Robert Ta introduces Eve, Vercel's open-source agent framework with durable execution, sandboxed compute, and human-in-the-loop approvals. It uses a directory structure where each agent is defined by files like agent.ts and Instructions.md, designed to be production-ready and scalable.
Vercel drops Next.js for agents, and it's already running 100+ production agents. Introducing Eve. Today we are proud to introduce Eve, an open-source agent framework for building, running, and scaling agents. Eve is designed around the idea that building an agent should mean defining what it does without assembling all the pieces that it needs to run in production. Instead, Eve comes with production already built in. So batteries included, durable execution, sandboxed compute, human-in-the-loop approvals, subagents, evals, and more. The tagline is Next.js for agents. And the core design principle, agent is a directory. This is an Eve agent. Agent.ts, the model it runs on. Instructions.md, who it is. Tools, what it can do. Skills, what it knows. Subagents, who it delegates to. Channels, where it lives. And schedules when it acts on its own with jobs. Curious what you think of their opinionated take here on their Harness architecture.
I really like the idea of a Next.js for agents, a Vercel-like experience for agents. Like you and I have talked about this, like we, we need a container to just like ship our agents and manage them. I think like if we look back at when was Harness engineering coined, I think that set off the clock for like a lot of us to say, what's the Harness that I need and how can I build this? And then you have this from Vercel, you have a lot of other Harness engineering type of frameworks that are just reaching maturity enough to be released in the wild. What I really like about this is that it is, uh, stress tested with internally at Vercel and with some of their clients. So you're getting sort of a mature framework that's tested. The package descriptions and how they're building the file structure, there's nothing magical there. It's just like a good tested pattern that you can use and you can inherit, you can build off of. So this definitely got me thinking about how should we rethink the things that we really want to innovate on, building off of these kind of best practices that the companies with resources and access to customer data are building them. I think I've got a project today to sort of like say, let me rethink the architecture of our stack harness and say, where do we want to put the emphasis? Because I think what we're saying is how can we capture the human domain expertise? How can we use that in evals? How can we create an LLM judge and incubate an agent through this harness into the place where it's a closed loop system that can add value to customers?
