Agent Engineering
Multi-Agent Collaboration: When One Agent Isn't Enough, Deploy a Team
Main Agent breaks tasks → Sub-Agents each handle their specialty → Aggregate and deliver. Read-only tasks run in parallel for speed; write tasks run in series for safety.
Scenario · Agent Team
User Instruction
"Help me refactor the user authentication module in this project"
Main Agent · Coordinator
🔍 Researcher
💻 Developer
🧪 Tester
ResearcherRead-only
Analyze the current auth module's code structure and dependencies
read_filesearch_filesgrep
Unassigned
DeveloperRead-write
Rewrite the auth middleware to use JWT
read_fileedit_filerun_command
Unassigned
TesterRead + Run
Write and run unit tests for the auth module
read_fileedit_filerun_command
Unassigned
Core Concepts
Analogy
Single Agent = one person doing everything
Multi-Agent = a team, each with their specialty
Single Agent = one person doing everything
Multi-Agent = a team, each with their specialty
Technical Principle
Sub-Agents run in isolated Worker Threads
Memory is isolated—no interference
Parent can terminate children at any time
Sub-Agents run in isolated Worker Threads
Memory is isolated—no interference
Parent can terminate children at any time
Event Communication
subagent_start → sub-Agent launched
subagent_chunk → streaming in progress
subagent_end → sub-Agent complete
subagent_start → sub-Agent launched
subagent_chunk → streaming in progress
subagent_end → sub-Agent complete
Execution Flow
Product Decisions
Takeaway Complex tasks don't rely on a single Agent grinding through everything—they're broken into specialized sub-Agents: a Researcher reads code, a Developer changes code, a Tester validates. Read-only tasks parallelize for speed; write tasks serialize for safety. This is team collaboration in the Agent world.