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Everything around LLMs is still magical and wishful thinking

dmitriid.com

191–200 of 377 posts

Re: Everything around LLMs is still magical and wishful thinking

#191

I think that the disparity comes between people that are too in the weeds believing that their use cases apply to everyone. The reality is this world is made up of people with a wide array of different needs and AI is yet to proliferate into all usage applications. Sure some of this comes from a lack of education. But similar to crypto these movements only have value if the value is widely perceived. We have to work…

> But similar to crypto these movements only have value if the value is widely perceived.

The difference in the AI case is that companies that are actually able to use it to boost productivity significantly will start to outcompete those who don't.

That's why, unlike crypto/blockchain, so many mainstream companies are pouring money into AI. It's not FOMO so much as fear of extinction.

Re: Everything around LLMs is still magical and wishful thinking

#192
post #186

Earlier quoted context omitted.

The item lost is pipeline of talent in all of this though. Precision machining is going through an absolute nightmare where the journeymen or master machinists are aging out of the work force. These were people who originally learned on manual machines, and upgraded to CNC over the years. The pipeline collapsed about 1997. Now there are no apprentice machinists to replace the skills of the retiring workforce. This wi…

> The item lost is pipeline of talent in all of this though. Totally agree. However, I think this pipeline has been taking a hit for a while already because juniors as a whole have been devaluing themselves: if we expect them to leave after one year, what's the point of hiring and training them? Only helping their next employer at that point.

[deleted]

Re: Everything around LLMs is still magical and wishful thinking

#193
post #186

Earlier quoted context omitted.

The item lost is pipeline of talent in all of this though. Precision machining is going through an absolute nightmare where the journeymen or master machinists are aging out of the work force. These were people who originally learned on manual machines, and upgraded to CNC over the years. The pipeline collapsed about 1997. Now there are no apprentice machinists to replace the skills of the retiring workforce. This wi…

> The item lost is pipeline of talent in all of this though. Totally agree. However, I think this pipeline has been taking a hit for a while already because juniors as a whole have been devaluing themselves: if we expect them to leave after one year, what's the point of hiring and training them? Only helping their next employer at that point.

That old canard? If you pay people in a way that incentivizes them to stay, they will. If you train people and treat them right and pay them right, they wont leave. If they are, try to fix one of those things, stop blaming the juniors for their massive collusion in a market where they literally are struggling to get jobs.

Re: Everything around LLMs is still magical and wishful thinking

#194

I'm a retired programmer. I can't imagine trusting code generated by probablities for anything mission critical. If it were close and just needed minor tweaks I could understand that. But I don't have experience with it. My comment is mainly to say LLMs are amazing in areas that are not coding, like brainstorming, blue sky thinking, filling in research details, asking questions that make me reflect. I treat the LLM l…

I say this as an LLM skeptic.

All code, including stuff that we experienced coders write is inherently probabilistic. That’s why we have code reviews, unit tests, pair programming, guidelines and guardrails in any critical project. If you’re using LLM output uncritically, you’re doing it wrong, but if you’re using _human_ output uncritically you’re doing it wrong too.

That said, they are not magic, and my fear is that people use copilots and agentic models and all the rest to hide poor engineering practice, building more and more boilerplate instead of refactoring or redesigning for efficiency or safety or any of the things that matter in the long run.

Re: Everything around LLMs is still magical and wishful thinking

#195

One thing I find frustrating is that management where I work has heard of 10x productivity gains. Some of those claims even come from early adopters at my work. But that sets expectation way too high. Partly it is due to Amdahl's law: I spend only a portion of my time coding, and far more time thinking and communicating with others that are customers of my code. Even if does make the coding 10x faster (and it doesn't…

Its great when they use AI to write a small app “without coding at all” over the weekend and then come in on Monday to brag about it and act baffled that tasks take engineers any time at all.

Re: Everything around LLMs is still magical and wishful thinking

#196

I have to say I’m in the exact camp the author is complaining about. I’ve shipped non trivial greenfield products which I started back when it was only ChatGPT and it was shitty. I started using Claude with copying and pasting back and forth between the web chat and XCode. Then I discovered Cursor. It left me with a lot of annoying build errors, but my productivity was still at least 3x. Now that agents are better an…

But you just confirmed everything the blogpost claimed. You didn't share any evidence with us even though you claim unbelievable things. You even went as far as registering a throwavay account to hide your identity and to make verifying any of your claims impossible. Your comment feels more like a joke to me

... this from an account with Look, the person who wrote that comment doesn't need to prove anything to you just because you're hopped up after reading a blog post that has clearly given you a temporary dopamine bump.

People who understand their domains well and are excellent written communicators can craft prompts that will do what we used to spend a week spinning up. It's self-evident to anyone in that situation, and the only thing we see when people demand "evidence" is that you aren't using the tools properly.

We don't need to prove anything because if you are working on interesting problems, even the most skeptical person will prove it to themselves in a few hours.

Re: Everything around LLMs is still magical and wishful thinking

#197

Earlier quoted context omitted.

