Because I keep wondering myself if AI is here and our output is charged up, then why am I keep seeing more of the same products but with an "AI" sticker slapped on top of them? From a group of technologists like HN and the startup world, that live on the edge of evolution and revolution, maybe my expectations were a bit too high.
All I see is the equivalent of a "look how fast my new car made me go to the super market, when I'm not too demanding on the super market I want to end up with, and all I want is milk and eggs". Which is 100% fine, but at the end of the day I eat the same omelette as always. In this metaphor, I don't feel the slightest behind, or have any sense of FOMO if I cook my omelette slowly. I guess I have more time for my kids if I see the culinary arts as just a job. And it's not like restaurants suddenly get all their tables booked faster just because everyone cooks omelettes faster.
>It's allowed me to do things that I simply would not have been able to do previously.
You're not the one doing them. Me barking orders to John Carmack himself doesn't make me a Quake co-creator, and even if I micromanage his output like the world's most toxic micromanager who knows better I'm still not Carmack.
On top of that, you would have been able to do previously, if you cared enough to upskill to the point where token feeding isn't needed for you to feel productive. Tons of programmers broke barriers, and solved problems that haven't been solved by anyone in their companies before.
I don't see why everyone claiming that they previously couldn't do something is a bragging point. The LLM's that you're using were trained by the Google results you could've gotten if you Google searched.
>Then everyone who wants AI can have it and those that don't .... don't.
The current trajectory of products with integrated online worries me, due to the fact that the average computer/phone user isn't as tech-savvy as the average HN reader, to the point where they are unable to toggle stuff they genuinely never asked for, but they begrudgingly accept them because they're... there.
My mother complained about AI mode on Google Chrome, and the "press tab" on the address bar, but she's old and doesn't even know how to connect to the Wi-Fi. Are we safe to assume that she belongs to the percentage of Google Chrome users that they embrace AI, based on the fact that she doesn't know how to turn it off, and there's no easy way to go about it?
I'm willing to bet that Google's reports will assume so, and demonstrate a wide adoption of AI by Chrome users to stakeholders, which will be leveraged as a fact that everyone loves it.
My counterpoint to this is, if someone cannot verify the validity of the summary then is it truly a summary? And what would the end result be if the vast majority of people opted to adopt or deny a position based on the summary written by a third party?
This isn't strictly a case against AI, just a case that we have a contradiction on the definition of "well informed". We value over-consumption, to the point where we see learning 3 things in 5 minutes as better than learning 1 thing in 5 minutes, even if that means being fully unable to defend or counterpoint what we just read.
I'm speficially referring to what you said: "the speaker used some obscure technical terminology I didn't know" this is due to lack of assumed background knowledge, which makes it hard to verify a summary on your own.
>2. Internalized speed: be a great individual contributor, build a deep, precise mental model, build correct guardrails and convention (because you understand the problem) and protect those boundaries ruthlessly, optimize for future change, move fast because there are fewer surprises
I think the issue here is, to become a great individual contributor one needs to spent time on the saddle, polishing their skills. And with mandatory AI delegation this polishing stage will take more time than ever before.
Have we really reached the point where a candidate gets outright rejected for not using AI tools, without taking personal aptitudes into consideration?
I learned to accept the fact that HN reached a critical mass point that made it fill up with people who market themselves as "product-oriented engineers", which is a way to say "I only build things when they lead to products".
People commiting to the hacker ethos that consists of, among many other things, resistance to the established tools, embracing knowledge and code sharing, and exploration for its own sake are the minority.
The fact that there are many commenters who will claim that they finally build something they weren't able to build before and it's all thanks to LLM's is evidence that we already sacrificed the pursuit of personal competence, softly reframing it as "LLM competence", without caring about the implications.
Because obviously, every kid that dreamt of becoming a software engineer thought about orchestrating multiple agentic models that talk to each other and was excited about reviewing their output over and over again while editing markdown files.
>It's the same with genetics. Getting lucky with looks is fine but working for the same goal (eg surgery) is somehow bad and people often hide it.
