Building with LangChain Deep Agents

You have already built this agent three times. LangChain Deep Agents is the one you keep rebuilding, made reusable. Building with LangChain Deep Agents turns the agent loop, the filesystem, the tools, and the guardrails into a library you configure instead of code you babysit.

Across thirteen parts it moves from the loop and the agent's filesystem to permissions, an undo button, on-demand skills, governance, long-running deployment, the silent failures that end a launch, and the five agent patterns everyone cites with the code that actually is each one.

Start at Part 1, or jump to any part below.

The parts

1. You've Already Built This Agent Three Times. LangChain Deep Agents Is the One You Keep Rebuilding.
2. The Agent Loop Is Just a While Loop You Did Not Have to Write
3. Your AI Agent Is Not Frozen. It Just Cannot Tell You It Is Working.
4. Your Agent's Filesystem Is a Decision. Most People Make It by Accident.
5. You Gave Your Agent Hands. Now Give It a Leash.
6. The Refactor Broke Everything. Good Thing Your Agent Has an Undo Button.
7. Stop Stuffing Your System Prompt. Teach the Agent on Demand Instead.
8. Three Ways to Give Your Deep Agent New Powers, in the Order You Will Want Them
9. Stop Configuring Your AI Agent. Start Governing It.
10. You Cannot Deploy a Long-Running Graph Like a Lambda
11. The Silent Failure That Ends a Good Agent Launch
12. The Five Agent Patterns Everyone Cites, and the Code That Actually Is Each One
13. The Hardest Part of Building an AI Agent Is Not the Eighth Feature. It Is Keeping the First Seven Working.