Claude Code Agent Teams
Master parallel AI collaboration with agent teams. Learn to coordinate multiple Claude instances for complex debugging, code reviews, and cross-layer development.
Why take this course?
Unlock the power of parallel AI collaboration. When production is down and you need answers in minutes, not hours, agent teams let you investigate multiple hypotheses simultaneously. Learn to coordinate multiple Claude instances, implement competing hypotheses debugging, and orchestrate complex cross-layer development. From setup to advanced patterns, this course gives you the skills to leverage team-based AI for research, review, and development at scale.
Course Modules
Learning Goals
- Understand when and why to use agent teams vs single sessions or subagents
- Identify tasks that benefit from parallel exploration
- Distinguish between subagents and agent teams
Concept Card Preview
Visuals, diagrams, and micro-interactions you'll see in this module.
Agent Teams Introduction
This is a placeholder concept card for the Agent Teams course. Content will be added soon.
Learning Goals
- Understand the three-layer architecture of agent teams
- Learn how teammates share information through the mailbox system
- Know where team configuration and tasks are stored
- Understand context boundaries between lead and teammates
Learning Goals
- Configure display modes (in-process vs split panes)
- Create your first agent team with proper prompts
- Navigate between teammates and communicate effectively
- Understand task claiming and assignment
Learning Goals
- Master the competing hypotheses pattern for debugging
- Implement plan approval workflows for high-risk changes
- Use delegate mode for pure orchestration
- Apply quality gates with hooks
Learning Goals
- Understand token cost implications of agent teams
- Know the hard limitations and how to work around them
- Apply battle-tested best practices
- Properly clean up teams when finished