Adoption of AI at a FOMO corporate pace doesn't seem to include this consideration. They largely want your skills to atrophy as you instead beep boop the AI machine to do the job (arguably) faster. I think they're wrong and silly and any time they try to justify it, the words don't reconcile into a rational series of statements. But they're the boss and they can do the thing if they want to. At work I either do what they want in exchange for money or I say no thank you and walk away.
Which led me to the conclusion I'm currently at: I think I'm mostly just mourning the fact that I got to do my hobby as a career for the past 15 years, but that’s ending. I can still code at home.
I saw something similar in ML when neural nets came around. The whole “stack moar layerz” thing is a meme, but it was a real sentiment about newer entrants into the field not learning anything about ML theory or best practices. As it turns out, neural nets “won” and using them effectively required development and acquisition of some new domain knowledge and best practices. And the kids are ok. The people who scoffed at neural nets and never got up to speed not so much.
Edit: as an aside, I have learned plenty from reviewing coding agent generated implementations of various algorithms or methods.
Well, it's not. There's a small moat around that right now because the UX is still being ironed out, but in a short while able to use coding agents will be the new able to use Excel.
What will remain are the things that already differentiate a good developer from a bad one:
- Able to review the output of coding agents
- Able to guide the architecture of an application
- Able to guide the architecture of a system
- Able to minimize vulnerabilities
- Able to ensure test quality
- Able to interpret business needs
- Able to communicate with stakeholders
I think, most likely, you'll still need developers in the mix to make sure the development is going right. You can't just have only business people, because they have no way to gauge if the AI is making the right decisions in regards to technical requirements. So even if the AI DOES get as good as you're saying, they wouldn't know that without developers.
For some definition of work, yes, not every definition. Their product is not without flaw, leaving room at for improvement, and room for improvement by more than only other AI.
> There are no vulnerabilities
That's just not true. There's loads of vulnerabilities, just as there's plenty of vulnerabilities in human written code. Try it, point an AI looking for vulns at the output of an AI that's been through the highest intensity and scrutiny workflow, even code that has already been AI reviewed for vulnerabilities.
That probably won’t be necessary in a few years.
Probably even more valuable than code that just worked, because evidently we have enough of that and AI code still has issues.
I fail to see how we transition society into a positive future without supplying means of verifying systemic integrity. There is a reason that Upton Sinclair became famous: wayward incentives behind closed doors generally cause subpar standards, which cause subpar results. If the FDA didn't exist, or they didn't "review the output", society would be materially worse off. If the whole pitch for AI ends with "and no one will even need to check anything" I find that highly convenient for the AI industry.
As a simple use-case, I've found LLMs to be much better than me at macro programming, and I don't really need to care about what it does because ultimately the constraint is just that it bends the syntax I have into the syntax I want, and things compile. The details are basically irrelevant.
But if you peel back that layer to the point where you are no longer discussing the code, and just saying "code X that does Y"... how big is X going to get without verifying it? This is a basic, fundamental question that gets deflected by evaluating each case where AI is useful.
When you stop being specific about what the AI is doing, and switch to the general tense, there is a massive and obvious gap that nobody is adequately addressing. I don't think anyone would say that details are irrelevant in the case of life-threatening scenarios, and yet no one is acknowledging where the logical end to this line of thinking goes.
I use LLMs with best practices to program professionally in an enterprise every day, and even Opus 4.6 still consistently makes some of the dumbest architectural decisions, even with full context, complete access to the codebase and me asking very specific questions that should point it in the right direction.
I just went “hmmm, nice” and went on. The problem there is that I didn’t get that sense of accomplishment I crave and I really didn’t learn anything. Those are “me” problems but I think programmers are collectively grappling with this.
Complexity is not just a matter of reducing the complexity of the code, it's also a matter of reducing the complexity of the problem. A programmer can do the former alone with the code, but the latter can only be done during a frank discussion with stakeholders.
A vibe coder using an LLM to generate complexity will not be able to tell which complexity to get rid of, and we don't have enough training data of well-curated complexity for LLMs to figure it out yet.
Overall, we are trying to "silo" LLM-generated code into its own services with a well-defined interface so that the code can just be thrown away and regenerated (or rewritten by hand) because maintaining it is so difficult.
I'm relieved to hear this because the LLM hype in this thread is seriously disorienting. Deeply convinced that coding "by hand" is just as defensible in the LLM age as handwriting was in the TTY age. My dopamine system is quite unconvinced though, killing me.
If it does go as far that way as many seem to expect (or, indeed, want), then most people will be able to do it, there will be a dearth of jobs and many people wanting them so it'll be a race to the bottom for all but the lucky few: development will become a minimum wage job or so close to that it'll make no odds. If I'm earning minimum wage it isn't going to be sat on my own doing someone else's prompting, I'll find a job that involves not sitting along in front of a screen and reclaim programming for hobby time (or just stop doing it at all, I have other hobbies to divide my time between). I dislike (effectively) being a remote worker already, but put up with it for the salary, if the salary goes because “AI” turns it into a race-to-the-bottom job then I'm off.
