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Vercel EVE Framework Agent
In the **AGENTIC ERA**, and already entering the **LOOPy ERA**, Vercel is launching a framework for creating agents from a folder-based structure.
## What Is Vercel EVE?
**Vercel EVE** is an open-source framework for building and deploying AI agents using an architecture based on files and folders.
In practice, the entire agent is organized inside a single folder:
```text
agent/
├── agent.ts
├── instructions.md
├── skills/
├── tools/
├── subagents/
├── connections/
├── channels/
├── schedules/
├── sandbox/
└── evals/
```
Each directory represents one of the agent’s capabilities:
* `agent.ts`: defines the model and the main configuration;
* `instructions.md`: contains the system prompt and global rules;
* `skills/`: specialized procedures and knowledge;
* `tools/`: functions the agent can execute;
* `subagents/`: specialized agents for more complex tasks;
* `connections/`: APIs, databases, and MCP servers;
* `channels/`: Slack, Discord, an API, or a custom interface;
* `schedules/`: automated and scheduled tasks;
* `sandbox/`: isolated code execution;
* `evals/`: behavior and security tests.
EVE’s main differentiator is automatic component discovery.
You do not need to manually import every skill, tool, or subagent into the main file. The framework scans the folder structure, identifies the components, and generates a manifest with everything connected.
This turns the file system into a kind of declarative configuration for the agent.
Instead of writing one massive central file:
```ts
import toolA from "./tools/toolA";
import toolB from "./tools/toolB";
import skillA from "./skills/skillA";
import investigator from "./subagents/investigator";
```
You simply place each component in the correct folder, and EVE handles the integration during compilation.
In addition to organization, EVE adds capabilities required for production:
* durable sessions;
* recovery after failures or redeployments;
* sandboxed code execution;
* human approval for risky actions;
* testing before deployment;
* integration with Slack and APIs;
* scalability through Vercel’s infrastructure.
A simple example would be an analyst agent connected to a database.
The user asks:
```text
What was last month’s revenue?
```
The agent:
1. identifies that the question is about revenue;
2. loads the financial skill;
3. calls a query tool;
4. executes SQL against the database;
5. processes the data;
6. returns the answer in the defined format;
7. requests approval if the query is considered risky.
In summary:
> Vercel EVE is an organization, compilation, and execution layer for modular AI agents, where files and folders define the agent’s capabilities.
It is not an AI model.
It is the framework that connects:
```text
Model
+ instructions
+ skills
+ tools
+ subagents
+ MCP
+ channels
+ security
+ tests
+ infrastructure
```
The main concept is:
> An agent is a folder that can be compiled, tested, deployed, and scaled like an application.
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Vercel EVE Framework Agent
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