We also tend to hide how hard we work to make our success look natural, but we reveal how hard we work on the extremes of success. For example, if I work hard and take a score of 17 out of 20 in a test people will say "I barely read last evening, phew", but if you're consistently scoring 19-20/20 people may even approach you to learn your studying methods and for tips, because they assume there are important takeaways that they can adopt.
It's my pet peeve with how society recognizes that someone is talented, which is blatantly flawed because all you can do is see what they're capable of doing. Someone may be talented yet unable (or unwilling?) to tap into their talent, but since we recognize talent by the output you can't really tell the existence of talent unless it's at the extremes of success, like the 8 year old who can solve mathematics that are a grade or more above the current grade.
I see talent like a genetic predisposition that can be appropriately cultivated to attain success. It's not much different than my height, because I didn't choose it, yet I can guess that there are men out there who hate the fact that I have their desirable height yet I never hit the gym, cultivate my social skills, or take advantage the fact that I look younger than I am. I am willing to bet everything that I met at least one person who thought of all of these things the first moments they looked at me.
But at least genetic predispositions like height are visible to the naked eye and no one can dispute the differences. When it comes to differences in the brain it's where we ignorantly proclaim that things are obscure therefore they can violate the very facts of observable nature.
In sort, not only I fully agree with you, but I also agree with the obvious double standards in society around it. If I take ADHD medication and that helps with my focus to improve my performance in school or work then I deserve that success as much as someone who naturally had no problems with ADHD. Why is this different for looks (like hair transplants, etc.) is beyond me.
What I find amusing with this argument is that, no one ever brought power savings when e.g. used "let me google that for you" instead of giving someone the answer to their question, because we saw the utility of teaching others how to Google. But apparently we can't see the utility of measuring the oversold competence of current AI models, given sufficiently large sampling size.
Clippy only helped with very specific products, and was compensating for really odd UI/UX design decisions.
LLM's are a product that want to data collect and get trained by a huge amount of inputs, with upvotes and downvotes to calibrate their quality of output, with the hope that they will eventually become good enough to replace the very people they trained them.
The best part is, we're conditioned to treat those products as if they are forces of nature. An inevitability that, like a tornado, is approaching us. As if they're not the byproduct of humans.
If we consider that, then we the users get the shorter end of the stick, and we only keep moving forward with it because we've been sold to the idea that whatever lies at the peak is a net positive for everyone.
That, or we just don't care about the end result. Both are bad in their own way.
One can assume that, given the goal is money (always has been), the best case scenario for money is to make it so the problem also works as the most effective treatment. Money gets printed by both sides and the company is happy.
>People exaggerate the problems of using a stable distro.
Stability isn't a problem, it's a feature. Companies trust Debian, Ubuntu LTS, etc. for their servers EXACTLY because the packages are old.
This isn't the case with desktop computers, where the latest optimizations are delivered weekly if not monthly, and may improve performance across the board.
Every time I read an LLM's response state something like "I'm sorry for X", "I'm happy for Y" reminds me of the demons in Frieren, where they lacked any sense of emotion but they emulated it in order to get humans respond in a specific way. It's all a ploy to make people feel like they talk to a person that doesn't exist.
And yeah, I'm aware enough what an LLM is and I can shrug it off, but how many laypeople hear "AI", read almost human-like replies and subconsciously interpret it as talking to a person?
It's not about what the company uses, but how informed the technical people responsible for hiring candidates are around the ecosystem they claim they work with.
Example:
Expected: "Oh, you're on Linux? I heard about Rider. We use Windows and Visual Studio here for parity. You're okay with that, right?" (me: Obviously, tools are tools)
Actual: "Does .NET run on Linux? What is Rider?"
I mean, .NET has been running on Linux since forever now (11 years according to https://news.ycombinator.com/item?id=9459513, let's say about 9 for stability because I feel generous). How do they not know about it?
Every time I read about new .NET version improvements I always remember my attempt to get a job using this stack in my local job market (Greece), where .NET Framework is super prevalent, majorly used by classic companies that don't even give you a fair technical chance if you lack a degree, and the devs are considered to be a cost center.
I really, REALLY wish I was in another timeline where I could say in an interview "yes, I use Linux on my desktop and Rider for my IDE" without being seen as a traveler from outer space.