Conversely: if that doesn't happen then I can continue to do what I want, which is program and not instruct someone else (be it a person I manage or an artificial construct) to program. I'm happy to accept the aid of tools for automation and such, I've written a few of my own, but there is a line past which my interest will just vanish.
No one will be eager to employ “ai-natives” who don’t understand what the llm is pumping out, they’ll just keep the seasoned engineers who can manage and tame the output properly. Similarly, no one is going to hire a bunch of prompt engineers to replace their accountants, they’ll hire fewer seasoned accountants who can confidently review llm output.
Or other people who just kept their research dataset private and milked it for years training incrementally better ML models on the same data. Then similar datasets appeared openly and they threw a hissy fit.
Usually there are a million little tricks and oral culture around how to use various datasets, configurations, hyperparameters etc and papers often only gave the high level ideas and math away. But when the code started to become open it freaked out many who felt they won't be able to keep up and just wanted to keep on until retirement by simply guarding their knowledge and skill from getting too known. Many of them were convinced it's going to go away. "Python is just a silly, free language. Serious engineers use Matlab, after all, that's a serious paid product. All the kiddies stacking layers in Theano will just go away, it's just a fad and we will all go back to SVM which has real math backing it up from VC theory." (The Vapnik-Chervonenkis kind, not the venture capital kind.)
I don't want to be too dismissive though. People build up an identity, like the blacksmith of the village back in the day, and just want to keep doing it and build a life on a skill they learn in their youth and then just do it 9 to 5 and focus on family etc. I get it. But wishing it won't make it so.
Talented, skilled people with good intuition and judgements will be needed for a long time but that will still require adapting to changing tools and workflows. But the bulk of the workforce is not that.
Tailored to my workflow, style, goals, projects and as close as possible to what I think is how an agent should work. I’m deliberately only using an existing agent as a rubber duck.
It’s a very empowering learning experience.
I agree if that's all you can do. Using a coding agent to complement a valuable domain-specific skill is gold.
At least when you're talking about shipping software customers pay for, or debugging it, etc. Research, narrow specializations, etc may be a different category and some will indeed be obsoleted.
It’s also the most important capability engineering orgs can be working on developing right now.
Software Engineering itself is being disrupted.
There's so much hand wringing about people not understanding how LLMs work and not nearly enough hand wringing about people not understanding how computer systems work.
Doing so will effectively force a (potentially unwanted) career change for many people and will lead to the end of software engineering (and software as a career), assuming AI continues to improve.
"Effectively" using agents means that you're writing specs and reading code (in batches through change diffs) instead of writing code directly. This requires the ability to write well (or well enough to get what you want from the agent) and clearly communicate intent (in your language of choice, not code; very different IMO).
The way that you read code is different with agents as well. Agents can produce a smattering of tests alongside implementation in a single turn. This is usually a lot of code. Thus, instead of red-green-refactor'ing a single change that you can cumulatively map in your head, you're prompt-build-executing entire features all at once and focusing on the result.
Code itself loses its importance as a result. See also: projects that are moving towards agentic-first development using agents for maintenance and PR review. Some maintainers don't even read their codebases anymore. They have no idea what the software is actually doing. Need security? Have an agent that does nothing but security look at it. DevOps? Use a DevOps agent.
This isn't too far off from what I was doing as a business analyst a little over 20 years ago (and what some technical product managers do now for spikes/prototypes). I wrote FRDs [^0] describing what the software should do. Architects would create TRDs [^1] from those FRDs. These got sent off to developers to get developed, then to QA to get bugs hammered out, then back to my team for UAT.
If agents existed back then, there would've been way fewer developers/QA in the middle. Architects would probably do a lot of what they would've done. I foresee that this is the direction we're heading in, but with agents powered by staff engineers/Enterprise Architects in the middle.
> Edit: as an aside, I have learned plenty from reviewing coding agent generated implementations of various algorithms or methods.
People learn differently. I (and others) learn from doing. Typing code from Stack Overflow/Expertsexchange/etc instead of pasting it, then modifying it is how I learned to code. Some can learn from reading alone.
[^0]: https://www.modernanalyst.com/Resources/Articles/tabid/115/I...
> As it turns out, neural nets “won”
> The people who scoffed at neural nets and never got up to speed not so much.
I get the feeling you don’t know what you’re talking about. LLMs are impressive but what have they “won” exactly? They require millions of dollars of infrastructure to run coming around a decade after their debut, and we’re really having trouble using them for anything all that serious. Now I’m sure in a few decades’ time this comment will read like a silly cynic but I bet that will only be after those old school machine learning losers come back around and start making improvements again.
Every company I've ever worked at has genuinely believed in and invested in improving developer skills.
It seems they were correct not to invest in your skills.
