---
title: Overview
description: The AI assistant built into deco Studio
icon: Sparkles
---

import Callout from "../../../../../components/ui/Callout.astro";

## What is Decopilot?

**Decopilot** is the AI assistant built into deco Studio — the **org's pilot**. It's the chat you land on at Home, and it has visibility across your entire organization: every agent, every connection, every tool. It's not a chatbot bolted on the side; it's a router and executor in one.

You start a conversation and Decopilot works in the background. When it needs your input, it asks. Otherwise it keeps going — answering inline, reaching into your connected tools, or handing focused work to a specialist [agent](/en/studio/agents). Every conversation is saved under **Decopilot** in the sidebar.

## How it works

Decopilot follows a simple loop: understand the task → take action → check the result → repeat. It reads from your connected services, calls the right tools, and adapts based on what it learns.

What makes it different from a regular AI chat is that it can reach into the apps where your actual work lives — it's not limited to answering questions. It can look up orders, update records, send notifications, and coordinate workflows across multiple services in one go.

## It can run the platform for you

Decopilot isn't just for using your tools — it can **set Studio up for you**, straight from the chat. Ask in plain language and it handles the configuration that a power user would otherwise click through by hand:

- **Create and configure agents** — "make me an agent that triages support email"
- **Set up automations** — "run this every weekday at 9am"
- **Connect new tools** — "connect our Shopify store"; if a connection is missing mid-task, Decopilot surfaces an inline prompt to add it and continues once you approve
- **Browse and install from the [Store](/en/studio/store)** — find and add MCP servers from the catalog
- **Manage your organization** — invite members, adjust settings

Under the hood, Decopilot delegates each of these to a built-in **manager agent** — one each for agents, automations, connections, the Store, brand, and usage — but from your seat it simply happens in the conversation. This is what makes Studio approachable: a new, non-technical user can get real work done by asking, without learning where every setting lives.

## Scope: where you're working determines what's available

Decopilot adapts to where you are in Studio:

- **Organization scope** — you're at the home screen with no agent open. Decopilot has access to org-wide built-in tools (managing connections, agents, members) and your full agent catalog.
- **Agent scope** — you've opened a specific agent. Decopilot now uses *that agent's* tools and instructions, with the agent's thread history as context.

To switch, just open or close an agent from the sidebar. There's nothing extra to configure.

## Chat modes

The chat input has a mode selector that shapes how Decopilot approaches a turn. You can switch modes at any time without losing your conversation.

| Mode | What changes |
|---|---|
| **Default** | Normal chat — Decopilot picks tools on its own. |
| **Plan** | Decopilot must end the turn with a `propose_plan` call. Destructive tools are blocked until you approve a plan; only read-only tools can be enabled. Useful before doing something risky. |
| **Web search** | The first step is forced to call `web_search`, which streams a quick search result directly to you. Requires a web-search model under [AI Providers](/en/studio/ai-providers). |
| **Deep research** | The first step is forced to call `deep_research`, which runs a slow, multi-source async research pass. Requires a deep-research model under [AI Providers](/en/studio/ai-providers). |
| **Gen image** | The first step is forced to call `generate_image`. Requires an image model. |

## Models

Decopilot works with multiple AI providers — Anthropic, Google, OpenRouter, the Deco AI Gateway, and self-hosted models. Pick a stronger model for complex tasks and a faster one for simple operations. See [AI Providers](/en/studio/ai-providers).

## Agents and subtasks

When a task needs focused work — a customer-support question, a research pass, a data analysis — Decopilot can hand it off to a specialist [agent](/en/studio/agents) or directly to a concrete MCP connection in a **subtask**. A connection target runs as an ephemeral subagent, so it doesn't require a dedicated agent configuration. The subtask runs independently with its own clean context, then reports a summary back. Your main conversation stays clean.

## Built-in tools

Decopilot ships with tools for coordinating work across any scope:

| Tool | What it does |
|---|---|
| `subtask` | Delegates work to a specialist agent or concrete MCP connection |
| `user_ask` | Asks you a question when it needs clarification |
| `enable_tool` | Activates a scope tool for use in subsequent steps |
| `read_resource` | Reads documentation or guidelines available in scope |
| `read_prompt` | Reads a reusable prompt template |
| `read_tool_output` | Re-reads a previous tool result that was offloaded to storage |
| `web_search` | Runs a quick streaming web search and streams the result |
| `deep_research` | Runs a slow, multi-source async research pass and returns a synthesized report |
| `generate_image` | Creates an image with the configured image model |
| `propose_plan` | Proposes a plan for your approval (plan mode only) |

When an agent is backed by a sandbox (a linked GitHub repo), Decopilot also gets six **VM tools** — `bash`, `read`, `write`, `edit`, `grep`, `glob` — so it can execute and modify code in that sandbox.

Sandboxes also mount the **organization filesystem** under `org/`: `org/home/` is the org's shared home — editable, free-form, shared across every member, agent, and run, where agents record durable knowledge and check for context before starting work; `org/upload` holds the files attached to the current conversation (chat attachments land there automatically — no copy step); `org/output` is the current run's shared output folder; and `org/public/<set>` exposes curated read-only skill sets synced from versioned repositories. Files written to the home folder and `org/output` sync to your organization's cloud storage and are visible to every member and agent; external changes appear inside the sandbox within about a second.

<Callout type="info">
  **macOS desktop links:** when a sandbox runs on your machine (`deco link`),
  the `org/` folders are network volumes, and macOS asks once per app for
  permission to access them. Approve the "access files on a network volume"
  prompt for your terminal or editor — or enable it manually under **System
  Settings → Privacy & Security → Files & Folders → _your app_ → Network
  Volumes**. Without the grant, reads and writes in `org/` fail with
  "Operation not permitted".
</Callout>

For the full reference, see [Tools](/en/studio/decopilot/tools).

---

## Learn more

**[Context and tasks](/en/studio/decopilot/context-and-tasks)** — how memory works, and how to use subtasks for heavy work

**[Tools](/en/studio/decopilot/tools)** — full reference for built-in and scope tools
