In this episode, a16z General Partner Martin Casado sits down with Sujay Jayakar, co-founder and Chief Scientist at Convex, to talk about his team’s latest work benchmarking AI agents on full-stack coding tasks. From designing Fullstack Bench to the quirks of agent behavior, the two dig into what’s actually hard about autonomous software development, and why robust evals—and guardrails like type safety—matter more than ever. They also get tactical: which models perform best for real-world app building? How should developers think about trajectory management and variance across runs? And what changes when you treat your toolchain like part of the prompt? Whether you're a hobbyist developer or building the next generation of AI-powered devtools, Sujay’s systems-level insights are not to be missed.

Drawing from Sujay’s work developing the Fullstack-Bench, they cover:

• Why full-stack coding is still a frontier task for autonomous agents
• How type safety and other “guardrails” can significantly reduce variance and failure
• What makes a good eval—and why evals might matter more than clever prompts
• How different models perform on real-world app-building tasks (and what to watch out for)
• Why your toolchain might be the most underrated part of the prompt
• And what all of this means for devs—from hobbyists to infra teams building with AI in the loop

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Introducing Fullstack-Bench

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Martin Casado

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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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In this episode of AI + a16z,  Resend founder and CEO Zeno Rocha sits down with a16z partner Yoko Li to discuss:

• How generative AI — powered by agents and, now, MCP — is reshaping the email experience for developers, as well as the overall world of programming. 
• Zeno's obsession with developer experience has evolved into designing for "agent experience" — a new frontier where LLM-powered agents are not only building products but also operating within them. 
• How email, one of the most ubiquitous tools for developers and end users alike, is being reimagined for a future where agents send, parse, and optimize communication. 
• What it means to build agent-friendly APIs. 
• The emerging MCP protocol, and how AI is collapsing the creative loop for prosumers and developers alike.

Learn more:

What is AX (agent experience) and how to improve it

A deep dive into MCP and the future of AI tooling

Dracula theme

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Yoko Li

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In this episode of AI + a16z, a16z Partner Joe Schmidt sits down with 11x CTO Prabhav Jain for an inside look at how AI-powered digital workers are reshaping sales and revenue operations. They discuss the evolution of agentic AI, the trade-offs between orchestration and autonomy, and the technical innovations driving 11x’s products, Alice and Mike.

Prabhav breaks down the challenges of real-time voice AI, the complexities of multimodal agent interactions, and why the future of enterprise AI is about delivering measurable customer outcomes—not just automation. They also dive into the fast-moving landscape of model providers, the impact of open-source AI, and how startups can stay ahead in an environment of constant technological change.

Plus, they explore 11x’s bold decision to re-architect its platform from the ground up, the lessons learned from scaling AI-powered sales automation, and what it takes to build truly effective digital workers.

• The difference between true AI agents and complex orchestrations—and why it matters.
• How 11x built Alice and Mike to deliver human-like sales performance at scale.
• The cutting-edge advancements shaping AI voice assistants and real-time multimodal interactions.
• Lessons from rebuilding an AI platform while supporting a fast-growing customer base.
• How AI startups can balance rapid iteration with long-term strategic bets.

For anyone interested in AI-powered automation, enterprise sales, or the future of digital work, this episode offers a front-row seat to the latest innovations pushing the boundaries of AI agents.

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11x

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In this episode of AI + a16z, Sesame Cofounder and CTO Ankit Kumar joins a16z general partner Anjney Midha for a deep dive into the research and engineering behind their voice technology. They discuss the technical challenges of real-time speech generation, the trade-offs in balancing personality with efficiency, and why the team is open-sourcing key components of their model. Ankit breaks down the complexities of multimodal AI, full-duplex conversation modeling, and the computational optimizations that enable low-latency interactions. 

They also explore the evolution of natural language as a user interface and its potential to redefine human-computer interaction.
Plus, we take audience questions on everything from scaling laws in speech synthesis to the role of in-context learning in making AI voices more expressive.

Key Takeaways:
How Sesame AI achieves natural voice interactions through real-time speech generation.

