Build a research agent and writing workflow connected through MCP in 7 free lessons from the course.
Built for: Software Engineers · Developers · Data Engineers · AI/ML Enthusiasts
You'll build on a working prototype of the multi-agent system built across the full course: a research agent and writing workflow connected through MCP.
This is a lightweight version designed to show you how the pieces fit together before you build them from scratch.
📩 Want to take this system to production? We'll send you exactly how, watch your inbox and spam.
Full lessons with code you can run: from building your first agent prototypes to the foundational techniques that power every production system.
Context engineering, structured outputs, tool calling, chaining, and routing, each built from scratch, which you can reference, reuse, and build on.
A lightweight research agent and writing workflow you can run, inspect, and experiment with. These are starter versions of the production systems you'll build in the full course.
The full course takes you from prototype to production in 35 lessons. You will build production systems from scratch with LangGraph, ReAct, RAG, persistent memory, multi-agent orchestration, calibrated evals, observability, and GCP cloud deployment, and walk out with what AI engineering roles are hiring for: the skills to ship AI systems and the portfolio to prove it.
