Building Effective AI Agents

As someone who works for a company having a real Agent in production, (not a workflow), I cannot disagree more than the very first statement here: Use Agent Frameworks like Langraph. We did exactly that, and had to throw everything away just a month down the line. Then we built everything from scratch and now our system scales pretty well.

To be fair, I think there might be a space for using Agent Frameworks, but the Agent space is too early for a good enough framework to emerge. The semi contrarian though, which I hold to a certain extent, is that the Agent space is moving so fast that a good enough framework might NEVER emerge.

I'm just in the process of moving from a prototype in N8N's agent tools to an actual system that could be self-hosted.

I've read a lot of comments that most pragmatic shops have dumped langchain/graph, haystack, crew etc for their own internal code that does everything more simply, but I can't currently conceptualize how tooling etc is actually done in the real world.

Do you have any links or docs that you've used as a basis for the work you could share? Thanks.