> ## Documentation Index
> Fetch the complete documentation index at: https://ai.aidalinfo.fr/llms.txt
> Use this file to discover all available pages before exploring further.

# Build an agent in 5 minutes

> Instantiate `Agent`, generate your first answer, and understand the key options.

Agents bundle a model, instructions, and optional tools. They expose the two AI SDK execution modes: `generate` for single responses and `stream` for token streams.

## 1. Instantiate an agent

```ts theme={null}
import { Agent, scaleway } from "@ai_kit/core";

const assistant = new Agent({
  name: "docs-assistant",
  instructions: "You help developers understand the AI Kit platform.",
  model: scaleway("gpt-oss-120b"),
});
```

* `name` identifies the agent for logging and telemetry.
* `instructions` provide the default system prompt (override per call with `system`).
* `model` expects a `LanguageModel` from the AI SDK. Pick the provider you need.

## 2. Generate a single response

```ts theme={null}
const result = await assistant.generate({
  prompt: "Explain the difference between generate and stream in AI Kit.",
});

console.log(result.text);
```

The return value mirrors `ai.generateText`:

* `text` holds the final answer.
* `response` exposes raw metadata (messages, usage, tool calls, …).
* `loopTool` tells you whether the tool loop was triggered.

### Conversation mode

```ts theme={null}
await assistant.generate({
  messages: [
    { role: "user", content: "Give me three tutorial ideas." },
  ],
  maxOutputTokens: 256,
});
```

When you pass `messages`, AI Kit automatically injects the agent instructions as a system message.

## 3. Enable telemetry

```ts theme={null}
const supportAgent = new Agent({
  name: "support-assistant",
  model: scaleway("gpt-oss-120b"),
  telemetry: true,
});
```

The `telemetry` flag enables Langfuse export when instrumentation is configured. Call `agent.withTelemetry(false)` to disable it temporarily.

## 4. Keep exploring

* Add tools and control the loop with [`loopTools`](/en/agents/tools).
* Stream tokens in real time with [`agent.stream`](/en/agents/streaming).
* Validate answers via [`structuredOutput`](/en/agents/structured-output).