I've worked for six companies over almost 20 years. The majority invested in my skills, and I hope that investment has paid off for them!
Hanging around for a while (a long while) doesn't necessarily mean dedication worth investing in, it could just be that I have a shocking lack of ambition :)
What is more likely with the 35 number is that these are multiple simultaneous contracts. When working as a contractor you're fixing that problem or that project. The company isn't going to have you around for longer than a month after it's been fixed and documented.
There's no reason to spend company resources on training a person any more than there's reason for you to pay a plumber to be reading "learn to be an electrician in 10 days" while they're supposed to be working on fixing the sink or doing the plumbing for new construction.
You just spent $250k and 5 years in college learning stuff.
You get hired to do a job for money.
What "investment" do you expect company to do?
Give me number of weeks and amount of dollars per year and tell me how it stacks against $250k and 5 years that you just spent?
If you want to learn on the job, shouldn't YOU be paying the company for teaching you, like you pay college to teach you?
In my experience, a lot of the Rust fighting with the borrow checker is really just enforcing better quality code I should've been writing anyway.
(To explicitly state the obvious: I'm not saying OP's a bad person for doing this, just saying the employers were right not to invest in them...)
I can't understand what people are looking for when they talk about lack of investment into training for engineers. It's not the kind of job where someone can train you. It's like an executive complaining they aren't trained. You're the one who's supposed to be coming up with answers and making decisions. You need to spend time on self-motivated learning/discovering how to better do your work. Every company I've been at big or small assumes that's part of the job.
Book subscriptions and conference travel are quite cheap in comparison.
Guided learning with instant feedback can be much more efficient than just consuming and tinkering on your own. Depends on the topic, the teacher and situation of course. The quality of available material is also all over the place, and not every topic has enough material, or anything at all.
Again I just don't have any idea of what training people expect. The entire job is basically "we might have some idea of what we want to do, but no one here knows the details. Go figure it out."
What kind of guided learning would you want? How to solve problems? That's what 16 years of school was for!
The explosion of stacks means it’s hard to keep everything in your head at once. Lookup is routine but will sink you as a candidate.
Personally not great under the gun in adversarial interviews, so my extensive self learning is not well highlighted.
In US you go to college for 4-5 years and pay $50k per year. Or more.
You pay to learn. A lot of money, a lot of time.
Then you get a job, where the idea is that you get paid for doing work and you expect the employer to do what?
You seem to expect that not only you won't be doing the things you're being paid to do but the employer will pay for your education on company's time.
How many weeks per year of time off do you expect to get from a company?
You'll either say a reasonable number, like 1 or 2, which is insignificant to the time you supposedly spent learnings (5 years). You just spend 250 weeks supposedly learning but 1 or 2 weeks a year is supposed to make a difference?
Or you'll say unreasonable number (anything above 2 weeks) because employment is not free education.
With 35 companies, that would be around 1-2 years per company on average if you are retired or near retirement. I doubt any company is seriously investing in a worker who would likely be gone the next year. Getting lip service seems already good deal at that point.
There is a mismatch between how you would expect industry to work and what my last 30 years has taught me.
> With 35 companies, that would be around 1-2 years per company on average if you are retired or near retirement.
I have been at 4 companies for around 2 years or more. The rest of the positions were either contract or startup or contract-to-hire. The vast majority of engineers seem to settle in and suffer at terrible companies, rather than make moves to better jobs. They also tend to settle at whatever they are assigned and grow their skillsets by their employer's needs, rather than on their own.
Over the last 2 decades, if you stayed somewhere for over 2 years, you better have added concrete skills to your resume and have increased your compensation by over 10%. If that's not on track, look for another job, imo.
Contract-to-hire has been very popular. ie JPMC, credit, medical, adtech, games, big retail, subcontractor shops, to startups (4 of which were acquired). All initiatives to progress the careers of developers is applied more or less company wide because the line between contract-to-hire and fulltime is considered an engineering issue if there is more than hub. If you are a sole contributor, on some satellite project or still considered in training, you might not participate due to scheduling that had already been arranged, but the idea that contractors are excluded is more a possibility than a certainty. Most of the initiatives are little more than maybe someone talking with you every quarter, anyway.
> Getting lip service seems already good deal at that point.
It's strange that people are assuming engineers are treated special because of a resume that nobody looks at after an offer is made - having conducted hundreds of interviews. This must be a very rare thing some people may do.
It's not like I don't speak with ex-coworkers or run into them at times - eg one guy I taught Java to (at a position where java wasn't required except for a tiny tool), is the team lead at blizzard now. If I was made a pariah, I would hear about it over the years.
There doesn’t seem to be a plan for maintaining that culture.
