[soulofmischief]

Comments like this are a great example of the Dunning-Kruger effect. Your comment is actually an indication that you don't have the mastery required to get useful, productive output from a high quality LLM.

Maybe you don't push your boundaries as an engineer and thus rarely need to know new things or at least learn new API surfaces. Maybe you don't know how to effectively prompt an LLM. Maybe you lack the mastery to analyze and refine the results. Maybe you just like doing things the slow way. I too remember a time as an early programmer where I eschewed even Intellisense and basic auto complete...

I'd recommend learning a bit more and practicing some humility and curiosity before condemning an entire class of engineers just because you don't understand their workflow. Just because you've had subpar experiences with a new tool doesn't mean it's not a useful tool in another engineer's toolkit.

[namaria]

Funny you should make claims about my skills when you have exactly zero data about my abilities or performance.

Evaluating my skills based on how I evaluated someone else's skills when they tell me about their abilities with and without a crutch, and throwing big academic sounding expressions with 'effect' in them might be intimidating to some but to me it just transparently sounds pretentious and way off mark, since, like I said, you have zero data about my abilities or output.

> I'd recommend learning a bit more and practicing some humility and curiosity before condemning an entire class of engineers

You're clearly coming from an emotional place because you feel slighted. There is no 'class of engineers' in my evaluation. I recommend reading comments more closely, thinking about their content, and not getting offended when someone points out signs of lacking skills, because you might just be advertising your own limitations.

[soulofmischief]

> Funny you should make claims about my skills when you have exactly zero data about my abilities or performance.

Didn't you just do that to an entire class of engineers:

> Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary

Anyway,

> Evaluating my skills based on how I evaluated someone else's skills when they tell me about their abilities with and without a crutch

Your argument rests on the assumption that LLMs are a "crutch", and you're going to have to prove that before the rest of your argument holds any water.

It sucks getting generalized, doesn't it? Feels ostracizing? That's the exact experience someone who productively and effectively uses LLMs will have upon encountering your premature judgement.

> You're clearly coming from an emotional place because you feel slighted.

You start off your post upset that I'm "making claims" about your skills (I used the word "maybe" intentionally, multiple times), and then turn around and make a pretty intense claim about me. I'm not "clearly" coming from an emotional place, you did not "trigger" me, I took a moment to educate you about being overly judgemental before fully understanding something, and pointed out the inherent hypocrisy.

> you might just be advertising your own limitations

But apparently my approach was ineffective, and you are still perceiving a world where people who approach their work differently than you are inferior. Your toxic attitude is unproductive, and while you're busy imagining yourself as some masterful engineer, people are out there getting massive productivity boosts with careful application of cutting-edge generative technologies. LLMs have been nothing short of transcendental to a curious but skilled mind.

[Ygg2]

> Didn't you just do that to an entire class of engineers

Not really. He said "if you claim LLM's are next thing since sliced butter I am doubting your abilities". Which is fair. It's not really a class as much as a group.

I've never been wowed over by LLMs. At best they are boilerplate enhancers. At worst they write plausibly looking bullshit that compiles but breaks everything. Give it something truly novel and/or fringe and it will fold like a deck of cards.

Even latest research called LLM's benefits into question: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4945566

That said. They are fine at generating commit messages and docs than me.

[soulofmischief]

> Not really. He said "if you claim LLM's are next thing since sliced butter I am doubting your abilities". Which is fair.

No, OP said:

> Claiming LLMs are a massive boost for coding productivity is becoming a red flag that the claimant has a tenuous grasp on the skills necessary

Quotation marks are usually reserved for direct quotes, not paraphrases or straw mans.

> I've never been wowed over by LLMs.

Cool. I have, and many others have. I'm unsure why your experience justifies invalidating the experiences of others or supporting prejudice against people who have made good use of them.

> Give it something truly novel and/or fringe and it will fold like a deck of cards.

Few thoughts are truly novel, most are derivative or synergistic. Cutting edge LLMs, when paired with a capable human, are absolutely capable of productive work. I have long, highly technical and cross-cutting discussions with GPT 4o which I simply could not have with any human that I know. Humans like that exist, but I don't know them and so I'm making due with a very good approximation.

Your and OP's lack of imagination at the capabilities of LLMs are more telling than you realize to those intimate with them, which is what makes this all quite ironic given that it started from OP making claims about how people who say LLMs massively boost productivity are giving tells that they're not skilled enough.

[Ygg2]

> Quotation marks are usually reserved for direct quotes,

Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind.

> Cool. I have, and many others have. I'm unsure why your experience justifies invalidating the experiences of others

If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is scoring it wrong.

I gave papers that demonstrate its failings, where is your counter-proof?

> Your and OP's lack of imagination at the capabilities of LLMs

It's not lack of imagination. It's terribleness of results. It can't consistently write good doc comments. I does not understand the code nor it's purpose, but roughly guesses the shape. Which is fine for writing something that's not as formal as code.

It can't read and understand specifications, and even generate something as simple as useful API for it. The novel part doesn't have to be that novel just something out of its learned corpus.

Like Yaml parser in Rust. Maybe Zig or something beyond it's gobbled data repo.

> Few thoughts are truly novel, most are derivative or synergistic.

Sure but you still need A mind to derive/synergize the noise of everyday environment into something novel.

It can't even do that but remix data into plausibly looking forms. A stochastic parrot. Great for DnD campaign. Shit for code.

[soulofmischief]

> Not on HN. Customary is to use > paragraph quotes like you did. However I will keep that in mind.

Hacker News is not some strange place where the normal rules of discourse don't apply. I assume you are familiar with the function of quotation marks.

> If we're both grading a single student (LLM) in same field (programming), and you find it great and I find it disappointing, it means one of us is scoring it wrong.

No, it means we have different criteria and general capability for evaluating the LLM. There are plenty of standard criteria which LLMs are pitted against, and we have seen continued improvement since their inception.

> It can't consistently write good doc comments. I does not understand the code nor it's purpose, but roughly guesses the shape.

Writing good documentation is certainly a challenging task. Experience has led me to understand where current LLMs typically do and don't succeed with writing tests and documentation. Generally, the more organized and straightforward the code, the better. The smaller each module is, the higher the likelihood of a good first pass. And then you can fix deficiencies in a second, manual pass. If done right, it's generally faster than not making use of LLMs for typical workflows. Accuracy also goes down for more niche subject material. All tools have limitations, and understanding them is crucial to using them effectively.

> It can't read and understand specifications, and even generate something as simple as useful API for it.

Actually, I do this all the time and it works great. Keep practicing!

In general, the stochastic parrot argument is oft-repeated but fails to recognize the general capabilities of machine learning. We're not talking about basic Markov chains, here. There are literally academic benchmarks against which transformers have blown away all initial expectations, and they continue to incrementally improve. Getting caught up criticizing the crudeness of a new, revolutionary tool is definitely my idea of unimaginative.