I will build a langgraph ai agent with real state, retries and error handling

Most "AI agents" are a prompt in a while-loop. They work in the demo, then hit a real user and hang, loop forever, or silently return nothing - because there is no state, no retry path, and no defined behaviour for failure.

I build agents as actual state machines. Every step is a node, every failure has an edge, and the graph can loop deliberately instead of by accident.

I built a corrective-RAG copilot this way: an LLM grades each retrieved chunk, and if grading kills the retrieval the graph loops back with a rewritten query rather than answering from what survived. A chain cannot express that cycle. That is the entire argument for building it as a graph.

Backend engineer by day - Spring Boot, Go and Kafka in production at a US investment bank and a US insurer - so what I hand you is a service with error handling, not a notebook.

WHAT I NEED FROM YOU

What the agent must do, what tools or APIs it calls, and what it should do when a step fails. If you do not know the last one yet, that is fine - deciding it is part of the work.