91–93 of 93 posts
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…
What job is the agent performing?
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…
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…
The only software that we use is Langfuse for observability and that too was breaking down for us. But they launched a new version - V3 - which might still work out for us.
I would suggest to just use standard non-AI specific python libraries and build your own systems. If you are migrating from N8N to a self hosted system then you can actually use NonBioS to build it out for you directly. If you join our discord channels, we can get an engineer to help you out also.
Earlier quoted context omitted.
Having built several systems serving massive user bases with LLMs. I think the ability to swap out APIs just isn't the bottleneck.. like ever. It is always the behavioral issues or capability differences between models. The frameworks just usually add more complexity, obscurity, and API misalignment. Now the equation can change IF you are getting a lot of observability, experimentation, etc. I think we are just reach…
> I think the ability to swap out APIs just isn't the bottleneck.. like ever It's a massive pain in the arse for testing though. Checking which out of X number of things performs the best for your use case is quite annoying if you have to have X implementations. Having one set that you swap out keys and some vars makes this massively easier.