I enjoy working with modern C# way more than node.js but... that's it.
When I was in high school, I would see the algebra teacher work through expressions and go "ohhh, that makes sense". But when I got back home to work with the homework, I couldn't make the pieces fit.
Isn't that the same? Just because you recognize something someone else wrote and makes you go "ohh, I understand it conceptually" doesn't mean that you can apply that concept in a few days or weeks.
So when the person you responded to says:
>almost overnight *my abilities* and throughput were profoundly increased
I'd argue the throughput did but his abilities really weren't, because without the tool in question you're just as good as before the tool. To truly claim that his abilities were profoundly increased, he has to be able to internalize the pattern, recognize the pattern, and successfully reproduce it across variable contexts.
Another example would be claiming that my painting abilities and throughput were profoundly increased, because I used to draw stick figures and now I can draw Yu-Gi-Oh! cards by using the tool. My throughput was really increased, but my abilities as a painter really haven't.
>and if you’re training an agent for this specific task anyway, you’re effectively locking yourself to that specific LLM in perpetuity rather than a replaceable or promotable worker.
That's ONE of the long games that are currently played, and is arguably their fallback strategy: The equivalent of vendor lock-in but for LLM providers.
Before copilot what I'd do is diagnose and identify the feature that resembles the one that I'm about to build, and then I'd copy the files over before I start tweaking.
Boilerplate generation was never, ever the bottleneck.
I can't even begin to imagine how a 12-year old who discovered how empowering bending the machine to do your will through code feels when, over time, realize that their dream career has been reduced to being an LLM middleman.
I always assumed that general advice targets the average person, without accounting for potential mental health problems. I cannot imagine myself trying to tailor an advice for all neurotypical people out there, because everyone can only share their own experience with the world.
>Turns out just running on autopilot most of the time is the healthier human experience.
I cannot believe that you'd argue for mindful nuance only to end up in such a blatantly general statement that contradicts everything you advocated for. That's without even bothering to argue how much of the time is "most of the time".
I'm kind on the fence, but not with the article. It's true that there are engineers who lean more towards one or the other way. For example, since the author brings up the switch from Neovim to VS Code due to features, I do love using Neovim for my TypeScript and Golang needs. But, if I were to work with Java or C# I'm switching to IntelliJ or Rider.
I believe it's healthier to attain some kind of pure-leaning... centrism(?) if we were to present pure/impure as black/white choices. I find it easier to imagine someone who deeply cares about squeezing performance through min-maxing to suddenly shift gears and deliberately introduce debt and just ship-ship-ship for the sake of pushing the product out, because they know exactly the price of the corner that they're cutting.
So I don't see it as a "you're either this or that" but more like "you should be this, and also be that when it's deemed appropriate".
Because I keep wondering myself if AI is here and our output is charged up, then why am I keep seeing more of the same products but with an "AI" sticker slapped on top of them? From a group of technologists like HN and the startup world, that live on the edge of evolution and revolution, maybe my expectations were a bit too high.
All I see is the equivalent of a "look how fast my new car made me go to the super market, when I'm not too demanding on the super market I want to end up with, and all I want is milk and eggs". Which is 100% fine, but at the end of the day I eat the same omelette as always. In this metaphor, I don't feel the slightest behind, or have any sense of FOMO if I cook my omelette slowly. I guess I have more time for my kids if I see the culinary arts as just a job. And it's not like restaurants suddenly get all their tables booked faster just because everyone cooks omelettes faster.
>It's allowed me to do things that I simply would not have been able to do previously.
You're not the one doing them. Me barking orders to John Carmack himself doesn't make me a Quake co-creator, and even if I micromanage his output like the world's most toxic micromanager who knows better I'm still not Carmack.
On top of that, you would have been able to do previously, if you cared enough to upskill to the point where token feeding isn't needed for you to feel productive. Tons of programmers broke barriers, and solved problems that haven't been solved by anyone in their companies before.
I don't see why everyone claiming that they previously couldn't do something is a bragging point. The LLM's that you're using were trained by the Google results you could've gotten if you Google searched.