The Definitive Guide to Building AI Agents

Why this tutorial exists, the AI-Native mindset, and what you'll learn.

Build your first agent in 10 minutes, then understand what makes it tick.

Understanding the raw material: tokens, context windows, reasoning modes, and model limitations.

The art and science of programming models through natural language.

Taming non-determinism with JSON Schema, Pydantic, and constrained decoding.

Turning LLMs from text generators into decision makers that can execute code.

The universal standard for connecting AI agents to tools, data, and services.

Giving your agent access to external knowledge beyond the training data.

Building agents that remember across conversations and sessions.

LLMs that dynamically direct their own processes and tool usage.

Orchestrating LLMs through predefined code paths for predictable, consistent results.

Combining agents, workflows, and humans into production-ready systems.

Maximizing the signal-to-noise ratio in the context window.

Protecting against prompt injection, indirect attacks, and unintended agent behaviors.

Testing, debugging, and measuring what matters in probabilistic systems.

Versioning, gradual rollouts, cost guardrails, permissions, sandboxing, and model migration for production agents.

Building real-time voice and video agents that feel alive.

The protocol stack, frameworks, and infrastructure that power production AI agents.

Combine everything to build a personal assistant with tools, memory, and voice.