Doesn't credentialism kinda throw a spanner in that - where it's not enough to have people with a good track record of solving issues, but then someone along the way says "Yeah, we'd also like the devs who'll work on the project to have Java certs." (I've done those certs, they're orthogonal to one's ability to produce good software)
Might just be govt. projects or particular orgs where such requirements are drawn up by dinosaurs, go figure (as much as I'd love software development to be "real" engineering with best practices spanning decades, it's still the Wild West in many respects). Then again, the same thing more or less applies to security, a lot of it seems like posturing and checklists (how some years back the status quo was that you'll change your password every 30-90 days because IT said so) instead of the stuff that actually matters.
Not to detract from the point too much, but I've very much seen people not care about solving problems and shipping fast as stuff like that, or covering their own asses by paying for Oracle support or whatever (even when it gets in the way of actually shipping, like ADF and WebLogic and the horror that is JDeveloper).
But yeah, I think many companies out there don't care that much about the individual growth of their employees that much, unless they have the ability to actually look further into the future - which most don't, given how they prefer not to train junior devs into mid/senior ones over years.
Back in the day, there were more or less two consumer flight sims: MS Flight Simulator and XPlane. MSFS was and has always been the much prettier one, much easier to work with; xplane is kludgy, very old-school *NIX, and chonky in terms of resource usage. I was doing some work integrating flight systems data (FDAU/FDR outputs) into a cheaper flight re-creation tool, since the aircraft OEM's tool cost more than my annual salary. Hmm, actually, ten years of my salary.
So why use xplane at all, then?
The difference was that MSFS flight dynamics was driven from a model using table-based lookup that reproduced performance characteristics for a given airframe, whereas xplane (as you might be able to tell from the company name, Laminar Research) does fluid and gas simulation over the actual skin of the airframe, and then does the physics for the forces and masses and such.
I caught some flack for going with xplane: "Why not MSFS!? It's so much prettier!"
Unless the airframe is in a state that is near-equivalent with tabular lookup model, the actual flight is not going to be actually re-created. A plane in distress is very often in a boundary state- at best. OR you might be flying a plane that doesn't really have a model, like, say, a brand new planform (like the company was trying to develop). Without the aerodynamic fundamentals, the further away you get from the model represented by the tabular lookups, the greater the risk gets.
And how does this relate?
Those fundamentals- aerodynamic or mathematical or electrical- will be able to deal with a much broader range than models trained on existing data, regardless of whether or not they are LLMs or tabular lookups. If we rely on LLMs for aerodynamics, for chemistry, for electrical engineering, we are setting ourselves up for something like the 2008 Econopalypse except now it affects ALL the physical sciences; a Black Swan event that breaks reality.
I am genuinely worried we're working outselves into just such an event, where the fundamentals are all but forgotten, and a new phenomenon simply breaks the nuts and bolts of the applied sciences.
As for my xplane selection, it helped in other ways. Because often the FDR data is just plain wrong, but with xplane you could actually tell, because a control surface sticking out one way, while the flight instruments say another, lights up a "YOU GOT PROBLEMS" light in the cockpit as the aircraft inexplicably lurches to the right.
It could hardly have been a hobby if people were willing to pay you for it (and good rates too)?
I will rephrase it like this - the market has shifted away from providing value to the customers of said companies to pumping itself instead and it does not need to employ people for that. Simple as.
What's valuable to a company is not necessarily what's valuable to the customers or even more so, to a civilization at large.
Managers at companies are just doing what they've optimized their careers for: maintaining some edge over some competition, at some cost. What is pure FOMO to you or me, is good strategy to anyone trying to win [1]. In other words, FOMO was always the strategy.
This self-reinforcing loop is also not going away. There hasn't been any real evidence that any part of knowledge work, including coding, cannot be automated [2]. Even if human-level quality or cost-effectiveness takes 10 more years, all tasks are functionally solved or about to be. I don't like it, but it's true.
The big problem is that the people who are removed from this loop, who have the time to understand its effects and the power to make changes, are doing fuck-all.
So, whether the loop stops for a while or speeds up even more, we're fucked until we figure out how to detach full-time employment from survival.
[1] I believe this is called meta in PvP games; even if you want to subvert the meta, you gotta know it well first.
[2] Although it could just be my impression, and I'd be happy to be proven otherwise.
We are at the point where sure ai can write code, but we could always do that; lack of code writing ability was not what killed the OOP automation efforts. There was plenty ability to code back then as well. The distinction of whether it’s an offshore team in India or Claude writing the code doesn’t change things as far as the larger picture of building the software.
I do use Claude code at home maybe a couple hours a week, mostly for code base exploration. Still haven’t figured out how to fully vibe code: the generated code just annoys me and the agents are too chatty. (Insert old man shaking fist at cloud).
With how much some people spend on tokens that they've shared on here, and concerns about raising prices, I've kind of been wondering if we're actually heading to a point where seniors who don't use AI are going to be cheaper than juniors who do.
And executives will get millions in bonuses for figuring it out, and the remaining programmers, probably one or two, will raise their necks over who's the best prompter and how everyone else was dumber than them for not figuring it out.
I’ve eyerolled way less with Codex CLI and the GPT models than with Claude.
