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Ask HN: Examples of agentic LLM systems in production?

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Re: Ask HN: Examples of agentic LLM systems in production?

#21

Post by furyofantares »

If you are looking for LLM agents that go off and do a bunch of work on their own, you will be supremely underwhelmed. Anyone who went straight to building agents without a human in some large loop found that they were trying to make the LLM do things it was extremely bad at.

The right approach to build toward agents is to start with something that gives pretty good responses to prompts and build up an agentic mode to let it do more and more in response to each prompt. It should be thought of as extending how much you get per prompt, and doing so by chaining together components you've already worked at making to good at.

Cursor (the LLM powered VS Code fork) has an agentic mode and they are doing this the right way. The normal chat window is good at producing changes to your code, and at applying them, at looking at lints, at suggesting terminal commands, at doing directory listings or RAG on your codebase. Agentic mode is tying those together to do more of the work you want with fewer prompts from you.

Re: Ask HN: Examples of agentic LLM systems in production?

#23

Post by s-macke »

The term "agent" is quite broad. In my definition, an LLM becomes an agent when it utilizes the tool usage option.

ChatGPT is a good example: you ask for an image, and you receive one; you ask for a web search, and the chatbot provides an answer based on that search.

In both cases, the chatbot has the ability to rewrite your query for that tool and is even able to call the tools multiple times based on the previous result.

Re: Ask HN: Examples of agentic LLM systems in production?

#24

Post by wpietri »

SebaSeba wrote: post #4
klntsky wrote: post #2

Support bots. Scrapers. Personal assistants. Search startups like perplexity. Scammer bots. Bots that spread political agenda. "AI" memecoins.

When does a LLM customer support bot that is based for example on RAG architecture, become an LLM agent?

My take is that if the LLM outputs text for humans to read, that's not an agent. If it's making API calls and doing things with the results, that's an agent. But given the way "AI" has stretched to become the new "radium" [1], I'm sure "agent" will shortly become almost meaningless.

[1] https://en.wikipedia.org/wiki/Radium_fad

Re: Ask HN: Examples of agentic LLM systems in production?

#26

Post by wpietri »

frgtpsswrdlame wrote: post #17
bwfan123 wrote: post #14

Earlier quoted context omitted.

there are workflows where the outputs are "narratives" - an example is customer support. another example is summarization of text. characteristic of these use cases is that there is no one right answer. in these use cases agents fit in well. issue however, is that the agents cannot be chained. ie, chaining requires deterministic outputs and not narratives.

>characteristic of these use cases is that there is no one right answer I think what you mean is that they work best in cases where it's very hard to measure how well they are working.

And where it's also hard to tell who is doing the work! I'm reminded here of psychics and cold readers. They can easily convince people that they have great mental powers by outputting ambiguous text and letting the consumers of it do most of the work. You'll see similar effects with Meyers Briggs tests and other sorts of business astrology: some people feel like they get a lot of value out of them, but rigorous tests don't back that up.

Re: Ask HN: Examples of agentic LLM systems in production?

#28

Post by mistrial9 »

cloudking wrote: post #16

IMO "Agents" are a marketing term, they are simply software that use LLMs somewhere in the backend. Often daisy chained into a series of operations that may involve additional LLM calls or calls to other internal/external services. One we've been using for meeting notes + action items works quite well https://fireflies.ai

no "Agents" have a specific technical meaning.. an engine is connected to tools.. simple example is a bash terminal environment.

Re: Ask HN: Examples of agentic LLM systems in production?

#29

Post by isoprophlex »

An anecote that helps you maybe:

I do contracting work, we're building a text-to-sql automated business analyst. It's quite well-rounded: it tries to recover from errors, allows automatic creation of appropriate visualisations, has a generic "faq" component to help the user understand how to use the tool. The tool is available to some 10.000 b2b users.

It's just a bunch of prompts conditionally slapped together in a call graph.

The client needed AGENTIC AI, without specifying exactly what this meant. I spent two weeks pushing back on it, stating that if you replace the hardcoded call graph with something that has """free will""", accuracy and interpretability goes down whilst runtimes go up... but no, we must have agents.

So I did nothing, and called the current setup "constrained agentic ai". The result: High fives all around, everyone is happy

Make of that what you will... ai agents are at least 90% hype.

Re: Ask HN: Examples of agentic LLM systems in production?

#30

Post by simonw »

If we're going to have a conversation about agents or agentic it is really important we agree on which definition of those terms we are using for the purpose of this conversation.

If you ask two different people in the AI space to define "agent" you almost always get two slightly (or significantly) different definitions!

Here are just some of the definitions I've seen over time: https://news.ycombinator.com/item?id=42216217#42228364

For the purpose of this thread the most cynical definition, "LLMs that do something useful", might actually be the best fit!

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