No it just sounds completely stupid. You spent $10k to get a program to write text that you can write yourself just as well and for free. "Dissonance" doesn't even begin to describe it. It's like suddenly everyone has turned into the listless blobs of fat that humans have turned into in Wall-E.

I just hope all that will eventually correct itself: open (one way or another) models will reach parity with proprietary ones when diminishing returns eventually make it impossible for LLMs to grow any longer, OpenAI and Anthropic will succeed in bankrupting each other, it will become possible for everyone to run their own, personal, free and open (one way or another) model on their own laptop (assuming we still own our laptops) and at that point most of the problems with LLMs, particularly the ones that come from having to pay someone else to do the things you could always do yourself for free, will go away.

I just hope.

So far, so agreeable, but…

> If you have thoughts, they come out sharper and faster.

I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles.

Actual muscles need exercise to stay in shape (let alone grow), so does the brain. Can we really be sure that thoughts, opinions, taste will still come out sharper and faster after five, ten, 20 years of using these tools almost every day?

Conversely, I also am a user of LLMs (true shocker these days, I know), and am noticing a speedup in areas I was already familiar with, and a quicker introduction to new ones. The obvious benefit cannot be denied, and doing so regardless makes you look uninformed. [0]

So what’s the ideal “middle ground” in this situation? Stoically continuing to sharpen your skills on your own, but risking being left in the dust productivity-wise? Or taking an “agent first” approach and trying to learn and improve more only on the side, as more of an afterthought?

[0] Excluding people who don’t want anything to do with LLMs out of moral principle, which curiously just like the overarching topic I also both respect and understand, but on the other hand don’t do myself.

A smartphone is also a genuinely good all-around tool. Even social media is a genuinely good tool for connecting people.

Yet, I feel like we've been overly optimistic about the impact of said tools on us and our societies in the past two decades.

Smartphones are so good, in fact, in some societies, half of us are addicted to them. Billions of people world-wide.

I ask myself: Will LLMs enrich my thinking in the long run, or will they ruin it?

And what about most people? Will half of us outsource most of our thinking in a decade from now?

Given the speed and global scale that we're running these experiments with, it's fair, I think, to be a bit sceptical of the conclusion that, in the long run, LLMs will enrich our thinking.

The only evidence you have is US here and all the frontier models from China are free to download. Pure projection.

You can read China's AI strategy here: https://ipc.court.gov.cn/zh-cn/news/view-5766.html

What are people actually doing with all these tokens? I use LLMs pretty heavily for development, and I'm rarely spending all the tokens that come with a $10/month OpenCode Go subscription...

I have linked this elsewhere in this thread, but the studies on this matter suggest a worse outcome than just losing hand crafted or "artisanal" software: https://arxiv.org/pdf/2604.04721

> These findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning.

> We posit that persistence is reduced because AI conditions people to expect immediate answers, thereby denying them the experience of working through challenges on their own.

This issue is not that we are losing the ability to write good software by hand. It is possible we are losing our internal tools to learn new things by circumventing a necessary part of the process required by our biology.

This is where I take issue. I'm in a similar boat to the author. In the last couple of months, I've been experimenting with increasing the use of local and cloud LLMs for my research code. I'll create a prototype, maybe port it to a language I don't use very much like Rust, run some tests... but at the very end when I'm very happy with it, I _need_ to go line by line and understand _everything_ that is happening. Sometimes that means using an LLM to understand it, but even when I do and there is a concept I don't get, I try to read primary resources written by experts.

The least bad thing I've found LLMs good for is ideation because it's super easy to take the good nuggets and leave the bad, but even that carries risks of shaping thought and making everyone reach for and ignore the same ideas in the way the Spotify radio or YouTube autoplay has been shaping/flattening tastes for the worse.

I'm not sure what I'll rule at the end of my experiments with LLMs, but right now I'm enjoying the rush of having prototypes that run quickly. I've always been a top-down learner, being motivated by hacking a cool demo I half understand and progressively tearing it apart.

That seems unlikely given the diverse nature of mutually exclusive opinions that exist out there.

Critics seem to run the gamut from LLMs being incapable of even the most basic of functions to already sentient creatures secretly plotting our destruction with steganographic messages to each other.

It's maybe a bell curve with some wacky at those tails, but there's some fairly significant differences of opinion amongst the positions that are more mainstream.

Just the difference between critics of all LLMs and crutics of all closed weights models are a pretty big gap.

Similarly for those who criticise them for over censorship vs those who criticise them for unrestricted generation.