Yet every company does it, except the worst sweatshops.
There should be thousands or tens of thousands people worldwide that can build the operating systems, virtual machines, libraries, containers, and applications that AI is built on. But the number will dwindle and we'll ironically be unable to build what our ancestors did, utterly dependent on the AI artifacts to do it for us.
God I hope it doesn't all crash at once.
Before it was "hey $senior_programmer where's the $thing defined in this project?", which either required a dedicated person onboarding or someone's flow was interrupted - an expected cost of bringing up juniors.
Now a properly configured AI Agent can answer that question in 60 seconds, unblocking the Junior to work on something.
And no, it doesn't mean Juniors or anyone else get to make 10k line PRs of code they haven't read nor understand. That's a very different issue that can be solved by slapping people over the head.
> The problem is that juniors given access to AI don't seem to learn as much.
What you could do is encourage (or force with IT's assistance) them to use a prompt (or hook or whatever) that refuses to do work for them, but instead telling them where to change and what without actually doing the work.
It will be the same with software. AI will be writing and consuming most software. We will be utilizing experiences built on top of that, probably generated in real time for hyper personalization. Every app on your phone will be replaced by one app. (Except maybe games, at least for a short while longer).
Everyone's treating writing code as this reverent thing. No one wrote code 100 years ago. Very few today write assembly. It will become lost because the economic neccesity is gone.
It's the end of an era, but also the beginning of a new one. Building agentic systems is really hard, a hard enough problem that we need a ton of people building those systems. AI hardware devices have barely been registered, we need engineers who can build and integrate all sorts of systems.
Engineering as a discipline will be the last job to be automated, since who do you think is going to build all the worlds automation?
How does building agentic systems, a "really hard" problem, not just end up a "regular code" problem? Because that is what it is. A distributed systems problem with non-deterministic run lengths. How do you switch agent contexts? Similar to how you solve regular program context switching. How do you search tool capabilities and verify them? How do you effectively manage scheduled tasks?
Oh, look, you've just invented the operating system kernel. Suddenly, those 'dozen or two' experts don't seem so archaic after all!
You're low by several orders of magnitude. "The 2025 development cycle saw 2,134 developers contribute to [Linux] kernel 6.18" [1]
[1] https://commandlinux.com/statistics/linux-kernel-contributor...
Also, 200 years ago we didn't have bike mechanics. Car mechanics. Boat mechanics. Plumbers. Electricians. Not all new professions fade away.
I have been coding long before internet and before there were huge demand for software devs..and I would be coding even after there is no demand for the same.
I have a hard time believing any tenured developer is not actually learning things when using LLMs to build. They make interesting choices that are repeatable (new CLIs I didn't even know existed, writing scripts to churn through tricky data, using specific languages for specific tasks like Go for concurrently working through large numerous tasks, etc.)
Anyone not learning things via LLM coding right now either doesn't care at all about the underlying code/systems, or they had no foundational knowledge or interest in programming to begin with (which is also a valid way to use these tools, but they don't work very well without guidance for too long [yet]).
I've vibe coded plenty. I mostly don't look at the crap coming out. Don't want to. When I do I absorb a tiny bit, but not enough to recreate the thing from scratch. I might have a modicum more surface-level knowledge, but I don't have deep understanding and I don't have skills. To the extent that I've fixed or tweaked AI-generated code, it's not been to restructure, rearchitecture, or refactor. If this is all I did day in and day out, my entire skillset would atrophy.
This is pretty much my point. I use LLMs to code _and_ to learn. I read everything that comes out. Half of it is wrong or incomplete. The other half saved me a bunch of time and taught me things.
I vividly remember understanding how calculus works after watching some 3blue1brown videos on youtube, but once I looked at some exercises I quickly realized I was not able to solve them.
Similar thing happens with LLMs and programming. Sure I understand the code but I'm not intimately familiar with it like if I programmed it "old school".
So yes, I do learn more but I can't shake the feeling that there is some dunning kruger effect going on. In essence I think that "banging my head against the wall" while learning is a key part of the learning process. Or maybe it's just me :D
Once we addressed that, he did great solo. Working the mechanics of the problems with the notes helped, but it was getting independent understanding of the reason for each step that put everything together for him.
How many bytes is a pointer in C? How many bytes is a shared pointer in C++? What does sysctl do? What about fsync?
What is a mutex lock? How is it different from a spin lock?
You want to find the n nearest points to a given point on a 2-D Cartesian plane. Could you write the code to solve that on your own?
Can you answer any of these questions without searching for the answer?
I don't use LLMs and I learn things fine. Always have. For several decades. I care deeply about the underlying code and systems. It annoys me when people say they do and they cannot even understand how the computer works. I'm fine with people having domain-specific knowledge of programming: maybe you've only been interested in web development and scripting DOM elements. But don't pretend that your expertise in that area means you understand how to write an operating system.
Or worse: that it prevents you from learning how to write an operating system.
