U.S.-China competition, open source AI, and civil-military fusion 00:50: Public sector reform and government capability 00:53: AI for public policy 00:55: Industrial renaissance and American Dynamism 1:00: Closing thoughts Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ [https://a16zpolicy.substack.com/] Follow Marc Andreessen on X: https://x.com/pmarca [https://x.com/pmarca] Follow Navin Girishankar on X: https://x.com/ngirishankar [https://x.com/ngirishankar] Follow CSIS on X: https://x.com/CSIS [https://x.com/CSIS] 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 http://a16z.com/disclosures [http://a16z.com/disclosures]. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com [https://a16zpolicy.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

The Political Economy of Little Tech

Policymakers often say they want to support startups. Republicans say it. And Democrats say it. But despite repeatedly saying they support startups, policymakers often propose rules that make it harder for those startups to build and compete. In this episode, Collin McCune, head of government affairs, joins Matt Perault, head of AI policy at a16z, to discuss the political economy of Little Tech: the structural dynamics that produce a policy process that so consistently rewards the companies with the most time, money, and access. In sum, it favors Big over Little. They also talk about the impact of the political economy of Little Tech on consumers. When regulation locks in incumbents, people end up with fewer choices, products that are lower quality and less innovative, and higher costs. Topics covered: 01:00 The paradox of policymaker support for startups 03:30 Why startups are underrepresented in the policy process 05:40 How feedback on bills works in practice 07:30 Why “industry” feedback often misses Little Tech 09:45 The costs of showing up late to policy debates 12:00 Audits, impact assessments, and invisible compliance costs 15:30 How large policy teams create incumbent advantage 18:30 Why audits can be harder than they look 21:15 Policy ideas to better account for startup costs 23:45 Why startup competition matters for everyday people 25:45 Bright spots for Little Tech in Washington 27:30 Lessons from Dodd-Frank and the risk of repeating them in tech Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ [https://a16zpolicy.substack.com/] Follow Matt Perault: https://x.com/MattPerault [https://x.com/MattPerault] Follow Collin McCune: https://x.com/Collin_McCune [https://x.com/Collin_McCune] 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com [https://a16zpolicy.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

AI is How America Builds Again

Policymakers have spent years talking about rebuilding America’s industrial base, reshoring critical supply chains, strengthening defense production, and reducing U.S. dependence on China. But recognizing the need to build is not the same as having the ability to do it. Erin Price-Wright [https://a16z.com/author/erin-price-wright/], general partner on Andreessen Horowitz’s American Dynamism practice, joins the AI Policy Brief to make the case that AI isn’t just a software story. It’s the defining factor in the sectors that determine whether the U.S. can build, power, and defend itself in the decades ahead. She and Matt Perault discuss how AI can help make the math work for building in the U.S. again—from accelerating mine permitting and coordinating complex industrial projects to designing factories, lowering the cost of automation, and bringing robotics to more factory floors. They also discuss where policy needs to catch up: the laws and regulations that make it too hard and slow to build new factories in the U.S. and defense procurement that still favors incumbents over startups. Finally, they discuss how the debates over data centers and jobs will shape whether America’s reindustrialization effort succeeds. The takeaway: if the U.S. gets the policy environment right, AI can strengthen the industrial base, help create new kinds of jobs, and give America a powerful competitive advantage. Topics covered: 00:00: Intro 00:54: Erin’s work investing in AI for the physical world 01:47: Why AI and reindustrialization are converging now 03:07: Applying AI to mining and critical minerals 08:28: What Ukraine reveals about defense production 18:13: How startups are breaking into government markets 20:16: Bringing a factory mindset to critical sectors and complex systems 24:39: How robotics can expand factory automation 30:22: What still makes it too hard to build in the U.S. 32:49: Using AI to design better, cheaper manufactured goods 35:05: Why data centers matter for reindustrialization 39:46: How compute could help modernize the grid and lower costs for consumers 42:50: Why AI could create new industrial jobs Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ [https://a16zpolicy.substack.com/] Follow Matt Perault: https://x.com/MattPerault [https://x.com/MattPerault] Follow Erin Price-Wright: https://x.com/espricewright [https://x.com/espricewright] 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com [https://a16zpolicy.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

