Terminology

Here are the key terms and concepts used throughout CoAgents:

Term	Definition
Agentic Copilot	An AI agent designed to collaborate with users in Agent-Native applications, rather than operate autonomously.
CoAgent	Terminology referring to CopilotKit's suite of tools for building agentic applications. Typically interchangeable with agentic copilot.
Agent State	The current data and context maintained by a Pydantic AI agent during its execution, including both internal state and data that can be synchronized with the frontend UI.
Agentic Generative UI	UI components that are dynamically generated and updated based on the agent's current state, providing users with visibility into what the agent is doing and building trust through transparency.
Ground Truth	In CoAgents, CopilotKit serves as the "ground truth" for the full chat session, maintaining the persistent chat history and ensuring conversational continuity across different agents.
Human-in-the-Loop (HITL)	A workflow pattern where human input or validation is required during agent execution, enabling quality control and oversight at critical decision points.
Intermediate State	The updates to agent state that occur during function execution, rather than only at flow transitions, enabling real-time feedback about the agent's progress.
Pydantic AI	The agent framework integrated with CopilotKit that provides the orchestration layer for CoAgents, enabling sophisticated multi-step reasoning and state management.
Agent Lock Mode	A mode where CopilotKit is configured to work exclusively with a specific agent, ensuring all requests stay within a single workflow graph for precise control.
Router Mode	A mode where CopilotKit dynamically routes requests between different agents and tools based on context and user input, enabling flexible multi-agent workflows.
State Streaming	The real-time synchronization of agent state between the backend and frontend, enabling immediate updates to the UI as the agent performs tasks.

These terms are referenced throughout the documentation and are essential for understanding how CoAgents work and how to implement them effectively in your applications.

Here are the key terms and concepts used throughout CoAgents:

Term	Definition
Agentic Copilot	An AI agent designed to collaborate with users in Agent-Native applications, rather than operate autonomously.
CoAgent	Terminology referring to CopilotKit's suite of tools for building agentic applications. Typically interchangeable with agentic copilot.
Agent State	The current data and context maintained by a Pydantic AI agent during its execution, including both internal state and data that can be synchronized with the frontend UI.
Agentic Generative UI	UI components that are dynamically generated and updated based on the agent's current state, providing users with visibility into what the agent is doing and building trust through transparency.
Ground Truth	In CoAgents, CopilotKit serves as the "ground truth" for the full chat session, maintaining the persistent chat history and ensuring conversational continuity across different agents.
Human-in-the-Loop (HITL)	A workflow pattern where human input or validation is required during agent execution, enabling quality control and oversight at critical decision points.
Intermediate State	The updates to agent state that occur during function execution, rather than only at flow transitions, enabling real-time feedback about the agent's progress.
Pydantic AI	The agent framework integrated with CopilotKit that provides the orchestration layer for CoAgents, enabling sophisticated multi-step reasoning and state management.
Agent Lock Mode	A mode where CopilotKit is configured to work exclusively with a specific agent, ensuring all requests stay within a single workflow graph for precise control.
Router Mode	A mode where CopilotKit dynamically routes requests between different agents and tools based on context and user input, enabling flexible multi-agent workflows.
State Streaming	The real-time synchronization of agent state between the backend and frontend, enabling immediate updates to the UI as the agent performs tasks.

These terms are referenced throughout the documentation and are essential for understanding how CoAgents work and how to implement them effectively in your applications.