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home/pathways/building-ai-agents
IntermediateLearning Pathway

Building AI Agents

Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous — from your first agent loop to production-grade multi-agent systems.

11articles
~6htotal
Intermediate
Start Pathway Free →View All Pathways

What you'll learn

  • What loop engineering is and why it supersedes prompt engineering for agents
  • How to build an agent harness that makes AI behavior predictable
  • MCP (Model Context Protocol): the open protocol connecting agents to any tool
  • When to use RAG vs MCP for different context-augmentation scenarios
  • How embeddings and vector search work for agent memory
  • Top 10 agent loop patterns for production coding workflows

Curriculum — 11 articles

01

What Is Loop Engineering?

The new paradigm beyond prompt engineering — and why it matters.

8m read
02

What Is an Agent Harness?

The scaffolding layer that makes AI agents reliable in production.

10m read
03

How to Build Your First Agent Loop

Step-by-step guide to building a functional AI agent loop.

12m read
04

What Is MCP? Model Context Protocol Explained

The open protocol for connecting AI agents to any tool or service.

10m read
05

RAG vs MCP: Complete Guide to Context-Aware AI

When to use retrieval augmentation vs structured tool access.

10m read
06

What Are Embeddings? Vector Search Explained

The math behind semantic search and how agents use it.

10m read
07

Agent Markdown Files: SKILL.md, AGENT.md, CLAUDE.md

The files that give agents persistent identity and memory.

10m read
08

What Are Agent Skills?

Procedural memory for AI coding agents — complete guide.

8m read
09

Top 10 AI Agent Loops for Coding Workflows

Production-tested patterns for common agentic coding scenarios.

12m read
10

Agent Harness Engineering: When Scaffolding Wins

How LangChain jumped TerminalBench without changing the model.

10m read
11

The Agentic Era: How AI Agents Will Transform Everything

The big picture view from 2026 to 2030.

12m read

Start learning

Building AI Agents

Articles11
Time commitment~6h
LevelIntermediate
AccessFree
Start Pathway →

Free account. No credit card needed.

Who this is for

  • →Developers building autonomous AI systems and agents
  • →Engineers transitioning from chatbot-style AI to agentic AI
  • →Teams evaluating frameworks like LangChain, CrewAI, or custom harnesses
  • →Technical leads designing AI architecture for their organizations

After this pathway

Build your first working agent loop and understand the full architecture of production agent systems — from tool access and memory to multi-agent orchestration.

Frequently asked questions

What is an AI agent and how is it different from a chatbot?+

An AI agent is a system that can take autonomous actions — calling tools, reading files, running code, making web requests — to complete a task over multiple steps without continuous human guidance. A chatbot responds to single messages. An agent operates in a loop: observe, think, act, observe again, until the task is complete.

Do I need to use a specific framework to build AI agents?+

No. This pathway covers the principles of agent architecture — loops, harnesses, tool access, memory — that apply regardless of whether you use LangChain, CrewAI, a custom harness, or Claude Code's built-in agent capabilities. Framework knowledge becomes much easier to acquire once you understand the underlying patterns.

How long does the Building AI Agents pathway take?+

11 articles, approximately 6 hours. This is an intermediate pathway — completing AI Foundations and Prompt Engineering first will make it significantly more approachable.

Other pathways

AI Foundations

Beginner

Understand what AI actually is — tokens, transformers, agents, and the landscape. Start here if you're new.

10 articles · ~4h →

Prompt Engineering

Beginner

Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.

11 articles · ~5h →

Claude Code Mastery

Intermediate

Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.

13 articles · ~7h →

AI Tools by Role

Beginner

Practical AI adoption for your specific function — marketing, engineering, HR, finance, and more.

10 articles · ~4h →

AI Model Landscape

Intermediate

Navigate the crowded model market — Claude, GPT, Gemini, open-source — and understand the tradeoffs.

10 articles · ~6h →

Developer Fundamentals

Beginner

The technical foundations every AI builder needs — APIs, Git, Docker, Python, Next.js, and modern web.

10 articles · ~6h →