Data Security NoticeWhen exposing the same agent to multiple end users in Community Edition, Dify applies precautionary safeguards intended to reduce cross-conversation data access risks. However, CE relies on soft isolation rather than hard per-user or per-run filesystem isolation, and runs may share the same underlying container or base filesystem.As a result, malicious prompts, tool execution, or similar attacks may still access data outside the intended working directory. For strict security or compliance requirements, use Dify Cloud or Enterprise, or deploy with separate hardened infrastructure isolation.
The new Agent is in beta: deploy the Dify 1.16.0-rc1 release to try it out. It’s on by default on Docker Compose, with its runtime bundled in.For production, replace DIFY_AGENT_SERVER_SECRET_KEY with your own random value.
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It works in a sandbox of its own: it runs commands, installs programs, and reads and writes files, so it takes on open-ended work rather than just calling the tools you configured.
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You build it once and use it two ways: on its own as a chat app, or as a step inside a workflow.
Create, configure, and manage your agents on the Agents page. Open one anytime to refine it or revisit an earlier version.
Capability and Task
An Agent separates what it is from what you ask it to do:
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Its capability (think of it as the agent’s soul) is who the agent is.
The role and prompt you write, the model it runs on, and the knowledge, skills, Dify tools, and files you give it. You shape it once and keep refining it as you learn what the agent needs.
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Its task is what you ask it to do on a given run.
When the agent works on its own, the task is the message you send it. When it works inside a workflow, the task is the instruction you give the node.
It’s the same split as hiring someone: you choose a person for what they can do, then give them a specific task. Strong results need both: the right person for the job and a clear brief.
Two Ways to Use an Agent
On Its Own
The agent runs as its own chat app. You give it tasks by chatting, and you can publish it as a web app or call it through the service API.
Choose this when a single capable worker can reach the goal on its own: a support assistant that looks things up and answers, or a research agent that gathers sources and summarizes them.
Inside a Workflow
You invite the agent into an Agent node to handle one step of a larger process. There you set only the task you want done. It’s like asking a colleague to take care of one thing: you describe the task, and they bring their own skills to it.
Choose this when the work needs structure around it: several steps in a set order, branching on conditions, other kinds of nodes, or a few specialized agents handing off to each other.