I’m a tech lead and I have maybe 5X output now compared to everybody else under me. Quantified by scoring tickets at a team level. I also have more responsibilities outside of IC work compared to the people under me. At this point I’m asking my manager to fire people that still think llms are just toys because I’m tired of working with people with this poor mindset. A pragmatic engineer continually reevaluates what t…

A new copypasta is born.

Go back to reddit

Re: Everything around LLMs is still magical and wishful thinking

#198

I personally don't really get this. _So much_ work in the 'services' industries globally comes down to really a human transposing data from one Excel sheet to another (or from a CRM/emails to Excel), manually. Every (or nearly every) enterprise scale company will have hundreds if not thousands of FTEs doing this kind of work day in day out - often with a lot of it outsourced. I would guess that for every 1 software e…

Making a comparison to crypto is lazy criticism. It’s not even worth validating. It’s people who want to take the negative vibe from crypto and repurpose it. The two technologies have nothing to do with each other, and therefore there’s clearly no reason to make comparative technical assessments between them.

That said, the social response is a trend of tech worship that I suspect many engineers who have been around the block are weary of. It’s easy to find unrealistic claims, the worst coming from the CEOs of AI companies.

At the same time, a LOT of people are practically computer illiterate. I can only imagine how exciting it must seem to people who have very limited exposure to even basic automation. And the whole “talking computer” we’ve all become accustomed to seeing in science fiction is pretty much becoming reality.

There’s a world of takes in there. It’s wild.

I worked in ML and NLP several years before AI. What’s most striking to me is that this is way more mainstream than anything that has ever happened in the field. And with that comes a lot of inexperience in designing with statistical inference. It’s going to be the Wild West for a while — in opinions, in successful implementation, in learning how to form realistic project ideas.

Look at it this way: now your friend with a novel app idea can be told to do it themselves. That’s at least a win for everyone.

Re: Everything around LLMs is still magical and wishful thinking

#199
post #160

Earlier quoted context omitted.

12 months ago, if I fed a list of ~800 poems with about ~250k tokens to an LLM and asked it to summarize this huge collection, they would be completely blind to some poems and were prone to hallucinating not simply verses but full-blown poems. I was testing this with every available model out there that could accept 250k tokens. It just wouldn't work. I also experimented with a subset that was at around ~100k tokens…

Your comment warrants a longer, more insightful reply than I can provide, but I still feel compelled to say that I get the same feeling from o3. Colder, somewhat robotic and unhelpful. It's like the extreme opposite of 4o, and I like neither. My weapon of choice these days is Claude 4 Opus but it's slow, expensive and still not massively better than good old 3.5 Sonnet

Exactly! Here's my take:

4o tens do be, as they say, sycophantic. It's an AI masking as a helpful human, a personal assistant, a therapist, a friend, a fan, or someone on the other end of a support call. They sometimes embellish things, and will sometimes take a longer way getting to the destination if it makes for a what may be a more enjoyable conversation — they make conversations feel somewhat human.

OpenAI's reasoning models, though, feel more like an AI masking a code slave. It is not meant to embellish, to beat around the bush or to even be nice. Its job is to give you the damn answer.

This is why the o* models are terrible for creative writing, for "therapy" or pretty much anything that isn't solving logical problems. They are built for problem solving, coding, breaking down tasks, getting to the "end" of it. You present them a problem you need solved and they give you the solution, sometimes even omitting the intermediate steps because that's not what you asked for. (Note that I don't get this same vibe from 2.5 at all)

Ultimately, it's this "no-bullshit" approach that feels incredibly cold. It often won't even offer alternative suggestions, and it certainly doesn't bother about feelings because feelings don't really matter when solving problems. You may often hear 4o say it's "sorry to hear" about something going wrong in your life, whereas o* models have a much higher threshold for deciding that maybe they ought to act like a feeling machine, rather than a solving machine.

I think this is likely pretty deliberate of OpenAI. They must for some reason believe that if the model is much concise in its final answers (though not necessarily in the reasoning process, which we can't really see), then it produces better results. Or perhaps they lose less money on it, I don't know.

Claude is usually my go-to model if I want to "feel" like I'm talking to more of a human, one capable of empathy. 2.5 pro has been closing the gap, though. Also, Claude used to be by far much better than all other models at European Portuguese (+ portuguese culture and references in general), but, again, 2.5 pro seems just as good nowadays).

On another note, this is also why I also completely understand the need for the two kinds of models for OpenAI. 4o is the model I'll use to review an e-mail, because it won't just try to remove all the humanity of it and make it the most succinct, bland, "objective" thing — which is what the o* models will.

In other words, I think: (i) o* models are supposed to be tools, and (ii) 4o-like models are supposed to be "human".

Re: Everything around LLMs is still magical and wishful thinking

#200
Many well-trusted and reasonable tech folks who are known for sober takes on subjects have reported substantial improvements in their programming work by using various forms of generative AI.

What does substantial mean? Somewhere between 5% and 100%. Something NOT insignificant.

At a minimum, it is safe to say that GenAI is or could be a significantly beneficial tool for a significant number of people.

It's not required that folks disclose how many CPUs, lines of code, numbers of bytes processed, or other details for the above to be a reasonable take.

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