Agentic Workspace Overview
The Agentic Workspace is the section of your project where you build, test, and manage AI agents. It lives in the project sidebar under Agentic Workspace and contains three tabs: Agents, MAS Systems, and Agent Personas.
What you can build
Task Agent
A Task Agent is a graph-based workflow agent. You build it on a visual canvas by connecting nodes — each node performs one action (call an LLM, query a table, branch on a condition, etc.). Task Agents are deterministic: they follow the graph exactly as you wired it.
Use a Task Agent when you need a predictable, auditable pipeline — customer onboarding, data enrichment, approval workflows, RAG-powered Q&A.
AI Agent
An AI Agent is an LLM-driven agent that uses tool calling and autonomous planning. Instead of a fixed graph, you give it a goal, a set of tools, and policies. The LLM decides which tools to call and in what order.
Use an AI Agent when the problem is open-ended — research tasks, multi-step reasoning, complex information retrieval where the path isn’t known in advance.
MAS (Multi-Agent System)
A Multi-Agent System (MAS) puts two or more AI Agents behind one conversation, each acting as a specialist.
The orchestration pattern is the Conversation Router: a router classifies each incoming message and dispatches it to the best specialist agent, carrying the conversation across handoffs. Routing is decided from the member agents’ skills, so the quality of those skills is what makes a system accurate.
A MAS needs at least two AI Agents to be worth building — with a single member, the router simply forwards every message to it. See Multi-Agent System overview.
Agent Personas
A Persona defines the personality, tone, and behavior guidelines for an agent. You can assign a persona to any agent — it shapes how the agent communicates with users. Personas include instructions on voice, vocabulary, response length, and guardrails.
The agent lifecycle
Every agent follows the same lifecycle:
- Create — Pick a type (Task or AI), name it, define its goal.
- Build — For Task Agents: wire nodes on the canvas. For AI Agents: configure tools and policies.
- Test — Run the agent in a chat session. Inspect traces, replay, debug.
- Version — Save a snapshot. Compare versions. Promote to production.
- Deploy — Push to a Preview or Production environment.
- Monitor — Watch runs, costs, errors. Iterate.
Task Agent canvas at a glance
The Task Agent canvas is a full-screen visual graph editor (the Agent Builder). You drag nodes from the palette, connect them with edges, and configure each node via its settings panel.
Node palette categories
| Category | Nodes | Purpose |
|---|---|---|
| Flow Control | Start, End, Parallel, Merge | Entry/exit points, parallel branching |
| Actions | Agent Call, Tools Call, Quick Prompt | Sub-agent invocation, tool execution, LLM calls |
| Logic | Condition, Switch | Conditional branching and multi-way routing |
| Loops | Loop | Iterate over arrays or repeat until a condition |
| Data | Query Table, Insert Row, Update Row, Delete Row | CRUD operations on Data Vault tables |
| RAG | Search Content Store, Reindex Content Store | Vector search and re-indexing |
| Advanced | Code | Custom code execution |
The Start node defines the workflow entry point. Configure its Input Variables to pass data into the workflow from external callers.
What’s next
- Create a Task Agent → — Step-by-step creation wizard
- Canvas tour → — Toolbar, palette, inspector, run panel
- Node reference → — Detailed docs for every node type