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 of the pieces that it needs to run in production. Instead, eve comes with production already built in:

Durable execution

Sandboxed compute

Human-in-the-loop approvals

Subagents

Evals

And more

eve is the framework that we build and run our own agents on.

Agents today are where the web was before frameworks, with everyone hand-rolling the same plumbing and nothing carrying over to the next one. Next.js ended this for the web, and eve is doing the same for agents.

An agent is a directory

This is an eve agent.

agent/  agent.ts                   # the model it runs on  instructions.md            # who it is  tools/    run_sql.ts               # what it can do    post_chart.ts  skills/    revenue-definitions.md   # what it knows  subagents/    investigator/            # who it delegates to  channels/    slack.ts                 # where it lives  schedules/    monday-summary.ts        # when it acts on its own

A data analyst agent, readable at a glance

Each file describes one component of the agent, so at a glance, the tree tells you what an agent is, what it does, where it lives, and when it acts on its own.

Create an eve agent in minutes

Every agent starts with its definition.

1import { defineAgent } from "eve";2export default defineAgent({3  model: "anthropic/claude-opus-4.8",4});

Configuring the agent and its model in one file

The agent.ts file is where you configure the agent itself. You can define the model with one line, with provider fallbacks supported through AI Gateway, and compaction, model options, and other optional fields are there when you need them.

Giving your agent a job and personality is as simple as creating an instructions.md file, which serves as the system prompt that eve puts in front of every model call.

You are a senior data analyst. You answer questions about the team's data.
- Prefer exact numbers to hand-waving. If you can compute it, compute it.- State the assumptions behind any number you report (date range, filters, grain).- Use the tools available to you rather than guessing. If you cannot answer from  the data, say so plainly.

The agent's identity and standing rules, prepended to every model call

You create files for what your agent does, like post_chart.ts and revenue-definitions.md for tools and skills, and eve wires them into a working agent without any boilerplate or plumbing to manage. You can just focus on what your agent does instead of how it does it.

Why we built eve

We had built agents for years at Vercel, v0 among them. But once coding agents made building one something anyone could do, everyone did. We shipped hundreds of agents and internal apps, and it looked like a productivity revolution.