Build AI Systems

Turn what you learn into working AI architecture.

AI Chat Application

Learn the architecture behind a conversational AI product — the pattern nearly every other project in this section builds on.

RAG Application

Apply the RAG lessons to a working ingestion and retrieval architecture — from documents to a grounded answer.

AI Agent

Apply the agent lessons to a bounded, tool-using agent loop with retries, memory, and a human approval checkpoint.

MCP Application

Apply the MCP lessons to a client-server integration — discovering and calling tools through the protocol instead of custom code.

LLM Gateway

Apply the gateway lessons to a working routing, retry, fallback, and cost-tracking layer between applications and model providers.

Streaming AI Application

Apply the Streaming lesson to the full mechanics: time to first token, cancellation, backpressure, and mid-stream errors.

Production AI Application

The capstone project — see how the gateway, RAG, streaming, and engineering concerns from the other projects combine into one system.

Multi-Tenant AI System

Apply the multi-tenant architecture lessons to tenant isolation, quotas, and cost allocation on top of a shared AI system.

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