I’m interested in LangGraph because it seems the closest to an industry standard - every use case seems to be addressed with a tutorial (both first and third party) and there’s an ecosystem of already available graphs/agents. I’m aiming for both high extensibility (new use cases should be easily implementable) and high reliability. The LangGraph docs do a pretty good job at convincing me that they got the latter pretty nailed down. It seems like a hard enough problem to question a new solution on this.
I want to build a (highly reliable & controllable) UI for agents more than I want to build the agents themselves, so my hope is that LangGraph has the biggest ecosystem I can plug into.
They do have some funky lock-in attempts, for instance the LangGraph CLI, which acts as a server for their agent protocol (https://github.com/langchain-ai/agent-protocol), is proprietary. However (and this is what I consider indicative of a strong ecosystem) there’s a free reimplementation named Aegra: https://www.aegra.dev/