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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 Fra

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.

barrenko 1y ago
The event horizon of current AI space has been quite a thing to observe.
weego 1y ago
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.
- suninsight 1y ago
  Most of our stuff is built in house actually, simply because everything else is still kind of catching up. You can find a bunch of information on the blog (https://www.nonbios.ai/blog https://www.nonbios.ai/blog) 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.
gwd 1y ago
It sounds like you're agreeing with the article? From TFA: > Over the past year, we've worked with dozens of teams building large language model (LLM) agents across industries. Consistently, the most successful implementations weren't using complex frameworks or specialized libraries. Instead, they were building with simple, composable patterns. > ...There are many frameworks that make agentic systems easier to implement. ...These frameworks make it easy to get started by simplifying standard low-level tasks like calling LLMs, defining and parsing tools, and chaining calls together. However, they often create extra layers of abstraction that can obscure the underlying prompts and responses, making them harder to debug. They can also make it tempting to add complexity when a simpler setup would suffice. We suggest that developers start by using LLM APIs directly: many patterns can be implemented in a few lines of code.
i_love_retros 1y ago
What job is the agent performing?
- suninsight 1y ago
  It is AI Software Dev called NonBioS.ai

barrenko 1y ago

The event horizon of current AI space has been quite a thing to observe.

weego 1y ago

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.

suninsight 1y ago
Most of our stuff is built in house actually, simply because everything else is still kind of catching up. You can find a bunch of information on the blog (https://www.nonbios.ai/blog https://www.nonbios.ai/blog) 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.

gwd 1y ago

It sounds like you're agreeing with the article? From TFA: > Over the past year, we've worked with dozens of teams building large language model (LLM) agents across industries. Consistently, the most successful implementations weren't using complex frameworks or specialized libraries. Instead, they were building with simple, composable patterns. > ...There are many frameworks that make agentic systems easier to implement. ...These frameworks make it easy to get started by simplifying standard low-level tasks like calling LLMs, defining and parsing tools, and chaining calls together. However, they often create extra layers of abstraction that can obscure the underlying prompts and responses, making them harder to debug. They can also make it tempting to add complexity when a simpler setup would suffice. We suggest that developers start by using LLM APIs directly: many patterns can be implemented in a few lines of code.

i_love_retros 1y ago

What job is the agent performing?

suninsight 1y ago
It is AI Software Dev called NonBioS.ai