LangGraph for AI Agents: State, Tools & Human-in-the-Loop

This course contains the use of artificial intelligence.

LangGraph is the runtime underneath a lot of the agent code being written right now, and most material about it starts in the middle. You get a working snippet, a diagram with four boxes, and no answer to the question you actually have: what is in the state after that node ran, and why did the field I was collecting into come back with one item instead of three.

This course answers that question first and keeps answering it.

Six modules build one frame and then spend the largest module on a single agent. You see the graph a team sketched before writing anything, the first version with four nodes and one conditional edge, the version where notes started disappearing, the one line that fixed it, the approval gate that stopped a four-figure order from going out unseen, the day the process died mid-run and the thread resumed, and the three things that changed before it shipped. Six versions, in order, each one a reaction to something that went wrong in the last.

Nothing here needs installing. There is no key to get, no database to run and no account to open. Code arrives as slices of eight lines or fewer with a note on the lines that matter, and every output on screen is the text that really printed when the example was run. The practice lessons are one or two minutes of thinking, answered in your chair, with the model answer shown immediately whether you worked it out or not.

What you get from that is the ability to read somebody else's graph and say what it does, to name the part that is broken when a field will not hold its contents, and to know which of the four layers of this stack a given problem belongs to. What you do not get is a deployed application, because building one is a different course and this one says so.

The last module is unusually honest for a course. One lesson is entirely about when LangGraph is the wrong tool, with four cases where a plain loop or a ready-made harness is the better answer. Another names six subjects this course skipped and where to go for each. A course that only tells you when its subject fits has taught you half of the decision.

Two companies run through the course. A parts distributor triaging supplier back-order emails carries modules one through five. A college checking admission documents appears in module six to show the same shape failing differently. Both are composite cases, assembled from documented patterns, and the course states that on screen rather than claiming a postmortem nobody published.

Every module ends with a memo you keep: the terms in plain words, the diagrams worth saving, and a one-line cheat sheet. The last module adds a combined memo with every term in the course, a vocabulary for the words you will hear in meetings and job adverts, and a sheet on reading adverts and interview questions about this subject.

Covers LangGraph 1.x, including the move from the old prebuilt agent to the current one and the middleware model that came with it.