Lesson 1
What AI Agents Are
Learn the core definition, boundaries, and success criteria for practical AI agents.
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Build your first AI agent from scratch. Free, practical, no fluff.
AI Agent Fundamentals is a hands-on starter course for founders, operators, and builders who want useful automation without hype. Instead of abstract theory, you will design a real agent that can read context, decide next steps, call tools, and return reliable outputs. We start by clarifying what an agent is, where agents fail, and how to define success before you write a single prompt.
Across five focused lessons, you will build one working agent loop in TypeScript, add tools safely, structure lightweight memory, and apply practical guardrails to prevent bad actions. You will also learn how to test decisions, handle errors, and control token and cost budgets so your agent stays predictable under pressure. Every lesson includes concrete examples you can adapt to sales ops, customer support, content workflows, and internal automation.
By the end, you will have a deployable foundation, not another demo that breaks in production. If you have been stuck between simple chatbots and over-engineered frameworks, this course gives you the middle path: clear architecture, practical code, and fast wins you can ship this week.
You will leave with reusable prompts, tool schemas, and deployment checks so your next agent ships faster and performs better at launch.
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Lessons
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Lesson 1
Learn the core definition, boundaries, and success criteria for practical AI agents.
Lesson 2
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Build a reliable think-act-check loop with explicit state transitions.
Lesson 3
Ship a working TypeScript agent that classifies tasks and recommends next actions.
Lesson 4
Add tool contracts, lightweight memory, and safety checks without over-engineering.
Lesson 5
Move from local prototype to reliable production service with observability and limits.