Is the AI Agents Academy completely free?

Yes, 100% free. No sign-up, no credit card. All 13 modules, 58 lessons, 9 terminal labs, and 115 quiz questions are accessible immediately. Your progress saves locally in your browser.

How is Infinity AI Agents Academy different from vendor-locked agent courses?

Unlike single-framework platforms (such as LangChain Academy or CrewAI University) that tie you to a single proprietary ecosystem, Infinity Tech Stack's AI Agents Academy is a 100% free, vendor-neutral engineering curriculum. It teaches the complete production stack across ReAct loops, LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, A2A protocol, and Model Context Protocol (MCP) integration with in-browser terminal labs and zero sign-up required.

What topics does the AI Agents Academy cover?

The course covers agent fundamentals, ReAct loops, Plan-and-Solve, tool use & function calling, MCP integration, Agentic RAG, multi-agent systems (CrewAI, LangGraph), A2A protocol, Google ADK, agent memory, safety & guardrails, red teaming, CI/CD for agents, and production observability.

What is the A2A protocol?

A2A (Agent-to-Agent) is Google's open protocol for enabling interoperability between AI agents. It allows agents from different vendors and frameworks to discover each other, exchange capabilities via Agent Cards, and delegate tasks securely.

Google ADK (Agent Development Kit) is an open-source framework for building, orchestrating, and deploying AI agents. It supports Python, Go, Java, and TypeScript, and integrates with MCP for tools and A2A for agent-to-agent communication.

Do I need any prerequisites?

Basic programming knowledge is helpful but not required. The course starts from absolute fundamentals (what is an agent?) and progressively advances to expert-level topics like multi-agent orchestration and production safety.

Does the AI Agents Academy include hands-on labs?

Yes. Hands-on terminal labs are built into the lessons - build the minimal agent loop, scaffold a CrewAI crew, and launch LangGraph dev using real, vendor-verified commands, with objectives, hints, solutions, and XP rewards. No sign-up or setup needed.

Swarm Architectures Tutorial | Multi-Agent Systems

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Swarm Architectures

👥 Multi-Agent Systems⏱ 10 min⭐ 80 BASE XP⌨ HANDS-ON LAB

Why Multiple Agents?

A single prompt fails at complex tasks. By breaking a problem down and assigning specialized "personas" with specific tools to different agents, you get much higher quality results.

Common Topologies

Orchestrator-Worker: A manager agent breaks down the task and delegates to worker agents (e.g., Coder, Tester, Reviewer).
Pipeline: Agent A’s output goes directly into Agent B (Research → Write → Edit).
Debate: Two agents with opposite prompts argue a point, and a Judge agent synthesizes the result.

⌨ HANDS-ON LABSpawn Swarm Multi-Agent Cluster

⭐ +150 XP

Launch an autonomous swarm orchestrator with worker delegation rules and communication channels.

1Initialize an OpenAI Swarm or AutoGen multi-agent orchestrator team.

lab-sandbox — simulated environment

INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
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OBJECTIVE 1 / 1 — type "hint" if stuck

SYNAPSE VERIFICATION

QUERY 1 // 1

Which multi-agent topology uses one central agent to delegate tasks to specialized workers?

Pipeline

Debate

Orchestrator-Worker

Random Swarm