AI + a16z

• Models, Modalities, and Memes: Creating Compelling AI Characters

  Models, Modalities, and Memes: Creating Compelling AI CharactersIn this episode of AI + a16z, Hedra founder and CEO Michael Lingelbach joins a16z partners Justine Moore and Matt Bornstein to talk about building AI-native video — and why the next wave of generative content is all about characters, not just clips.They discuss how Hedra’s expressive, full-body, dialogue-centric video models are powering everything from viral meme content to enterprise training tools. Michael explains why “character” is the core design primitive in Hedra’s architecture, how consumers are leading the charge in discovering new use cases, and what it takes to productionize those behaviors for real-world applications.Along the way, they explore what makes multi-modal generation uniquely hard, the role of user control in shaping believable AI performances, and why being a founder sometimes means responding to thousands of support emails — at 6 a.m.Key takeaways:How Hedra’s real-time video model blends audio, image, and character controlWhy generative content is shifting from static avatars to programmable personasThe surprising crossover between consumer creativity and enterprise adoptionWhere existing LLMs fall short in generating emotionally authentic charactersWhat vibe coding, hands-on design, and founder obsession look like in practiceFor anyone curious about building AI characters, scaling creative workflows, or the future of human-computer interaction — this one’s not to be missed. Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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• Performance and Passion: Fal's Approach to AI Inference

  If you've been experimenting with image, video, and audio models, the chances are you've been both blown away by how good they're becoming, and also a little perturbed by how long they can take to generate. If you've been using a platform like Fal, however, your experience on the latter point might be more positive.In this episode, Fal cofounder and CEO Burkay Gur and head of engineering Batuhan Taskaya join a16z general partner Jennifer Li to discuss how they built an inference platform — or, as they call it, a generative media cloud — that's optimized for speed, performance, and user experience. These are core features for a great product, yes, and also ones borne of necessity as the early team obsessively engineered around its meager GPU capacity at the height of the AI infrastructure crunch.But this is more than a story about infrastructure. As you'll hear, they also delve into sales and hiring strategy; the team's overall excitement over these emerging modalities; and the trends they're seeing as competition in the world of video models, especially, heats up.  Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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• How to Vibe Code Securely

  In this episode, a16z partner Joel de la Garza sits down with Socket founder and CEO Feross Aboukhadijeh to dive into the intersection of vibe coding and security. As one of the earliest security founders to fully embrace LLMs, Feross shares firsthand insights into how these technologies are transforming software engineering workflows and productivity — and where there are sharp edges that practitioners need to avoid.The TL;DR: Treat AI-assisted programming the same way you'd treat other programming, by vetting packages, reviewing code, and generally make sure you're not sacrificing security for speed. As he explained, LLMs can make developers more productive and even make their software more secure, but only if developers do their part by maintaining a safe supply chain.Follow everyone on social media: Feross AboukhadijehJoel de la Garza Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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• AI Is Upending SaaS Pricing

  In this episode, a16z GP Martin Casado sits down with Metronome CEO Scott Woody to unpack how AI is fundamentally changing the value proposition of software—and why that shift demands a rethink of the traditional SaaS business model.They explore how, in the cloud era, value scaled with the number of users accessing a shared system (think Salesforce). However, in the AI era, value shifts to the work the software performs on your behalf, automating tasks such as writing code or resolving support tickets. As a result, the old value metric of “users” is being replaced by “output,” and it’s upending how companies monetize.This conversation goes deep on:What new pricing models will emerge in an AI-native world Why usage-based billing is gaining ground—and where it breaks How to align GTM teams and customer success orgs with evolving value metrics Strategic advice for SaaS founders navigating hybrid business models and incentive designIf you’re selling software today, you don’t want to miss this discussion.Follow everyone on social media:Scott Woody Martin Casado  Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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• The AI Infrastructure Stack with Jennifer Li

  In this episode, which originally aired on the Complex Systems Podcast, a16z General Partner Jennifer Li discusses how AI is reshaping every layer of the software stack, creating demand for new types of middleware. Jennifer talks about emerging infrastructure categories and why the next wave of valuable companies might be the unsexy infrastructure providers powering tomorrow's intelligent applications.Subscribe to Complex Systems:SpotifyApple Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.

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