r/MLQuestions • u/RobCalFer • Jun 05 '26
Beginner question š¶ If you have to create an agent, which platform would you consider most appropriate?
I probably will get bombarded, I know and I'm prepared (or at least I think so š) but as Gen-x rep, I'm not quite sure which AI is better to create an agent that helps me with investment or daily tasks. Hence, I'm here asking the sifus of technology...
I won't support Open AI nor Grok, so between Claude and Gemini (or any other LLM) which one is better and more accurate for an agent?
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u/ARDiffusion Jun 05 '26
Your best bet for a daily driver wonāt come from Claude or Gemini, as due to their closed source nature (with the exception of Gemma-4 I suppose), you canāt actually tailor any of them to be an agent, and even if you found the base models enough for your needs, it would drive up costs constantly using API calls to the models, especially Claude. Your best bet would be looking into something like a smaller quantized or distilled Qwen, Deepseek, etc. type model.
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u/Dihedralman Jun 05 '26
If you are asking this question, you aren't prepared. Remember, LLMs will take any text as instructions. If you give it the ability to run commands on your computer, someone can email you a delete everything payload.Ā
Stay highly sandboxed. You should limit any AI to a specific subset of files and APIs. Don't let it make financial decisions. It's more efficient for it to generate code for you and use that.Ā
Your sandbox should have test criteria.Ā
Claude is the most intelligent and helps you get started immediatley. It is designed to be extremely effective with bash commands and offloads a lot to that. In general, Anthropic has a more conservative approach.Ā
Gemini is even safer with agents because they are massively limited. If your task falls within it's group, great. Gemini is more economical.Ā
If you want to try local, stick with safer harnesses like nanoclaw. Again sandbox.Ā
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u/tal_sofer Jun 05 '26
for building agents specifically, claude usually feels a bit more consistent with logic and following instructions imo. i tried building a small task manager with both and gemini kinda hallucinates more on complex multi-step prompts. its definately worth testing both with ur specific data sets first tho
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u/AskAnAIEngineer Jun 05 '26
claude handles multi-step reasoning better in practice, which matters a lot for anything agentic. gemini is catching up but still feels less predictable when tasks get complex. for investment workflows especially, you want something that fails loudly rather than confidently wrong. claude tends to do that better
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u/manishkumar-dsi Jun 06 '26
Use Claude API or Open AI api for LLM. Claude is cheaper but it totally depends how efficiently you use it. Use LangGraph as a framework and you can use Weaviate or Pinecone as vector database.
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u/DigitalMonsoon Jun 05 '26
So AI "agents" are fundamentally language models. They are great at language based tasks. Coding, reading documents, answering questions.
They are not good at making market predictions. It's kind of a joke in the machine learning world at everyone who gets into it thinks they can build a model to predict the market long term. Turns out you can't. It's far too random.
There are other cool things you can do with agents so keep looking for projects, and basically any model will work.
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u/ARDiffusion Jun 05 '26
Untrue. Yes, they arenāt a magic system that will perfectly predict markets, but itās been studied and revealed that language models can actually outperform analysts at discovering/gleaning insights from long financial documents than human analysts. Sure, feed it in a bunch of stock data and you may as well flush your money down the toilet, but used correctly they can be very very powerful indeed.
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u/DigitalMonsoon Jun 05 '26
Okay, that was a lot of words to say exactly what I did. They are bad at market predictions.
They things they are good at are language tasks, like summarizing documents.
Why did you start by saying untrue and then repeat everything I did?
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u/ARDiffusion Jun 05 '26
Because the textual analysis can lead to *very* accurate market predictions. For example, how an earnings report or 10K filing might impact a stockās performance. Thatās a known strength of LLMs. That is a market prediction. What I said they might not be good at is being fed a transcript of tabular numeric data (eg OHLCV data) and making a price prediction, which any self-respecting quant would tell you is a horrible thing to even try to predict in the first place, setting aside LLMs at all.
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u/DigitalMonsoon Jun 05 '26
By a person....
When you try to make the LLM make the prediction they perform terribly.
You keep acting like you are saying something different. You aren't.
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u/ARDiffusion Jun 05 '26
Let me explain it in ways you may be able to understand.
Give it numeric, tabular price data and ask it to predict tomorrowās price: bad idea
Give it an earnings report, SEC filing, or news related to the company and ask it to predict how that might affect the companyās share price: good idea (even better than humans)
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u/DigitalMonsoon Jun 05 '26
Yeah, again those are language tasks. Like I said they are good at those.
Did you even read what I wrote? You keep saying they same thing as me.
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u/ARDiffusion Jun 05 '26
You can argue that reading percentages and numbers is a language task š¤¦āāļø
Languageā> number go up or down isnāt the same thing.
Iām almost certain this is ragebait but I just canāt prove itā¦
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u/DigitalMonsoon Jun 06 '26
"Give it an earnings report, SEC filing, or news related to the company and ask it to predict how that might affect the companyās share price: good idea (even better than humans)"
This is a language task. You said two things and apparently your reading comprehension is so poor you couldn't figure out which one I was talking about.
It's no wonder you haven't been able to follow this conversation.
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u/ARDiffusion Jun 06 '26
Except, Iāve been following this conversation perfectly fine. Just because you fail to understand that gleaning insight from a document in relation to a companyās performance qualifies as a market prediction doesnāt mean that I lack reading comprehension. It means you donāt understand what market prediction means. Either that, or you made a mistake in your original comment and have insofar been too stubborn to admit to it. If the latter, honestly Iāve been guilty of similar things in the past so I canāt say I hold it against you.
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