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How I write software with LLMs

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Re: How I write software with LLMs

#121

Post by luxcem »

akhrail1996 wrote: post #22

Genuine question: what's the evidence that the architect → developer → reviewer pipeline actually produces better results than just... talking to one strong model in one session? The author uses different models for each role, which I get. But I run production agents on Opus daily and in my experience, if you give it good context and clear direction in a single conversation, the output is already solid. The ceremony…

The agent "personalities" and LLM workflow really looks like cargo-cult behavior. It looks like it should be better but we don't really have data backing this.

Re: How I write software with LLMs

#122

Post by cpt_sobel »

TheDong wrote: post #102
cpt_sobel wrote: post #88

Earlier quoted context omitted.

> If the result of your prompt + its answer it's more likely to score higher i.e. gives better result that a prompt that feels out of place with the answer Sure seems like this could be the case with the structure of the prompt, but what about capitalizing the first letter of sentence, or adding commas, tag questions etc? They seem like semantics that will not play any role at the end

Why wouldn't capitalization, commas, etc do well? These are text completion engines. Punctuation and capitalization is found in polite discussion and textbooks, and so you'd expect those tokens to ever so slightly push the model in that direction. Lack of capitalization pushes towards text messages and irc perhaps. We cannot reason about these things in the same way we can reason about using search engines, these thi…

> Lack of capitalization pushes towards text messages and irc perhaps.

Might very well be the case, I wonder if there's some actual research on this by people that have some access to the the internals of these black boxes.

Re: How I write software with LLMs

#123

Post by cindyllm »

cpt_sobel wrote: post #119
bob1029 wrote: post #115

Earlier quoted context omitted.

With current models this isn't as big of a deal, but why risk being an asshole in any context? I don't think treating something like shit simply because it's a machine is a good excuse. Also consider the insanity of intentionally feeding bullshit into an information engine and expecting good things to come out the other end. The fact that they often perform well despite the ugliness is a miracle, but I wouldn't depen…

I neither talked about feeding bullshit into it, nor treating it like shit. Around half of the commenters here seem to be missing the middle ground, how is prompting "i need my project to do A, B, C using X Y Z" treating it like shit?

[dead]

Re: How I write software with LLMs

#124

Post by olalonde »

cpt_sobel wrote: post #72

In the plethora of all these articles that explain the process of building projects with LLMs, one thing I never understood it why the authors seem to write the prompts as if talking to a human that cares how good their grammar or syntax is, e.g.: > I'd like to add email support to this bot. Let's think through how we would do this. and I'm not not even talking about the usage of "please" or "thanks" (which this part…

I suspect they just find it easier and more natural to write with proper grammar.

Re: How I write software with LLMs

#125

Post by vitro »

cpt_sobel wrote: post #88
tarsinge wrote: post #83

Earlier quoted context omitted.

The reasoning is by being polite the LLM is more likely to stay on a professional path: at its core a LLM try to make your prompt coherent with its training set, and a polite prompt + its answer will score higher (gives better result) than a prompt that is out of place with the answer. I understand to some people it could feel like anthropomorphising and could turn them off but to me it's purely about engineering. Ed…

> If the result of your prompt + its answer it's more likely to score higher i.e. gives better result that a prompt that feels out of place with the answer Sure seems like this could be the case with the structure of the prompt, but what about capitalizing the first letter of sentence, or adding commas, tag questions etc? They seem like semantics that will not play any role at the end

For me it is just a good habit that I want to keep.

Re: How I write software with LLMs

#126

Post by tomgp »

vbezhenar wrote: post #107
slopinthebag wrote: post #62

Earlier quoted context omitted.

Most developer intuitions are wrong. See: OOP

Intuition is subjective. It's hard to convert subjective experience to objective facts.

That's what science is though * our intuition/ hunch/ guess is X * now let's design an experiment which can falsify X

Re: How I write software with LLMs

#127

Post by wiseowise »

tarsinge wrote: post #83
cpt_sobel wrote: post #72

In the plethora of all these articles that explain the process of building projects with LLMs, one thing I never understood it why the authors seem to write the prompts as if talking to a human that cares how good their grammar or syntax is, e.g.: > I'd like to add email support to this bot. Let's think through how we would do this. and I'm not not even talking about the usage of "please" or "thanks" (which this part…

The reasoning is by being polite the LLM is more likely to stay on a professional path: at its core a LLM try to make your prompt coherent with its training set, and a polite prompt + its answer will score higher (gives better result) than a prompt that is out of place with the answer. I understand to some people it could feel like anthropomorphising and could turn them off but to me it's purely about engineering. Ed…

> The reasoning is by being polite the LLM is more likely to stay on a professional path

So no evidence.

Re: How I write software with LLMs

#128

Post by lbreakjai »

xhale wrote: post #23

Hi, anyone has a simple example/scaffold how to set up agents/skills like this? I’ve looked at the stavrobots repo and only saw an AGENTS.md. Where do these skills live then? (I have seen obra/superpowers mentioned in the comments, but that’s already too complex and with an ui focus)

I played with this over the weekend:

https://github.com/marcosloic/notion-agent-hive

Ultimately, it's just a bunch of markdown files that live in an `/agents` folder, with some meta-information that will depend on the harness you use.

Re: How I write software with LLMs

#129

Post by vanviegen »

borski wrote: post #38
roncesvalles wrote: post #35

Earlier quoted context omitted.

You seem to think therapists are only for those in dire straits. Yes, if you're at that point, definitely speak to a human. But there are many ordinary things for which "drop-in" therapist advice is also useful. For me: mild road rage, social anxiety, processing embarrassment from past events, etc. The tools and reframing that LLMs have given me (Gemini 3.0/3.1 Pro) have been extremely effective and have genuinely im…

I never said therapists were only for those in crisis; that is a misreading of my argument entirely. An LLM cannot parse the complexity of your situation. Period. It is literally incapable of doing that, because it does not have any idea what it is like to be human. Therapy is not an objective science; it is, in many ways, subjective, and the therapeutic relationship is by far the most important part. I am not saying…

As you said earlier, therapists are (thoroughly) trained on how to best handle situations. Just 'being human' (and thus empathizing) may not be such a big part of the job as you seem to believe.

Training LLMs we can do.

Though it might be important for the patient to believe that the therapist is empathizing, so that may give AI therapy an inherent disadvantage (depending on the patient's view of AI).

Re: How I write software with LLMs

#130

Post by jstanley »

xnorswap wrote: post #117
dgb23 wrote: post #98

Earlier quoted context omitted.

I can't speak for everyone, but to me the most accurate answer is that I'm role-playing, because it just flows better. In the back of my head I know the chatbot is trained on conversations and I want it to reflect a professional and clear tone. But I usually keep it more simple in most cases. Your example: > I'd like to add email support to this bot. Let's think through how we would do this. I would likely write as:…

I agree, it's just easier to write requirements and refine things as if writing with a human. I no longer care that it risks anthropomorphising it, as that fight has long been lost. I prefer to focus on remembering it doesn't actually think/reason than not being polite to it. Keeping everything generally "human readable" also the advantage of it being easier for me to review later if needed.

How can you use these models for any length of time and walk away with the understanding that they do not think or reason?

What even is thinking and reasoning if these models aren't doing it?

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