Build Your Own AI Agent

AI agents are the next frontier in software — programs that don’t just respond to questions but reason, make decisions, take action, and run autonomously around the clock. This course teaches you to build them from scratch.

Over 4 weeks you’ll go from understanding what an agent actually is (not the buzzword version — the real architectural definition) to deploying production-grade agent systems that handle real email, monitor live data, search knowledge bases, and orchestrate multiple AI models working together. Every concept is taught with working code, real API calls, and practical exercises you run on your own machine.

By the time you finish, you’ll have built a complete email handling agent, a data monitoring and alerting agent, a RAG-powered knowledge assistant, and a multi-agent orchestration system — all deployed and running on real infrastructure. You’ll also walk away with a deep understanding of how every major agent framework (LangChain, AutoGen, Anthropic Agent SDK) works under the hood, because you’ll have built the equivalent yourself first.

This course doesn’t pad the content. Every lesson earns its place.

Who It’s For

This course is for **developers and technical builders** who want to move beyond using AI tools to actually building AI systems. You don’t need to be an expert — entry-level programmers who know basic Python and have called an API once or twice will be able to follow along. By the end, you’ll be operating at an advanced level in AI engineering.

It’s also a perfect fit for:

- Developers who want to add autonomous agent capabilities to their existing products
- Business owners with a technical background who want AI working for them 24/7
- Engineers who’ve used AI frameworks but want to understand what’s actually happening inside them
- Students who completed *Build AI Into Your Website* and want to go much deeper into autonomous systems

Key Skills Taught

- The agent loop: perceive, reason, act, observe — implemented in pure Python
- Tool use and function calling with the Anthropic API
- Building a complete ReAct agent from scratch (no frameworks required)
- Short-term and long-term agent memory: SQLite sessions + vector embeddings
- Retrieval-Augmented Generation (RAG): chunking, embedding, and semantic search
- Error handling, retry logic, circuit breakers, and infinite loop detection
- Multi-step planning, task decomposition, and self-reflection loops
- Multi-agent orchestration: orchestrator + specialist worker patterns
- The Anthropic Agent SDK: streaming, prompt caching, and computer use
- Security and guardrails: prompt injection defense, input validation, human-in-the-loop approval
- Structured logging, metrics collection, and automated cost alerting
- Deploying agents to a live server: gunicorn, nginx, systemd, HTTPS with Let’s Encrypt
- Building a complete production email triage and response agent
- Building a data monitoring and autonomous remediation agent