Is the AI Agents Academy completely free?

Yes, 100% free. No sign-up, no credit card. All 13 modules, 57 lessons, and 110 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.

What's the key architecture lesson from production coding agents?

Build a custom loop optimized for your specific use case — The best agents succeed with custom loops, no framework. Understand the core pattern, then build exactly what you need.

Case Study: Coding Agents Tutorial | Real-World Case Studies

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Case Study: Coding Agents

🎯 Real-World Case Studies⏱ 12 min⭐ 100 BASE XP

How Production Coding Agents Work

Coding agents like Claude Code are among the most capable agentic systems. Let's analyze their architecture.

Architecture Overview

Component	Implementation	Why
Core Model	Claude Sonnet w/ Extended Thinking	Best speed/cost/quality balance
Agent Loop	Custom loop (no framework)	Maximum control over execution
Memory	Compaction + project-level files	Persistent context across sessions
Tools	File read/write, bash, search	Full development workflow
Safety	Permission system, sandboxed bash	Prevent destructive actions

Key Design Decisions

Extended Thinking for Planning: Internal reasoning before multi-file edits reduces errors.
Tool Parallelism: Multiple file reads happen simultaneously per turn.
Compaction: Long sessions auto-summarized to prevent context overflow.
Persistent Memory: Project-specific files store conventions across sessions.

Lessons for Your Agents

Invest in permissions early - users need trust before granting access.
Compaction is essential for long-running tasks.
Project-level context files are simple but powerful persistent "memory."

💡 Key Insight: Top coding agents don't use frameworks. They're custom loops optimized for one use case. Frameworks are training wheels - once you understand the loop, build what you need.

SYNAPSE VERIFICATION

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What memory strategy do advanced coding agents use?

No memory

Conversation compaction + persistent project files

Fine-tuned model that remembers

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