Yeah, that's the thing for me. LLMs have made my work easier and faster, and they've made my side projects easier and faster. I think there are very sensible and valid critiques but so far the tool works for me.

> "Yet I still write all of my texts with LLMs"

So I'm guessing the author is actually ok with the point they put in the "LLMs are bad" part of the article?

Writing is thinking. If you're outsourcing your writing to an LLM, you are shortchanging yourself by skipping over much of the refinement of ideas that the process of writing provides.

I wish the author had clarified how he uses LLMs for writing. It's perfectly fine to have an LLM proofread and fix your grammatical errors--that's a mechanical task. But I think it's gross when it starts putting words and content on the page.

If you are bringing in juniors with the expectation that they won’t produce any value for some time then it might be better to block them from using LLMs.

Do this and you will get a better understanding of where they are in the process and they will probably learn the ropes more quickly.

I suspect a lot of people are in this boat. We both use it and cheer against it. But it's not cognitive dissonance, it's just a recognition that there's a useful tool being controlled by vile people.

I'm currently writing an onboarding doc for my team, encouraging LLM use for some tasks. (OK, well, I'm actually procrastinating by reading HN).

At the same time, I'm in a darkened office with tinfoil on the windows and a fan pointed at me because it's hell outside and it has been for weeks, and every year it seems to get hotter and hotter and we have longer and longer heatwaves.

This seems ... discordant, at a minimum.

Really, _should_ we be using these things to speed up, say, dependency updates if the cost is the planet? I wanted to know what the author thought about that.

At least the "industry" ones used for "networking" and all that other crap. Where's the news here? And why does the author not take a step back and realize that there is none?

This is because.. sometimes an idea is just bad. I learned the hard way the other day when I filed this PR against prek: https://github.com/j178/prek/pull/2302

My idea was bad.

The implementation was meant to solve my problem. All it did was expose more problems and waste my time and the maintainer's, and god knows how many tokens from Claude and Codex. In the end the PR was useless so I closed it.

The maintainer and I would have both been better off - less time wasted - if I was forced to forever wonder if the idea was good, letting it bounce around the back of my mind.

I'm saying it in jest, but it's also a bit true. Not necessarily because we use it any differently. But because my use of AI saves me time. But their use of AI adds more to my plate, no matter if it's slop or not.

It's sad that this can be true because if you did them alone the quality would be non-existent.

I use AI to code tools for myself, but I don't pretend anything I make is production quality. Duct tape engineering has always been a bit sloppy, and AI just made it faster.

I use AI to troubleshoot issues and plan out strategies, but I basically consider the AI draft of anything to be "draft 0", and use it as a framework for writing my own works for a real first draft of anything I write that will be read by other people. Sometimes the AI spits out a perfect paragraph that I might copy, but I don't ever blindly trust it or let it speak for me. I also double-check everything it says that I don't have existing knowledge of, rather than trust it to be right.

AI images, video, and music are all entertaining, but I only generate these things as a form of self-entertainment and maybe online meming. I could never in good conscience pass these creations off as my own, or publish them online on a personal or business website when something non-synthetic would suffice.

And I am never personally confiding in an LLM like it were a person. I have had it help me brainstorm options for office politics stuff, but I'm not about to ask it for relationship advice or to be my friend.

I do love that it accelerates the tedious stuff, and helps me learn new things pretty quickly if used right. It has definite utility. But I am always really distrustful of it. Sometimes at work we are asked to share how we use AI, and I have actually refused before, on the grounds that I may have found a useful way to use the AI, but I am worried that others will use my same method badly (e.g., not verifying eveything the AI says first), and I would rather not share.

It's like I have a finicky gun. I might be comfortable shooting it since I know its quirks and how to keep it from accidentally discharging, but I'm not loaning it out to anyone I wouldn't want to accidentally shoot themselves with it.

Master craftsmen didn't take on apprentices to give them chores.

It's really not incongruent to use LLMs and be in awe of their frankly incredible capabilities while at the same time recognize the risks and frankly real damage we are already seeing to junior training and hiring, open source communities and (in my opinion) very soon the entire fabric of our society.

I respect that people don't want to use agents themselves for whatever personal reason.

I respect maintainers not accepting AI-authored contributions. It's a tradeoff between progress, growing new contributors and maintainer sanity. Though I do feel that categoric opposition to anything AI will likely be futile in the mid-term.

I respect people pushing for regulation of AI or a global pause or whatever.

