What are AI agent teams? Build reusable specialist squads
A squad lets a company split a broad outcome across specialists. Each agent keeps a focused role, while squad membership defines which peers it can delegate to.
The concept
A plain-language definition before the product implementation.
A squad is a bounded peer network
A squad is not one larger prompt pretending to contain several jobs. It is a reusable group of separately configured agents. The active members become the delegation network, so the runtime can call the right specialist without making every agent in the workspace available.
How AI Agent uses it
Build squads that remain understandable
AI Agent squads are scoped to the company and resolve members by stable agent identity. Add or archive specialists without rewriting the supervisor's prompt, and keep each member's model, memory, skills, and tool access independent.
Focused specialists
Give research, analysis, writing, or operations to agents designed for that work.
Bounded delegation
Squad membership determines the peers an acting agent can reach.
Reusable squads
Use the same specialist group across chats and workflow-driven work.
From idea to a working system.
- 01
Create specialists
Build agents with narrow roles and the context they need.
- 02
Group the squad
Add active agents to a named squad for one business outcome.
- 03
Delegate
Let the acting agent route subtasks to its resolved squad peers.
Split broad outcomes across clear specialists
Best for
Work that benefits from separately equipped research, analysis, writing, or operations specialists with bounded delegation.
Choose another pattern when
One agent can own the outcome with a focused role and tool set. A squad adds value only when the specialist boundaries are real.
Included in AI Agent
The product capabilities behind the idea.
- Reusable, company-scoped squads
- Stable identity-based peer resolution
- Archived squad and agent filtering
- Independent configuration per specialist
Frequently asked questions
Keep exploring
Related product guides
Agents
An agent is the reasoning layer: it understands a goal, decides which approved tools to use, and works toward an outcome. AI Agent gives that reasoning a clear operating contract instead of relying on one giant prompt.
Chat
Agent chat is the conversational control surface for real work. Ask a question, attach context, choose an agent and skills, then review the evidence, tool activity, and proposed changes in the same thread.
Workflows
A workflow turns a business process into an explicit graph. The model can reason inside an agent step, while the surrounding sequence keeps triggers, tools, branches, approvals, and outputs predictable.
Build the smallest useful version first.
Start with the agent and one real task. Add workflow control, context, and approvals when the work shows you where they matter.