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 The conversation also covers why docs go out of date, what “self-healing” documentation requires to actually work, and how serving fast-moving customers has shaped both their product priorities and their pace.

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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.

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In this feed drop from The Six Five Pod, a16z General Partner Martin Casado discusses how AI is changing infrastructure, software, and enterprise purchasing. He explains why current constraints are driven less by technical limits and more by regulation, particularly around power, data centers, and compute expansion.

The episode also covers how AI is affecting software development, lowering the barrier to coding without eliminating the need for experienced engineers, and how agent-driven tools may shift infrastructure decision-making away from humans.

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Sourcegraph's CTO just revealed why 90% of his code now comes from agents—and why the Chinese models powering America's AI future should terrify Washington. While Silicon Valley obsesses over AGI apocalypse scenarios, Beyang Liu's team discovered something darker: every competitive open-source coding model they tested traces back to Chinese labs, and US companies have gone silent after releasing Llama 3. The regulatory fear that killed American open-source development isn't hypothetical anymore—it's already handed the infrastructure layer of the AI revolution to Beijing, one fine-tuned model at a time.

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The a16z AI Apps team outlines how they are thinking about the AI application cycle and why they believe it represents the largest and fastest product shift in software to date. The conversation places AI in the context of prior platform waves, from PCs to cloud to mobile, and examines where adoption is already translating into real enterprise usage and revenue. They walk through three core investment themes: existing software categories becoming AI-native, new categories where software directly replaces labor, and applications built around proprietary data and closed-loop workflows. Using portfolio examples, the discussion shows how these models play out in practice and why defensibility, workflow ownership, and data moats matter more than novelty as AI applications scale.

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Not an offer or solicitation. None of the information herein should be taken as investment advice; Some of the companies mentioned are portfolio companies of a16z. Please see https://a16z.com/disclosures/ for more information.  A list of investments made by a16z is available at https://a16z.com/portfolio

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The Stanford PhD who built DSPy thought he was just creating better prompts—until he realized he'd accidentally invented a new paradigm that makes LLMs actually programmable. 

While everyone obsesses over whether LLMs will get us to AGI, Omar Khattab is solving a more urgent problem: the gap between what you want AI to do and your ability to tell it, the absence of a real programming language for intent. He argues the entire field has been approaching this backwards, treating natural language prompts as the interface when we actually need something between imperative code and pure English, and the implications could determine whether AI systems remain unpredictable black boxes or become the reliable infrastructure layer everyone's betting on.

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

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a16z cofounders Marc Andreessen and Ben Horowitz join a16z general partner Erik Torenberg and Not Boring founder Packy McCormick for a conversation on how the media and information ecosystem has changed over the past decade. The discussion breaks down the shift toward a more open and decentralized speech environment, the rise of writer- and creator-led platforms like Substack, and the erosion of centralized media gatekeepers. Marc and Ben also tie these dynamics to their investing worldview, outlining how supply-driven markets, major technological step changes, and reputation-driven venture platforms shape outcomes in the AI era.

Timecodes: 

00:00  Introduction
00:46  How the media ecosystem is changing
4:20  Why a16z invested in Substack
6:28  Supply-driven markets and new content creation
8:07  Why writers felt trapped by media companies
10:09  Databricks and the 10x cloud multiplier
13:58  Long-form podcasting proves demand
15:40  What the new fund signals about the future
16:24  AI as a universal problem solver
18:49  Why market sizing is broken
20:45  Go-to-market, policy, and platform power
22:37  Turning inventors into confident CEOs
25:58  Borrowing power to scale faster
27:29  Building dreamers, not killing dreams
30:46  Reputation as a core competitive advantage
35:57  Taking arrows in public
38:56  Avoiding big company failure modes
40:39  Autonomous teams inside a16z
41:54  Venture capital as the last job
46:01  Why intangibles matter more than ever
48:17  Original thinkers with charisma
50:06  Why Zoomers are different

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a16z General Partner Alex Rampell joined the Technology Brothers Podcast Network following the announcement of Andreessen Horowitz’s new fund to discuss what drives founders to build enduring companies. Drawing on his journey from early software entrepreneur to leading a16z’s apps fund, Alex shared how high agency, deep historical understanding, and the ability to attract talent, capital, and customers separate great founders from the rest. He reflected on motivation beyond money, explaining why “revenge or redemption” often fuels the resilience required to push through the hardest moments of company building.

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AI is changing how companies are built and how venture firms operate, forcing faster decisions, clearer judgment, and new ways of working.

In this exclusive conversation, Ben Horowitz shares how Andreessen Horowitz adapts to that shift. He explains why managing GPs is different from running a company, how investors are evaluated at the moment of decision rather than years later, and why verticalized teams help the firm scale without internal politics.

Ben also breaks down the current AI cycle, from treating AI as a new computing platform to why application design and model orchestration matter more than raw model size. He discusses the return of M&A and why today’s AI market reflects real demand, not just inflated valuations.

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This episode is a special feed drop from The Twenty Minute VC, featuring a conversation between Harry Stebbings and a16z General Partner Alex Rampell.

Alex shares how he thinks about investing at scale, including why ownership and incentives matter, how venture changes as funds get larger, and what it really takes to win the best deals. He walks through his core founder framework of backing people who can materialize talent, capital, and customers, and explains why the strongest companies often have “hostages,” not just customers.

The discussion also covers pricing risk, secondaries, moral hazard in private markets, and how AI is reshaping software, labor, and company formation. Together, Harry and Alex unpack what it takes to build durable, category-defining companies in an era where technology is moving faster than ever.

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