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Ask HN: What are some actual use cases of AI Agents right now?

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Re: Ask HN: What are some actual use cases of AI Agents right now?

#51

Post by chenxi9649 »

mise_en_place wrote: post #49

The only one I've found useful so far is a documentation agent, similar to what langchain has in their docs. It is useful to be able to interface with an agent, instead of having to scour the man-pages and find the relevant information.

Looping back to what the other person was talking about -> "Areas where slightly lower accuracy is acceptable."

Seems like information retrieval of any sorts is one use case where the cost of being wrong is not super high. I guess that's why ChatGPT took off lol.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#52

Post by Aerbil313 »

chenxi9649 wrote: post #43
PheonixPharts wrote: post #37

> I'd love to know what are some of the hidden challenges to making a useful product with agents? One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI". The biggest thing any ML practitioner realizes when they step out of a research setting is that…

Yea that's a good point. Now I am curious, what are some tasks that can accept a model that is at 80% as good as a human, but is 100x cheaper?(or, 100x faster?)

A ton of tasks. Call centers to start with (they already do[1]), with human fallback.

1: In my country, after ChatGPT launched last year, when you call customer support you are now prompted to “just say in a few words” what you want instead of going through tap-this-number menus (they exist as a fallback) and I believe the backend is an LLM. The user flow and voice recordings are still programmatically determined though, but I can easily see one streamlined model calling APIs and whatnot, handling it all.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#53

Post by thoughtlede »

Answering to your second part of the question about hidden challenges:

If you are using AI agents to automate a workflow [1] execution, then the question to ask is where is non-determinism in the workflow. As in, where do humans scratch their head as opposed to rely on deterministic computations.

It turns out, a lot of times, as humans, we scratch our head just once for a given kind of objectives to come with a plan. Once we devise a plan, we execute the same plan over and over again without much difficulty.

This inherent pattern in how humans solve problems sort of diminishes the value of AI agents because even in the best case scenario the agents would only be solving a one-time, front-loaded pain. The value add would have been immense if the pain has been recurrent for a given objective.

That is not to say there is no role for AI agents. We are trying to infuse AI agents into an environment where we as humans adapted pretty well. AI agents will have to create newer objectives and goals that we humans have not realized. Finding that uncharted territory, or blue ocean, is where the opportunity is.

[1] By 'workflow' I mean a series of steps to take in order to achieve an overall objective.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#54

Post by furyofantares »

furyofantares wrote: post #41

Agents are possible basically because the input to the LLM and the output of the LLM are both text. The loop is trivially closed. But they're universally garbage because they require the LLM to do a lot of things that LLMs are completely incompetent at. It's just way too early to expect to be able to remove that work and have it be done by an LLM. The fact is LLMs are useful because they easily do some work that you'…

I just looked up a similar comment I made ~9 months ago, where I also said I thought we could probably do better than 1-to-1 prompt-to-output iteration even if we can't close the loop, and was hopeful that plugins would help compress the iteration.

Looking again at it from that direction - think about plugins, functions, GPTs, custom instructions, and now memory. These are all attempts to get more out of the LLM.

And they haven't really made much progress. Certainly less than I expected 9 months ago when I was hopeful the iteration loop would get compressed, even if I was highly skeptical about closing it. This is pretty conclusive to me - if it's this hard to get much more value per prompt out of current LLMs then it's really unlikely to be able to usefully close any loops.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#55

Post by chenxi9649 »

deathmonger5000 wrote: post #26

I taught https://github.com/KillianLucas/open-interpreter how to use https://github.com/ferrislucas/promptr Then I asked it to add a test suite to a rails side project. It created missing factories, corrected a broken test database configuration, and wrote tests for the classes and controllers that I asked it to. I didn't have to get involved with mundane details. I did have to intervene here and there, but not much.…

This is pretty cool!

Another use case where the cost of being slightly worse than a human is totally fine.(coming from someone that doesn't write tests lol)

I'd love to learn in more detail how it created those factories, corrected broken test database. It _feels_ that some of these tasks require knowing different parts of the codebase decently well, which from my experience hasn't always been the strong suite for AI assisted coding.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#58

Post by CharlieDigital »

dongecko wrote: post #27

The company I work for has tons of documentation and regulations for several areas. In some areas the documents are well over a thousand and for the ease of use of these documents we build RAG based chat bots. This is why I have been playing with RAG systems on the scale of "build completely from scratch" to "connect the services in Azure". The retrieval part of a RAG is vital for good/reliable answers and if you bui…

> You can also build a network of agents

My experience has been that they are far too unpredictable to be of use.

In my testing with agent networks, it was a challenge to force it to provide a response, even if it was imperfect. So if there's a "reviewer" in the pool, it seemed to cause the cycle to keep going with no clear way of forcing it to break out.

3.5 actually worked better than 4 because it ran out of context sooner.

I am certain that I could have tuned it to get it to work, but at the end of the day, it felt like it was easier and more deterministic to do a few steps of old-fashioned data processing and then handing the data to the LLM.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#59

Post by chenxi9649 »

simonw wrote: post #24

Which definition of agents are you interested in? I'm pretty convinced at this point that the term "agents" is almost useless, because so many people are carrying entirely different mental models of what the term means - so it invites conversations where no-one is actually talking about the same exact idea.

Good point, I should've defined this a bit more clearly in the post.

Honestly, I'm not toooo sure how to segment the term "agents", but in my mind there seems to be one realm for retrieval assistance. Ie. how do we make the ChatGPT-ish experience better. How can I better extract information I need from the collective human knowledge base. And another realm for letting the agent do things so I don't have to do it. Ie. "how can I get an Upwork assistant/Chief of staff/freelancer for cheaper and faster".

Nevertheless, editing the post now would simply create more confusion. Hopefully this discussion at least invites conversation about the conversation on agents itself haha.

Re: Ask HN: What are some actual use cases of AI Agents right now?

#60

Post by a_wild_dandan »

nicksrose7224 wrote: post #31
a_wild_dandan wrote: post #29

A few personal uses: 1. Find, annotate, aggregate, organize, summarize, etc all of my knowledge from notes 2. A Google substitute with direct answers in place of SEO junktext and countless ads 3. Writing boilerplate code, especially in unfamiliar languages 4. Dynamic, general, richly nuanced multimodal content moderation without the human labor bill 5. As an extremely effective personal tutor for learning nearly anyt…

This sounds compelling but where i always get stuck is on trust of what the LLM / agent spits back out. Every time I've tried to use it for one of the above use cases you mentioned and then actually dug into the sources it may or may not mention, it's almost always highly imprecise, missing really important details, or straight up completely lying or hallucinating. how do you get around this issue? Granted on (3), yo…

Frame your question in human terms. LLM -> employee, hallucination -> false belief, etc. Same hiring problems. Same solutions.

You have a problem. The candidate must reliably solve it. What are their skills, general aptitudes, and observed reliability for this problem? Set them up to succeed, but move on if you distrust them to meet the role’s responsibility. We are all flawed, and that’s the nature of uncertainty when working with others.

Past that, there’s little situational advice that one can give about a general intelligence. If you want specific advice, give your specific attempt at a solution!

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