Introduction
Multi-agent systems are becoming common in modern software delivery. Instead of one agent performing isolated tasks, teams deploy multiple agents-each responsible for work such as dependency updates, vulnerability remediation, refactoring, documentation improvements, or repository reporting.
As soon as more than one agent operates in the same repository, the core challenge shifts from "can an agent do the work?" to "can the system coordinate that work safely?" Without a clear orchestration model, agents can collide by changing the same files, opening overlapping pull requests, or repeatedly triggering workflows without convergence.
In GitHub, multi-agent coordination is achieved through visible, enforceable workflows. Pull requests define the boundary for proposed changes, branches isolate execution, GitHub Actions coordinates validation, and repository policies-such as required checks, required reviews, CODEOWNERS, and environments-ensure changes are reviewed and gated before they're accepted.
In this module, you'll learn how to design multi-agent systems that coordinate through GitHub-native artifacts, remain observable through logs and workflow outputs, and recover safely through retry, rollback, and human escalation.
Learning objectives
By the end of this module, you'll be able to:
Define agent responsibilities and scope boundaries within the SDLC
Coordinate multi-agent workflows using GitHub Actions events and orchestration patterns
Isolate agent execution using branches, workflows, permissions, and concurrency controls
Detect and resolve conflicts using GitHub-native validation and review mechanisms
Ensure observability, attribution, and traceability of agent actions
Diagnose failures and implement recovery strategies for reliable multi-agent systems