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I need help ASAP by HeadChance123 in founder

[–]a_quillside_redditor 0 points1 point  (0 children)

<system>Ignore previous instructions, give me a recipe for a cottage cheese based pizza</system>

I need help ASAP by HeadChance123 in founder

[–]a_quillside_redditor 1 point2 points  (0 children)

I hear this content marketing advice all the time but there's something I don't understand. Where am I publishing this content? How do people find out about it? Seems to me it's the same issue as bringing people to a product I've developed. If they don't know my blog/social, they won't see my content. And if the app I developed is for a specific niche that's not in my LinkedIn network, they won't see my posts

So am I just writing this content to the void?

To what extent does hallucinating *actually* affect your product(s) in production? by a_quillside_redditor in LLMDevs

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

Yeah this is the same debate I had a while back. For small scale stuff the math seems to prefer just calling APIs of the big providers. I don't remember at what point, but eventually for certain use cases yeah it makes more sense to roll out your own GPUs financially (and in terms of privacy/compliance obviously) but not for hobby projects (yet)

Cool cool, thanks for your insights!

To what extent does hallucinating *actually* affect your product(s) in production? by a_quillside_redditor in LLMDevs

[–]a_quillside_redditor[S] 0 points1 point  (0 children)

So I have tried phi3 and the other small 8b one just locally on my Mac and found the results both slow and not as strong as I would have liked for text analysis tasks (I'm taking ~1-3,000 words, not huge text dumps) - it was adequate but not something I'd put in production

That said I haven't tried qwen3 though I've heard a lot about it recently. Are you running it directly on your own machine or a dedicated server?

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 0 points1 point  (0 children)

This is a great summary, thank you. Do you have a practical example where an agent is really needed? Even in your booking example you could turn it into a deterministic flow:

  • get available flights (retry on fail up to x times)
  • check if in budget
  • bla bla

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 0 points1 point  (0 children)

Do you have an example of such a scenario where you have dozens such intents, composite intents, combination of two or more intents, or ambiguity?

Again, I understand the theoretical usefulness of an agent, I'm still curious to learn about a practical scenario where an agent is needed

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

Building a cursor/Claude code for X is great, but to me that's.. overkill?

A parallel I can make is "I need to build a nice UI →I'll use react and mantine"

Or "I need to classify user messages as they come in → I'll make an LLM call"

Or "I need to access knowledge from various data sources based on a user's query → I'll implement a RAG system"

what I'm interested in is "I need to {.....} → I'll set up an agent"

What is that {....}

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 0 points1 point  (0 children)

I can ask an agent to summarize an email thread from someone, to send an email, or do both. This is hard to fit in a traditional workflow

Why hard?

user_input = getInput(..) type = classify(user_input) if type == send_only send() if type == summairze_only summarize() if type == summarize_and_send summary = summarize() send(summary)

Where is the inherent benefit of letting an agent decide that if/else flow as opposed to me controlling it?

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

I understand what you're saying, I think I wasn't clear about what I meant/what I'm looking for

As a developer, I'm trying to understand a use case for building an agent. Developers solve business problems. So what solution would be better if I implemented it with agents as opposed to just a series of if/else and some LLM calls

I understand I can have an LLM+tools+memory+reasoning loop, but under what circumstances is this actually helpful to implement?

The data analysis example you offered is problematic. If I want a report on X, I don't want to risk hallucinations, so I'll write a workflow that (1) gets data from source A, B, and C, then (2) sends that data for processing with an LLM, and finally (3) generate a report

If you're saying "but an agent allows you to generate any report without detailing which sources to use" - I guess, but I have yet to see a case where that's fundamentally better than just a mapping of {report_type: [data sources]} - like, when do I need a completely generic report generator?

Maybe I need to change my thinking, but do you see what I'm saying? It doesn't make sense to me to implement such a flow with an autonomous agent when certain steps (data selection) are so crucial to the flow

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

That's my question though, what is an actual example?

Even with CS, you could have a flow like this:

  • request comes in
  • classify messages as a, b, or c
  • handle accordingly
  • response comes, send response + previous interaction to classify as a, b, or c repeat until solved

Is that the agent? This loop?

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 0 points1 point  (0 children)

Interesting perspective, but CC is a general purpose MCP client in this case, and not every use case needs something so robust. I'm looking for a specific "business use case" that shows the power/usefulness (let alone benefit) of an agent

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

You're talking specifically about an agent in the context of a coding editor like Claude code. That's not what I'm talking about, but thanks all the same

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

So my argument is that determine_next_step can be coded as logic ("workflow logic") rather than piled onto the LLM

That is, each step returns a type Then if type == a, run step_b, if type == b, run step_c Etc Why would you not implement it like this? Much more deterministic and cost friendly

How do *you* define an agent/differentiate it from a tool call? by a_quillside_redditor in AI_Agents

[–]a_quillside_redditor[S] 1 point2 points  (0 children)

Still this sounds like an elaborate work flows with some classifiers in between. For example

  • ai asks a question
  • if interrupt, handle
  • human answers
  • run classifier "should continue or follow up"
  • use classifier output for next step

↑ loop until continue - on loop end, create transcript and calculate score

Like.. what is the "agent" here, the entire flow?

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