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Design an agent as a graph of nodes and edges with LangGraph — with persistence, branching and human-in-the-loop.
LangGraph treats agents as explicit graphs. State flows through nodes; edges decide where to go next. This is easier to reason about than a single mega-prompt.
The video shows how to pause execution, surface state to a human reviewer, and resume from the same checkpoint.
building AI agents: Enterprise adoption for Modern Teams explains the practical decisions, risks, metrics and rollout steps operators need to move from experiment to dependable production value.
A full walkthrough of building a working AI agent in n8n — from trigger to tool calls to memory — with the exact nodes and prompts.
How to design, instruct and deploy a Custom GPT with actions, knowledge files and a system prompt that survives real users.
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