You can do that without an LLM. There's no royal road. You have to understand the theory, read the books, read the code, write the code, make mistakes, fix mistakes, read papers, talk to other people with more experience than you... and just write code. And rewrite it. And do it all again.
I find the opposite is true: those who use LLM coding exclusively never enjoyed programming to begin with, only learned as much as they needed to, and want the end results.
There are always going to be people who just want the end result. The only difference now is that LLM tools allow them to get much closer to the end result than they previously were able to. And on the other side, there are always going to be people who want to _understand_ what's happening, and LLMs can help accelerate that. I use LLMs as a personalized guide to learning new things.
In the same way that googling for an SEO article's superficial answer ends up meaning you never really bother to memorize it, "ask chat" seems to lead to never really bothering to think hard about it.
Of course I google things, but maybe I should be trying to learn in a way that minimizes the need. Maybe its important to learn how to learn in way that minimizes exposure to sycophantic average-blog-speak.
To those reading this thread though, be wary of the answers LLMs generate: they're plausible sounding and the LLM's are designed to be sycophants. Be wary, double check their answers to your queries against credible sources.
And read the source!
If you make a pizza from scratch but you used canned sauce was it from scratch? What if you used store bought dough? What if you made the sauce and the dough but you didn't grow the tomato?
That's only a brief moment in time. We learned it once, we can learn it again if we have to. People will tinker with those things as hobbies and they'll broadcast that out too. Worst case we hobble along until we get better at it. And if we have to hobble along and it's important, someone's going to be paying well for learning all of that stuff from zero, so the motivation will be there.
Why do people worry about a potential, temporary loss of skill?
Like, yeah, you have the resources right now to boot strap your knowledge of most coding languages. But that is predicated on so many previous skills learn through out your life, adulthood and childhood. Many of which we take for granted. And ultimately AI/LLM's aren't just affecting developers, they are infecting all strata of education. So it is quite possible that we build a society that is entirely dependent on these LLM's to function, because we have offloaded the knowledge from societies collective mind... And getting it back is not as simple as sitting down with a book.
Society can replace the systems it relies on. The replacement might not be the best, but it'll probably handle things until we can reinvent a newer, better system. It probably won't be easy, but you can't convince me that humanity suddenly cannot adapt and fix problems right in front of them. How long does history have us doing that?
These are extraordinary claims that all of society will just become dumb and not be able to do any of this. History is also littered with people fretting about the next generation not being smart enough or whatever, and those fears rhyme pretty closely with what we're talking about here.
Maybe humans will still be here in a century. But you won't be. It didn't have to be this way.
The COBOL thing seems to be working out just fine last I heard. Today a small number of people get paid well to know COBOL's depths and legacy platforms/software. The world moved on, where possible, to lower cost labor and tools.
Arguably, that outcome was the right creative destruction. Market economics doesn't long-term incentivize any other outcomes. We'll see the arc of COBOL play out again with LLM coding.
While LLMs have become pretty good at generating code, I think some of their other capabilities are still undersold and poorly understood, and one of them is that they are very good at porting. AI may offer the way out for porting COBOL finally.
You definitely can't just blindly point it at one code base and tell it to convert to another. The LLMs do "blur" the code, I find, just sort of deciding that maybe this little clause wasn't important and dropping it. (Though in some cases I've encountered this, I sometimes understand where it is coming from, when the old code was twisty and full of indirection I often as a human have a hard time being sure what is and is not used just by reading the code too...) But the process is still way, way faster than the old days of typing the new code in one line at a time by staring at the old code. It's definitely way cheaper to port a code base into a new language in 2026 than it was in 2020. In 2020 it was so expensive it was almost always not even an option. I think a lot of people have not caught up with the cost reductions in such porting actions now, and are not correctly calculating that into their costs.
It is easier than ever to get out of a language that has some fundamental issue that is hard to overcome (performance, general lack of capability like COBOL) and into something more modern that doesn't have that flaw.
The salaries were ok but not good for COBOL.
Here's an anecdotal Reddit thread about it. https://www.reddit.com/r/developpeurs/comments/1ixfpsx/le_sa...
Yes we can but there is a big problem here. We will "learn it again" after something breaks. And the way the world currently functions there might not be a time to react. It is like growing food on industrial scale. We have slowly learned it over the time. If it breaks now with the knowledge gone and we have to learn it again it will end the civilization as we know it.
How many people do you think know how to do that today? It's in the millions (probably 10s to 100s), scattered all across the globe because we all need to eat. Not to mention all of the publications on the topic in many different languages. The only credible case for everyone forgetting how to farm is nuclear doomsday and at that point we'll all be dead anyway.
>If it breaks now with the knowledge gone and we have to learn it again it will end the civilization as we know it.
I don't think there is a single piece of technology that is so critical to civilization that everyone alive easily forgets how to do it and there is also zero documentation on how it works.
These vague doomsday scenarios around losing knowledge and crashing civilization just have zero plausibility to me.