• The impact of open-sourcing their speech model and what it means for AI research.
• The role of full-duplex modeling in improving AI responsiveness.
• How computational efficiency and system latency shape AI conversation quality.
• The growing role of natural language as a user interface in AI-driven experiences.

For anyone interested in AI and voice technology, this episode offers an in-depth look at the latest advancements pushing the boundaries of human-computer interaction.

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The Maya + Miles demo

Crossing the uncanny valley of conversational voice

Sesame CSM 1B model

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Anjney Midha

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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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In this episode of AI + a16z, Netlify CEO and Cofounder Matt Biilmann joins a16z General Partner Martin Casado to explore how AI is reshaping web development — not just through faster code generation, but by fundamentally shifting how we think about building for the web. At the center of this shift is Agent Experience (AX), a new paradigm where AI agents aren’t just tools, but active participants in development, shaping both the creative process and the underlying infrastructure.

Matt shares how Netlify is evolving to meet this future, why the next 100 million web developers will collaborate with AI, and what’s at stake if the web doesn’t adapt — will we see a thriving, open, AI-powered internet, or a future dominated by walled gardens?

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Introducing AX: Why Agent Experience Matters

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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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In this episode of AI + a16z, a trio of security experts join a16z partner Joel de la Garza to discuss the security implications of the DeepSeek reasoning model that made waves recently. It's three separate discussions, focusing on different aspects of DeepSeek and the fast-moving world of generative AI.

The first segment, with Ian Webster of Promptfoo, focuses on vulnerabilities within DeepSeek itself, and how users can protect themselves against backdoors, jailbreaks, and censorship. 

The second segment, with Dylan Ayrey of Truffle Security, focuses on the advent of AI-generated code and how developers and security teams can ensure it's safe. As Dylan explains, many problem lie in how the underlying models were trained and how their security alignment was carried out.

The final segment features Brian Long of Adaptive, who highlights a growing list of risk vectors for deepfakes and other threats that generative AI can exacerbate. In his view, it's up to individuals and organizations to keep sharp about what's possible — while the the arms race between hackers and white-hat AI agents kicks into gear.

Learn more: 

What Are the Security Risks of Deploying DeepSeek-R1?

Research finds 12,000 ‘Live’ API Keys and Passwords in DeepSeek's Training Data

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Dylan Ayrey

Brian Long

Joel de la Garza

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In this episode of AI + a16z, Aatish Nayak, head of product at Harvey, sits down with a16z partner Kimberly Tan to share his experience building AI products for enterprises — including the legal profession — and how to address areas like UX, trust, and customer engagement. Importantly, Aatish explains, industries like law don't need AGI or even the latest and greatest models; they need products that augment their existing workflows so they can better serve clients and still make it home for dinner.

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BigLaw Bench

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In this episode of AI + a16z, a16z partner Alex Immerman sits down with Hebbia founder and CEO George Sivulka to discuss the potential for reasoning models and AI agents to supercharge knowledge-worker productivity — and the global economy along with it. As George explains, his customers are already saving significant time and and effort on important, but monotonous, tasks, and improved models paired with savvy users will continue to reshape how industries including finance, law, and other professional services operate.

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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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In this episode of AI + a16z, Fivetran cofounder and CEO George Fraser and a16z partner Guido Appenzeller discuss how LLMs fit into the data management picture within large enterprises. In order to take advantage of a potentially revolutionary technology, organizations don't need to rip out their existing infrastructure, but they do need to rethink their data hygiene so language models can understand it.

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Derrick Harris

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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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In this episode of AI + a16z, a16z General Partner Martin Casado and Rasa cofounder and CEO Alan Nichol discuss the past, present, and future of AI agents and chatbots. Alan shares his history working to solve this problem with traditional natural language processing (NLP), expounds on how large language models (LLMs) are helping to dull the many sharp corners of natural-language interactions, and explains how pairing them with inflexible business logic is a great combination.

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Task-Oriented Dialogue with In-Context Learning

GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Application

CALM Summit

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Martin Casado

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