Multi-Agent AI Systems & the A2A Protocol

Design and build cooperative multi-agent systems using Google's Agent-to-Agent protocol, LangGraph, CrewAI, AutoGen, and the Claude Agent SDK

Course Format and Delivery

Delivery Method: LiveOnline
Schedule: [text here]

All sessions are delivered live by an expert instructor in a fully interactive online environment.

*20% off for group bookings when booking 3 or more attendees from the same organization on the same course dates in the same transaction.

About this course

Single agents hit a ceiling. The real power — and the real complexity — comes from multiple specialized agents working together. 57% of organizations already deploy multi-step agent workflows, 16% have cross-functional agents, and 81% plan expansion. Google's A2A (Agent to-Agent) protocol, now at v1.0 with 150+ organizations under Linux Foundation stewardship and production deployments at Microsoft, Salesforce, and ServiceNow, standardizes how agents discover each other via Agent Cards, negotiate task delegation via JSON-RPC 2.0/gRPC, and exchange structured results with multi-modal payloads. MCP defines agent-to tool communication; A2A defines agent-to-agent communication — together they form the complete interoperability stack.

This full-day workshop teaches participants to design, build, and orchestrate multi-agent systems. They'll work hands-on with the four leading frameworks — LangGraph (126K+ stars, graph-based orchestration), CrewAI (44,300+ stars, 5.2M monthly downloads, role-based crews), AutoGen/Microsoft Agent Framework 1.0 (conversational GroupChat + A2A native support), and Google ADK (8,200+ stars, SDKs in Python/TypeScript/Java/Go) — and connect agents across frameworks using A2A for true cross-platform interoperability. Participants build three progressively complex multi-agent systems, culminating in a heterogeneous A2A connected agent network.

Topics Covered

Multi-agent architecture patterns (supervisor, hierarchical, collaborative, competitive, swarm);
Google A2A protocol (Agent Cards, task lifecycle, JSON-RPC/gRPC transport, capability discovery, signed cards, multi-tenancy);
LangGraph subgraphs and multi-agent patterns;
CrewAI role-based crews with process types;
AutoGen/MS Agent Framework conversational GroupChat;
Google ADK multi-agent orchestration; cross-framework interoperability via A2A;
Agent communication patterns (delegation, negotiation, consensus, escalation);
and production concerns (budget enforcement, deadlock prevention, observability). Approximately 35% lecture, 65% hands-on labs.

Brent Laster

Facilitator

Brent Laster is a global trainer, author, speaker, and founder/president of Tech Skills Transformations LLC. He helps enterprise teams adopt modern software practices in AI engineering, AI-assisted development, DevOps, automation, and secure software delivery. He is the author of Learning GitHub Copilot, Learning GitHub Actions, Professional Git, and Jenkins 2: Up and Running, as well as multiple online and live training programs for companies such as O'Reilly. In addition to AI expertise, Brent brings more than 25 years of experience in software development, management and technical leadership, DevOps, release engineering, and open-source technologies. He regularly presents and conducts workshops at industry conferences and for private clients.