Frankly I don't think so. The AI using LLMs is the perpetual motion mechanism scam of our time. But it is cloaked in unimaginable complexity, and thus it is the perfect scam. But even the most elaborately hidden power source in a perpetual motion machine cannot fool nature and should come to a complete stop as it runs out.
It kind of feels like companies are being fooled into outsourcing/offshoring their jr. developer level work. Then the companies depend on it because operational inertia is powerful, and will pay as the price keeps going up to cover the perpetual motion lie. Then they look back and realize they're just paying Microsoft for 20 jr. developers but are getting zero benefit from in-house skill development.
It's not perpetual motion, it's very real capability, you just have to be able to learn how to use it.
What I am saying is that once the high quality training data runs out, it will drop in its capabilities pretty fast. That is how I compare it to perpetual motion mechanism scams. In the case of a perpetual motion machine, it appear that it will continue to run indefinitely. That is analogous to the impression that you have now. You feel that this will go on and on for ever, and that is the scam you are falling for.
That's more a misunderstood study that over time turned into a confidently stated fact. Yes, the model collapses if you loop the output to the input. But no, that's not how it's done.
The reality is that all the labs are already using synthetic training data, and have been for at least a year now. It basically turned out to be a non-issue if you have robust monitoring and curation in place for the generated data.
yea, look up how it is done.
It is exactly how a perpetual motion machine scam would project an appearance of working like using a generator to drive a motor, and the motor driving the generator..something that would obscure the fact that there is energy loss happening along the way....
There is no "conservation of fallacy" law (bad data must conserve it's level of bad), so I'm struggling to connect the dots on the analogy, unless I ignore the fact that training on synthetic data works, is being used, and the models are getting better.
But that is because the synthetic data helped the model capture what was already there in the training data.
But after all such information has been extracted, then it would not be possible to use synthetic data or anything that is derived from the original data to create "new" information for training....
Will the developer of a new programming language be able to reach out to model companies to give a huge amount of training data, ensuring that the models are good at that new language? I don’t think a small team can write enough code, the models already struggle in medium-popularity languages that have years of history. They hallucinate lua functionality sometimes, for example, even though I’m sure there is lots of lua code out there.
So if most people use coding agents, we’re stuck with the current most popular languages because no new language will get past the barrier of having enough code that models can write it well, meaning nobody adopts the new language, etc.
Same thing with libraries and frameworks - technical decisions are already being made based on “is this popular enough that the agents can use it well?” Rather than a newer library that meets our needs perfectly but isn’t in the training data
Is the world any better for them existing? The decline of coding and sw engineering skills in humans from outsourcing the practice of it to AI is it worth it and sustainable long term?
The world is going to be no worse than it was when humans transitioned from writing assembly to writing compilers for high level languages. Assembly is still necessary, but not that often. In the same way writing code is going to become less necessary as tools are going to be written in higher level language in standards and requirements documents instead of code most of the time, with more specific exact coding only occasionally.
Programmers were mostly solving the same plumbing problems over and over in secret because of "proprietary" needs to hide your code, but one million separate integrations of your billing backend with Stripe didn't really add to humanity. We're cutting out the boring middle drudgery and human effort is going to be freed up to work on the edges of human knowledge instead of tromping around in the middle.
When I open some Electron apps I wish we stopped right about there.
People yeating a (shitty) Github clone with Claude in a week apparently can't imagine it, but if you know the shit out of Rails, start with a good a boiler plate, and have a good git library, a solo dev can also build a (shitty) Github clone in a week. And they'll be able to take it somewhere, unlike the llm ratsnest that will require increasingly expensive tokens to (frustratingly) modify.
That's not how you prove that code works properly and isn't going to fail due to some obscure or unforessen corner case. You need actual proof that's driven by the code's overall structure. Humans do this at least informally when they code, AI's can't do that with any reliability, especially not for non-trivial projects (for reasons that are quite structural and hard to change) so most coding agents simply work their way iteratively to get their test results to pass. That's not a robust methodology.
Yes it is. What do you expect, formal verification of a toy GUI library? Get real.
> and isn't going to fail due to some obscure or unforessen corner case.
That's called "a bug", they get fixed when they're found. This isn't aerospace software, failure is not only an option, it's an expected part of the process.
> You need actual proof that's driven by the code's overall structure.
I literally don't.
> Humans do this at least informally when they code, AI's can't do that with any reliability
Sounds like a borderline theological argument. Coding agents one-shot problems a lot more often than I ever did. Results are what matters, demonstrable results.
So? We didn't prove human code "isn't going to fail due to some obscure or unforessen corner case" either (aside the tiny niche of formal verification).
So from that aspect it's quite similar.
>so most coding agents simply work their way iteratively to get their test results to pass. That's not a robust methodology.
You seem to imply they do some sort of random iteration until the tests pass, which is not the case. Usually they can see the test failing, and describe the issue exactly in the way a human programmer would, then fix it.
