Agent Teams — AI Glossary

Agent teams are multi-agent architectures where multiple AI agents work together on a shared task, each handling a specialized subtask in parallel or sequence. Instead of a single agent processing everything serially, agent teams decompose complex work into independent units — one agent researches, another writes code, a third runs tests — then coordinate their outputs into a unified result.

Why Agent Teams Matter

Large-scale engineering tasks often exceed what a single agent can handle efficiently within one context window. Agent teams solve this by distributing work across specialized sub-agents, each with its own focused context. This enables parallel execution — a refactoring agent can update module A while a test-generation agent writes coverage for module B simultaneously.

Claude Code implements agent teams natively: a primary agent spawns sub-agents for independent subtasks, each operating in its own context with access to the full codebase. This is particularly valuable for monorepo refactoring, multi-file migrations, and tasks where different parts of the work have no dependencies on each other. Our deep dive on Claude Code agent teams covers real-world usage patterns.

How Agent Teams Work

Agent teams follow a coordinator-worker pattern. A primary agentic process analyzes the task, identifies parallelizable subtasks, and spawns specialized sub-agents. Each sub-agent receives a focused prompt, operates within its own context window, and returns results to the coordinator.

Key mechanisms:

• Task decomposition: The coordinator breaks work into independent units that can run concurrently
• Isolated context: Each sub-agent gets its own context window, preventing context pollution from unrelated subtasks
• Result aggregation: The coordinator merges sub-agent outputs, resolving conflicts and ensuring consistency
• Skill specialization: Sub-agents can be configured with different instructions and capabilities, optimizing each for its specific role

Related Terms

• Agentic: The broader paradigm of AI systems that autonomously plan and execute multi-step tasks — agent teams extend this to multi-agent collaboration
• Claude Code: Anthropic's terminal-based coding agent that supports native agent team spawning for parallel task execution
• Claude: Anthropic's family of large language models that powers individual agents within a team

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