Fixing the Front Door to Government

For AI startups, the policy landscape is expanding faster than most small teams can reasonably track. This creates a practical challenge for Little Tech: even when a startup wants to engage constructively, it may not have the resources to follow every debate in every jurisdiction. Ben Supple, head of global policy at ElevenLabs, joins Matt Perault to talk about his experience running a public policy function at a company that is scaling rapidly. ElevenLabs is a leader in voice AI, building products for creators, enterprises, and governments, while its public policy function is still small enough to count on one hand. The conversation offers a look at how a fast-growing AI company prioritizes policy work, builds relationships with governments, and makes the case for clear, consistent rules that startups can implement. They also discuss how voice AI can improve citizen services and outcomes: replacing rigid, menu-based phone trees with more intelligent conversational agents that can resolve issues, switch languages live, and offer greater accessibility. Topics covered: 00:00: Intro 01:42: What is ElevenLabs? 04:59: Voice AI use cases, from dubbing to customer service 06:59: The competitive landscape for voice AI 10:51: Building a policy function at ElevenLabs 12:00: Prioritizing policy work with a small team 15:13: Engaging policymakers across jurisdictions 18:11: Growing and shipping at startup speed 20:19: Human oversight and AI agents 22:54: Key policy issues for voice AI 25:42: Scaling into new regulatory obligations 30:17: State AI rules and the need for clear goalposts 32:25: ElevenLabs’ expansion in New York 34:10: Fixing the front door to government 36:22: Government use cases for voice AI 38:55: The social value of voice AI, One Million Voices, and accessibility Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ [https://a16zpolicy.substack.com/] Follow Matt Perault: https://x.com/MattPerault [https://x.com/MattPerault] Follow Ben Supple: https://www.linkedin.com/in/ben-supple-a900695/ [https://www.linkedin.com/in/ben-supple-a900695/] Learn more about ElevenLabs for Government: https://elevenlabs.io/chatbot/government [https://elevenlabs.io/chatbot/government] 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com [https://a16zpolicy.substack.com?utm_medium=podcast&utm_campaign=CTA_1]

A Guide to Crafting a Liability Regime for AI

How should we hold people responsible when AI causes harm? That's the job of a liability regime. In this conversation, Jai Ramaswamy, chief legal and policy officer, joins Matt Perault, head of AI policy at a16z, to unpack the role of liability in AI policy: how to protect people from real harms without slowing innovation, limiting competition, or punishing the wrong actors. They discuss why trust is essential to long-term AI adoption, why liability should focus on harmful uses rather than general-purpose development, and how policymakers can design rules that hold bad actors accountable while giving startups room to build. The conversation also explores what a workable AI liability regime should prioritize: accountability, proportionality, enforcement of existing laws, and targeted updates where current law falls short. For founders, policymakers, and anyone tracking the future of AI regulation, this episode offers a guide for thinking about responsibility, risk, and innovation in the AI era. Topics covered: 00:00: Intro 01:00: Why AI liability is on the table now, and why it's been on Jai's mind for years 02:00: Why this matters — trust, long-term ecosystems, and the equities at stake 04:00: Failure modes at both ends — crushing liability vs. blanket immunity, and why neither serves Little Tech 08:00: The proposals we're concerned about — SB 1047, strict developer liability for downstream misuse, AI as an automatic aggravating factor in criminal law 14:00: The Little Tech lens — focusing on wrongdoing, not building, and why "paperwork favors the powerful" 18:00: The least-cost avoider principle and how it maps onto AI 23:00: Building a better regime — presumption of user liability for AI outputs, procedural safeguards, and well-designed safe harbors 31:00: Protecting good behavior — information sharing, incident reporting, and getting incentives right 32:00: Federal vs. state roles — the constitutional allocation as a guide to liability design Resources: Subscribe to the a16z AI Policy Brief: https://a16zpolicy.substack.com/ [https://a16zpolicy.substack.com/] Follow Matt Perault: https://x.com/MattPerault [https://x.com/MattPerault] Follow Jai Ramaswamy: https://www.linkedin.com/in/jai-ramaswamy-85a77675/ [https://www.linkedin.com/in/jai-ramaswamy-85a77675/] 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit a16zpolicy.substack.com [https://a16zpolicy.substack.com?utm_medium=podcast&utm_campaign=CTA_1]