I don't particularly respect people dismissing everything AI authored as slop. Categorically refusing to read an article because it contains em-dashes or the term "load-bearing" is silly. While this is slowly changing now, many people are still in complete denial as to what the frontier AI is capable of.

Love it, hate it - I don't care, but at least respect it, goddamit.

Ding ding ding. This is my biggest gripe with AI. Even the SEO blogspam, the fluff in front of every recipe, yarnwork or DIY instruction, it all was clearly written by a human. Someone had invested time (and money) in getting something in front of my eyes.

But now, it's all just slop. Everywhere. And hell I'm tired because the onslaught breaks my trust filters.

Maybe I think this is an age thing. Boomers? They trust everything written down somewhere. No matter what, and no matter if they didn't spend half my childhood to "never trust what people write on the Internet", and now they fall for scams left and right. My generation as said grew up with this "never trust, always verify" thing. And the younger generation? They DGAF about anything any more, all they care about is trying to survive.

> And b), the teaching, aka “How do we teach new people?”: previously, there was this balance aka “the junior does some pretty mundane tasks, but for this the senior reviews it together with him and helps him to grow”.

GOD YES YES YES THIS x1000.

There is barely anything more rewarding than teaching someone something, to watch the other person grow - and eventually surpassing your own abilities. That is when you know you did right and well. My wife is the best example, she started out at "can you help me with Excel", and these days, she pulls off stuff that would make more than a few finance people blush.

Even this article has some cognitive dissonance in it. What it really comes down to is how much you trust your own verification process. The branches of questions an LLM generates are still trapped within the biases of its training data. Of course, the authority to craft that initial prompt, the very first question, comes from human experience and learning.

But I think thought itself is the easiest resource to outsource. People say the human did the thinking and the LLM just amplified it, but the truth is, the LLM outsources the thinking. Otherwise, when the result is good, people say "human thought was present," and when it's bad, they say "human thought was absent." But a part of the actual thinking really is outsourced. The alternatives, the counterexamples, the sentence structure. In programming terms, the reader's experience gets outsourced. When you write a blog post, you find yourself thinking about how to make something you understand easy for someone else to understand. With an LLM, that part gets outsourced.

But at the same time, I don't get the argument that you shouldn't use it at all. We don't "think" about everything. We have limited cognitive resources. So we study deeply the things we care about, but for the things we don't need, we mostly leave them to "common sense" or prejudice. We just skim the surface.

I think of "common sense" as "the largest collection of prejudice." Because what we call common sense usually just amounts to surface level knowledge, the kind of thing we know just enough about to get by.

That's why I think LLMs are good. The reason is simple. I don't think deeply about everything in the world anyway. For everything else, I'm buried in some kind of bias. You see it on HN all the time, right? People fight over some technology, but they often don't think about its internal structure or why it works the way it does. They just treat it as an identity. They fight over a particular language, a framework, an operating system, but they rarely check how that technology actually works internally or why it was designed that way. Why use MVC, why a different architecture might be better for my case, it's easier to just go with what's popular. Put more elegantly, "job mobility" gets bundled in there too. I use Windows. In my country, if it's not Windows, you literally can't do anything. You can't even do basic online banking. From regional context like that all the way down to personal interests, people are bound to be different. So I'm just going to use LLMs. The most common excuse you hear around this is the whole "reinventing the wheel" thing.

So yeah, I'm going to use LLMs. Because I recognize that I bias myself toward only thinking about what I want to think about. And I know that bias isn't cognitively healthy. But on the flip side, I think what the world values, whether it's knowing a lot or knowing one thing deeply, is going to change.

Honestly, I don't know what's right. I think both the advocates and the critics are making valid points. I respect the people who don't use it, and the people who do just have their own workflow. There's really no reason to fight over whose workflow is superior.

Saying agents produce shitty code is a bad argument though. They produce shitty codebase organization, but at a micro level their code is solid if not elegant. If you let them turn your codebase into a spaghetti mess, that's on you.

Hypocritical garbage. Into the blacklist you go.

If you can’t even use your own words for basic communication then there’s absolutely no reason for me to take you seriously.

The big thing people used to call AI was that it was a stochastic parrot and all it did was summarize things. Clearly. None of this is/was true anymore. And very likely all the current criticism will be eliminated soon and we have to find new excuses about AI that makes us feel we are superior.

The status quo is about to change. Every 6 months. And you will always think of yourself as superior to LLMs. Your current criticisms will evolve as most of them will be rendered not true pretty soon.

The tech world does not care about woke ideology, german technical illiteracy and self importance.

LLMs are useful and here to stay.