ElevenLabs Agent Workflows: Build Smarter AI Conversations with Visual Control
AI agents work best when they can adjust to what people actually say. ElevenLabs has introduced a new way to control this behavior with its Agent Workflows feature. It lets you visually map how an AI agent should act during a conversation. You can set paths, define actions, and even hand the chat over to another agent or tool when needed.
Imagine drawing a flowchart for your chatbot. That is what Agent Workflows make possible, but with far more depth and real functionality built into ElevenLabs’ system. It gives creators full control over logic, responses, and outcomes in a clear, visual format.
Table of Contents
What Are Agent Workflows?
Agent Workflows are part of the ElevenLabs Agents Platform. They allow creators to build structured conversation paths using connected blocks called nodes. Each node performs a task, such as asking a question, calling a tool, or ending a conversation. The lines that connect them are called edges, and they decide how the conversation moves from one step to the next.
With workflows, conversations no longer have to follow a simple, straight line. You can create multiple branches, alternate paths, and fallback options, which help the agent react naturally to different user requests.
What are the Node Types?
Here are the main node types in the ElevenLabs workflow system:
Subagent Nodes
A subagent node is a flexible block that changes how the agent behaves during a conversation. At this point, you can adjust the system prompt, switch the language model, or alter the voice settings. It also allows you to attach or remove tools and knowledge bases for that specific interaction.
For example, if a user starts asking technical questions, the workflow can switch to a subagent that uses a model trained for deeper reasoning. This way, the agent adapts without restarting the conversation.
Dispatch Tool Nodes
The dispatch tool node ensures a specific tool or function is called within the workflow. It can handle two outcomes: one when the tool call succeeds and another when it fails. This control helps the conversation stay smooth even if something goes wrong in the background.
For instance, if a weather API fails to respond, the workflow can redirect to a backup node that explains the issue politely or asks the user to try again later.
Agent Transfer Nodes
Sometimes, a conversation needs to move from one agent to another. The agent transfer node is built for this handover. You might use it when a general assistant must pass the chat to a more specialized agent, such as one trained for billing or customer service. This keeps communication consistent while ensuring users reach the right expert.
Transfer to Number Nodes
This node connects the conversation to a real person through a phone system. It is useful in customer support or sales where live human contact may be necessary. Once triggered, it redirects the user from the AI flow to a human representative, closing the gap between automated and personal help.
End Node
Every conversation needs a clear ending. The end node does this by closing the workflow politely and signaling that no further steps follow. It helps prevent the agent from looping or continuing unnecessarily after its task is done.
Edges and Flow Control
Edges are the lines that connect the nodes and define how one part of the conversation leads to another. Some edges follow a simple path, while others depend on certain conditions. For example, an edge might trigger only if a tool succeeds, or it may loop back if a question needs to be asked again.
By combining different edge types, creators can design realistic, branching conversations that react to user input instead of following a single fixed script.
Conclusion
Agent Workflows give developers and creators full creative control over how AI agents think, act, and respond. They make it possible to change voice, reasoning style, or even the model mid-conversation. They also make error handling and user routing far more natural, ensuring every interaction feels intentional and responsive.
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