AI + a16z

Mintlify is a documentation platform built by cofounders Han Wang and Hahnbee Lee to help teams create and maintain developer docs. In this episode, Andreessen Horowitz general partners Jennifer Li and Yoko Li speak with Han and Hahnbee about how coding agents are changing what “good docs” mean, shifting documentation from a human-only resource into infrastructure that powers AI tools, support agents, and internal knowledge workflows. They share Mintlify’s early journey, including eight pivots, the two-day prototype that landed their first customer, and the “do things that don’t scale” sales motion that helped them win early traction. The conversation also covers why docs go out of date, what “self-healing” documentation requires to actually work, and how serving fast-moving customers has shaped both their product priorities and their pace.
Follow Jennifer Li on X: https://twitter.com/JenniferHli
Follow Yoko Li on X: https://twitter.com/stuffyokodraws
Follow Han Wang on X: https://twitter.com/handotdev
Follow Hahnbee Lee on X: https://twitter.com/hahnbeelee

Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Inferact is a new AI infrastructure company founded by the creators and core maintainers of vLLM. Its mission is to build a universal, open-source inference layer that makes large AI models faster, cheaper, and more reliable to run across any hardware, model architecture, or deployment environment. Together, they broke down how modern AI models are actually run in production, why “inference” has quietly become one of the hardest problems in AI infrastructure, and how the open-source project vLLM emerged to solve it. The conversation also looked at why the vLLM team started Inferact and their vision for a universal inference layer that can run any model, on any chip, efficiently.
Follow Matt Bornstein on X: https://twitter.com/BornsteinMatt
Follow Simon Mo on X: https://twitter.com/simon_mo_
Follow Woosuk Kwon on X: https://twitter.com/woosuk_k
Follow vLLM on X: https://twitter.com/vllm_project

Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

To Regulate AI Effectively, Focus on How It’s Used
A conversation with Martin Casado on learning from past computing platform shifts, understanding marginal risk in AI, and why open source matters for US competitiveness.
One of the core pillars of our roadmap for federal AI legislation makes clear AI should not excuse wrongdoing. When people or companies use AI to break the law, existing criminal, civil rights, consumer protection, and antitrust frameworks should still apply. Enforcement agencies should have the resources they need to enforce the law. If existing bodies of law fall short in accounting for certain AI use cases, any new laws should be evidence-based, clearly defining marginal risks and the optimal approach to target harms directly. 
In this conversation, we go deeper on what that principle means in practice with Martin Casado, general partner at a16z where he leads the firm’s infrastructure practice and invests in advanced AI systems and foundational compute. Martin has lived through multiple platform shifts–as a researcher where he worked on large-scale simulations for the Department of Defense before working with the intelligence community on networking and cybersecurity, a pioneer of software-defined networking at Stanford, and the cofounder and CTO of Nicira, which was acquired by VMware–giving him a rare perspective on how breakthrough technologies are governed as they develop and scale. 
Martin joins Jai Ramaswamy and Matt Perault to discuss how decades of technology policy can inform addressing harmful uses of AI, defining marginal risk in AI, the importance of open source for long-term competitiveness, and more. 
 
Follow Jai Ramaswamy on X: https://twitter.com/jai_ramaswamy
Follow Matt Perault on X: https://twitter.com/MattPerault
Follow Martin Casado on X: https://twitter.com/martin_casado
Read the a16z AI Policy Brief here: https://a16zpolicy.substack.com/

Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When four MIT grads decided to build a code editor while everyone else was building AI agents, they created the fastest-growing developer tool ever built. 
Cursor CEO Michael Truell joins a16z’s Martin Casado to discuss the deliberate constraints that led to breakthroughs: why they rejected the "democratization" narrative to focus on power users, how their 2-day work trials test for agency over credentials, and the strategic decision to own the editor when conventional wisdom said it was impossible.
Follow Michael on X: https://x.com/mntruell 
Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! 
Find a16z on X: https://x.com/a16z 
Find a16z on LinkedIn: https://www.linkedin.com/company/a16z 
Listen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX 
Listen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 
Follow our host: https://x.com/eriktorenberg

Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nvidia’s $5 billion investment in Intel is one of the biggest surprises in semiconductors in years. Two longtime rivals are now teaming up, and the ripple effects could reshape AI, cloud, and the global chip race.
To make sense of it all, Erik Torenberg is joined by Dylan Patel, chief analyst at SemiAnalysis, joins Sarah Wang, general partner at a16z, and Guido Appenzeller, a16z partner and former CTO of Intel’s Data Center and AI business unit. Together, they dig into what the deal means for Nvidia, Intel, AMD, ARM, and Huawei; the state of US-China tech bans; Nvidia’s moat and Jensen Huang’s leadership; and the future of GPUs, mega data centers, and AI infrastructure.
Resources: 
Find Dylan on X: https://x.com/dylan522p
Find Sarah on X: https://x.com/sarahdingwang
Find Guido on X: https://x.com/appenz
Learn more about SemiAnalysis: https://semianalysis.com/dylan-patel/

Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.