Talk
Last year was about Agents at Work.This year, we built our own.Meet V, Vercel’s super intelligent custom agent. See how we built it, what we learned, and how you can build your own.
Talk
How do you build in an AI-first world? Learn the agentic patterns shipping to production across hundreds of engineering teams, from self-correcting agents to multi-agent orchestration, built on AWS and Vercel. See how Vercel's BYOC on AWS delivers platform speed with full VPC control.
Talk
This presentation will explore how SAP is revolutionizing its approach to generative interfaces and compositional services, with a particular focus on the pivotal role of Vercel's technologies including v0, Eve, and json-render. Phil will delve into the transformative impact of AI on software design and delivery, demonstrating how SAP is navigating the complexities of maintaining consistent interfaces and adhering to stringent government standards in an AI-driven landscape.
Talk
Mercor connects domain experts with frontier AI labs, generating the human data used to train and evaluate leading models. Behind the platform, hundreds of business users build the apps their work depends on, and engineering teams tap a wide range of open-weight and closed models. The challenge: doing both without the business losing track of what's shipping, who has access, and what it costs. See how Mercor, with Vercel, built a managed identity layer every app inherits by default and gained full observability into who is spending and where, on a foundation that scales to the agents it's building next.
Talk
See how Notion uses Vercel's primitives to build a platform designed for both developers and AI agents.
Talk
Building a custom agents platform is one of the key pieces to unlocking AI for complex business workflows. Monte Carlo is the sales-specific system we've built to help scale Monaco's revenue: a platform where revenue teams encode their own playbooks as agents that run against everything we've ingested about their business, including pipeline, outbound, calls, and CRM. Sales is a particularly complex vertical for the following reasons: no two revenue orgs look alike, the data is large and heterogeneous, and the expertise that matters lives in per-rep workflows nobody has written down. Making it work at scale meant rebuilding the agent runtime on per-run Vercel Sandbox microVMs, a decision that propagated much further than we expected into how we handle context, how much of a playbook ends up as prose versus code, and what an agent is permitted to do at all. In this talk, I'll break down the components a verticalized agent platform needs in order to be fast and correct, including an execution substrate, memory and context, how expertise gets represented, and the evaluation loop, along with what is still unresolved.
Talk
AI coding tools make it easy to track tokens, licenses, and model spend. The harder question is what that spend actually produces. In this session, Emilie Schario, VP of Engineering at Anaconda and Co-Founder of Kilo Code, introduces AI Cost to Ship, a metric that connects AI spend with merged pull requests, and explores how leaders can use it alongside adoption, quality, and model choice to understand whether AI investment is translating into shipped engineering output.
