Building AI Agents with Claude: From Prompts to Production

Design, build, and deploy production AI agents with Claude

AI agents are moving from demos to production — and this course teaches you to build them properly with Anthropic's Claude. You'll go from understanding what an agent actually is to deploying agentic systems that use tools, retrieve knowledge, and coordinate with each other reliably.

You'll start with the fundamentals: the different types of agents and architectures, the Claude model family (Haiku, Sonnet, Opus), and the crucial judgment call of when a simple prompt beats a full agent.

What you'll master:

• Claude API fundamentals — the Anthropic SDK in Python and JavaScript, the Messages API, streaming, and token/cost management
• Prompt engineering — effective system prompts, few-shot and chain-of-thought, structured JSON output, and sampling tuning
• Tool use & function calling — defining tools with JSON Schema, handling tool_use blocks, and multi-step tool chains (you build a working calculator agent)
• RAG systems — embeddings and vector databases, chunking strategies, the retrieval pipeline, and generating grounded answers
• Multi-agent architectures — the orchestrator pattern, agent delegation and parallel execution, and the Model Context Protocol (MCP)
• Production deployment — rate limiting and error handling, cost optimization, observability, and safety guardrails

Who this is for: developers who know the basics and want to build real, reliable agentic systems rather than fragile prototypes. Each concept is applied in code, so you leave with patterns you can put straight into production.

By the end you'll be able to take an agent from a prompt on your screen to a monitored, guardrailed system running in production.