The a16z Show

Amazon expects to spend roughly $220 billion in CapEx in 2026, yet CEO Andy Jassy says the company is still leaving meaningful AI demand on the table.** He believes the buildout could ultimately help make AWS a $1 trillion annual run-rate business. Andy joins a16z co-founder Ben Horowitz and Erik Torenberg to discuss why AI demand is growing so quickly, how Amazon decides how much infrastructure to build, and why lower inference costs could unlock broader enterprise adoption. They also discuss how AI is reshaping Amazon itself, from smaller teams building products faster to reimagining Alexa, and why Andy sees cybersecurity, human judgment, and critical thinking as increasingly important in the AI era.

a16z is expanding a16z crypto into a16z Frontier, a broader mandate to back founders building at the edges of what's possible. Chris Dixon joins Marc Andreessen, Ben Horowitz, and Erik Torenberg to explain why founders should increasingly ask not “is this too ambitious?” but “is this ambitious enough?” — and how AI could pull decades of technological progress forward across hardware, robotics, entertainment, science, and entirely new forms of media. They also explore the coming internet of AI agents, why open source matters as AI becomes more powerful, and why some of the most important companies of the next decade may combine technologies and business models that previously belonged in separate categories.

AI agents can reason over enormous amounts of information, but much of the world’s actual work is still trapped in PDFs, spreadsheets, scans, and other formats that models struggle to reliably understand. Reducto co-founder and CEO Adit Abraham argues that solving this document layer is essential if agents are going to take on consequential work in healthcare, legal, finance, and insurance. Adit joins a16z General Partner Jennifer Li to explain why traditional OCR breaks down on messy real-world documents, how Reducto combines vision-language models with specialized infrastructure to reach high accuracy without sacrificing cost or latency, and why frontier models can silently drop information on long extraction tasks. Reducto now processes billions of pages each month, including its seven billionth page the morning of the recording. They also discuss Reducto’s R1 model, agents that can review and correct their own document extraction, and the company’s push beyond simply reading files toward letting agents reliably work with and edit them. Underneath it all is a higher-stakes problem: when a misread word can affect a healthcare claim or financial decision, getting the input right matters just as much as making the model smarter.

More than 300 million people use ChatGPT for health and wellness questions each week. OpenAI’s Karan Singhal thinks that’s only the beginning: the longer-term goal is AI that can help people navigate their health proactively, while making trustworthy medical intelligence dramatically more accessible. Karan joins a16z Partner Jay Rughani to explain why OpenAI trains healthcare expertise directly into its general-purpose frontier models, how it works with hundreds of medical experts to evaluate safety and disagreement, and why the company sees AI as a complement to doctors rather than a replacement for medical care. They also discuss integrations with Epic, AI copilots for clinicians, and what happens as personal agents begin navigating appointments, health records, and other fragmented parts of the healthcare system. Looking further ahead, Karan makes the case that the cost of medical intelligence could continue to fall dramatically, allowing AI to act as a safety net for patients and clinicians, surface insights from years of health data, and potentially accelerate the discovery and validation of new treatments.

Why hasn't AI transformed everyday work as quickly as coding? Town CEO Jean-Denis Greze argues the bottleneck isn't intelligence, but making AI useful to people who don't have the time or technical skills to build their own automations. Jean-Denis joins a16z General Partner Alex Rampell to share why he pivoted Town from tax software to a personal AI assistant built around email, calendars, and the workflows that run businesses. They discuss why consumer-grade experiences may win in enterprise AI, how Town discovers and automates tasks users wouldn't think to delegate, and why model neutrality and data ownership matter as AI labs increasingly compete with application companies. They also explore what happens when agents begin acting on our behalf, from managing everyday work to shopping and commerce, and why the next generation of software may need to adapt to each user rather than the other way around.