AI Engineer

Get your environment running and ship your first AI-powered app.

Learn how code actually runs - variables, loops, functions, and scope.

Master lists, dicts, sets, and comprehensions - and know when to use each.

Understand classes, inheritance, and dunder methods so LangChain source code stops being a wall.

Read and write files, call real APIs, and handle errors gracefully - the 'I can do real things now' milestone.

Organise code into importable packages with pip, virtual environments, and proper project layout.

Containerize your work so it runs the same everywhere - a baseline skill for any backend or AI engineer.

Build your first agents using the LangChain framework - model calls, tools, and chains.

Upgrade to stateful, looping agents with LangGraph - the modern foundation for production AI systems.

Coordinate multiple specialised agents with the Agent SDK - supervisors, handoffs, and shared state.

Build long-horizon deep agents from first principles - planning, memory, and tool orchestration without a framework.

Learn the event-driven patterns that make AI systems reliable and scalable at production load.

Prove the full specialization by building RelayDesk: a durable local AI support copilot with safe tools, human approval, Ragas metrics, LangSmith experiments, and regression gates.