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.

Enterprise Observability with Fleet Tutorial | 2026 Production Infrastructure

[ ABORT TO HUD ]

SEQ. 1

SEQ. 2

SEQ. 3

Enterprise Observability with Fleet

🏢 2026 Production Infrastructure⏱ 12 min⭐ 100 BASE XP⌨ HANDS-ON LAB

LangSmith Fleet & Polly

Building an agent is easy. Managing 10,000 parallel agent sessions in production is hard. LangSmith Fleet is the industry standard for agent fleet management in 2026.

Fleet Management

Fleet provides a command center to monitor all active agents. You can:

View real-time state transitions of every active graph.
Interrupt long-running agents that are stuck in infinite loops.
Inject "Human-in-the-Loop" approvals directly from the dashboard.

AI-Assisted Debugging (Polly)

Polly is an AI-powered debugging assistant built into LangSmith. When an agent fails, Polly analyzes the execution trace, identifies the exact node where the context was lost or the tool schema failed, and proposes a fix for your graph logic.

💡 Key Insight: Enterprise SLAs require absolute visibility. You cannot deploy agents to production without tracing their thoughts, tool calls, and LLM latency. LangSmith Fleet is non-negotiable for enterprise deployments.

⌨ HANDS-ON LABMonitor Multi-Agent Fleet Health & Token Metrics

⭐ +150 XP

Query fleet telemetry aggregator to inspect active worker agent status, error rates, and token burn across 50 autonomous workers.

1Query fleet health metrics endpoint.

lab-sandbox — simulated environment

INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$

OBJECTIVE 1 / 1 — type "hint" if stuck

SYNAPSE VERIFICATION

QUERY 1 // 1

What role does Polly play in the LangSmith ecosystem?

It is a new LLM

It is an AI-powered debugging assistant that analyzes execution traces to identify failures

It writes code automatically

It manages billing