An agent in Dialog is a specialized AI assistant with its own dedicated workspace, tool configuration, and personality. Each agent operates independently, maintaining its own memory and context across every interaction. Think of agents as team members you deploy for different jobs.
Agent architecture
Every agent you create gets its own persistent workspace environment — a dedicated runtime that persists across sessions. This workspace stores your agent’s identity files, saved content, research notes, task lists, databases, and custom skills.
An agent bundles four key components:
- Workspace — A persistent environment with up to 50MB of storage for files, notes, research, bookmarks, and databases
- Tool configuration — A customizable set of enabled data sources that determine what the agent can access (74+ tools available)
- Session history — A full record of every conversation, research chat, and follow-up
- Scheduled tasks — Any automated research, monitoring, or briefing jobs the agent runs on your behalf
These components work together to give each agent a distinct capability and growing knowledge base.
Named personas
Agents come with pre-configured personas optimized for different workflows:
- Chief of Staff — Strategic assistant for managing tasks, saving links, organizing research, and daily briefings
- Research Analyst — Deep-dive researcher for competitive intelligence, market analysis, and comprehensive reports
- Content Strategist — Content-focused assistant for ideation, drafting posts, and workshopping marketing copy
- Custom Agent — Build your own persona with a name and instructions tailored to your needs
Each persona shapes how the agent approaches tasks, structures its output, and communicates with you. See Agent Personas for details.
One default agent
Every Dialog account comes with a Default Agent that’s ready to use right away. This is the agent you interact with when you first sign in.
The Default Agent works like any other agent — it has its own workspace, tool configuration, and session history. The only difference is that it can’t be deleted. Think of it as your home base.
You can create additional agents whenever you need a specialized assistant for a different domain or workflow.
Agent isolation
Agents are fully independent from each other. They don’t share workspaces, session histories, tool configurations, or any other data.
This isolation is intentional. It means you can:
- Run a Chief of Staff for day-to-day operations and a Research Analyst for deep competitive dives without any bleed-through
- Give different agents access to different tools based on their purpose
- Keep research contexts completely separate across projects
If you need to share information between agents, you can reference findings from one agent in a conversation with another, or use connected apps to store findings in shared tools like Notion or Google Docs.
Deleting an agent permanently removes its workspace, session history, and all associated data. This action cannot be undone.
When to use multiple agents
| Scenario | Approach |
|---|
| One person, multiple workflows | Create agents for each major workflow (research, content, operations) |
| Different projects | One agent per project to keep contexts clean |
| Team members | Each person gets their own agent(s) with personalized workspaces |
| Experimentation | Spin up a new agent to test a workflow without affecting your main workspace |
Lazy provisioning
Agent workspaces are created on first interaction, not when the agent is initially set up. This keeps account creation fast and avoids allocating resources for agents you haven’t started using yet.
You can create up to 10 concurrent agents per account, and each one provisions its workspace independently when you first engage with it. 
