Design, deploy, and monitor complex AI agents at scale.
3 months ago
LangGraph solved the biggest problem with agentic workflows: controlling the flow. Building agents as a state machine (a graph) makes them so much more predictable and debuggable than the old ReAct agent loops. The integration with LangSmith for visualization is perfect. This is the future of building complex LLM systems.
4 months ago
Defining all the nodes and edges for your graph can feel a bit verbose compared to a simple LangChain chain. But that explicitness is what gives you the power. When an agent gets into a loop, you can see exactly where it's happening in the graph. It's a worthwhile trade-off for any production application.
9 months ago
We were struggling to take our prototype agent to production because it was too unpredictable. LangGraph gave us the framework to add retries, fallbacks, and explicit state management that we needed for a reliable system. The cloud version handles all the scaling and observability for us. It's a fantastic product.
