LangGraph makes agent workflows easier to reason about. You can see the nodes. You can see the edges. You can see where state is read, updated, and passed forward. That is a big improvement over a black-box agent loop. But it also exposes the question most agent pipelines eventually have to answer: Which parts of this graph are allowed to trust external content? A graph-based agent can read search results, PDFs, emails, tickets, web pages, tool outputs, and user-pasted text. Some of that content is useful evidence. Some of it may contain instructions that should never become part of the agent’s control flow. The problem is not only whether a user prompt is malicious. In a stateful graph, the real question is: Where does untrusted content enter the graph, can it get written into state, and can it later influence a tool node? That is where a stateful trust boundary helps. This post shows how to add that boundary to a LangGraph workflow with Omega Walls.…