Human programmers don't usually hallucinate things out of thin air, AIs like to do that a whole lot. So no, they aren't working the exact same way.
Oh, you wouldn't believe how much they do that too, or are unreliable in similar ways. Bullshiting, thinking they tested x when they didn't, misremembering things, confidently saying that X is the bottleneck and spending weeks refactoring without measuring (to turn out not to be), the list goes on.
>So no, they aren't working the exact same way.
However they work internally, most of the time, current agents (of say, last year and above) "describe the issue exactly in the way a human programmer would".
LLM hallucinating is not an edge case. It is how they generate output 100% time. Mainstream media only calls it "hallucination" when the output is wrong, but from the point of view of a LLM, it is working exactly it is supposed to....
If enough of the time it matches reality -- which it does, it doesn't matter. Especially in a coding setup, where you can verify the results, have tests you wrote yourself, and the end goal is well defined.
And conversely, if a human is a bullshitter, or ignorant, or liar, or stupid, it doesn't matter if they end up with useless stuff "in a different way" than an LLM hallucinating. The end result regarding the low utility of his output is the same.
Besides, one theory of cognition (pre LLM even) is of the human brain as a prediction machine. In which case, it's not that different than an LLM in principle, even if the scope and design is better.
One might argue that this is a substitute for metaprogramming, not software developers.
At my own firm, we generally have a rule we do almost everything through metaprogramming.
Objectively, my GitHub clone is still shitty, BUT it got several ways github is shitty out of my way and allowed me to add several features I wanted, no small one of which was GitHub not owning my data.
I don't know the shit out of Rails and I don't want to, I know the shit out of other things and I want the tools I'm using to be better and Claude is making that happen.
It's a little odd the skepticism to the level that people keep telling me I'm delusional for being satisfied that I've created something useful for myself. The opposition to AI/LLMs seems to be growing into a weird morality cult trying to convince everybody else that they're leading unhappy immoral lives. I'm exaggerating but it's looking like things are going in that direction... and in my house, so to speak, here on HN there are factions. Like programming language zealots but worse.
Hobby-project vibe coding is pretty cool (if I'm being honest, its fucking miraculous; this tech is wild) but isn't it clear that there's a problem with the linkedincels, the investors, the management that are all convinced this will remove say 50% of programming jobs? I understand these things have legitimate uses, but I'm at my wits end hearing about how deep understanding, craftsmanship, patience and hard work aren't "results oriented".
There's definitely zealotry developing against AI, but I suspect it is a proportional (if unhelpful) response to the hype machine. Is it really zealotry to insist on the value of your mind and your competence? These people saying you should never "hand write" your code-- how the fuck did the discourse move so much that this isn't a laughably stupid thing to say? "I'm a CEO, and if you aren't using consultants to make your decisions you've already lost"
These people have always been doing this. Starting in the 90s it was outsourcing programming jobs, they were right then, they got more work for less money and you could have less expertise on staff farming out work somewhere else that was cheaper. You also got worse results sometimes. So it goes.
LLMs are making people more powerful and sucking a lot of income off to the people who provide them. Yup. It makes idiot shysters more powerful just the same as it makes experts more powerful.
People are acting like the software engineering industry is full of fine artistry building the finest bespoke tools instead of duct taping rocks to sticks. I'm sorry but there is a tremendous amount of crap out there by people who barely know what they're doing.
Yes new technology empowers idiots, but it also empowers smart people and if you use it well it'll lead to more quality. Yes you're going to have the same problems you had before of someone doing something cheaply competing with someone trying to be careful to build something well. There also will continue to be idiots spouting off about it.
Nothing changed but the tools got more powerful and people are whining complaining about this change this time ruining everything. Like they always have forever.
More and more the bar is being lowered. Don’t fall to brain rot. Don’t quite quit. Stay active and engaged, and you’ll begin to stand out among your peers.
Here's my advice: if there's someone around you who can teach you, learn from them. But if there isn't anyone around you who can teach you, find someone around you who can learn from you and mentor them. You'll actually grow more from the latter than from the former, if you can believe that.
I think there's a broad blindness in industry to the benefits of mentorship for the mentors. Mentoring has sharpened my thinking and pushed me to articulate why things are true in a way I never would have gone to the effort of otherwise.
If there are no juniors around to teach, seniors will forever be less senior than they might have been had they been getting reps at mentorship along the way.
It's purely because of the fact that if you can't teach something, you really don't understand it.
And the act of having to simplify and break down a skill to explain it to others improves your knowledge of it.
I haven't really been a reader, but I can definitely notice when a book/text is "hard". I'm currently reading the old testament, and I understand very little (even the oxford one that has a lot of annotations is hard for me). I like this, because its a measurement of what I don't know (if that makes sense).
I'm trying to decide if my attention span has atrophied, or if I'm just more aware now of my ADD.
Either way, I'm hopeful that my attention span for this kind of reading will grow with practice.
I used to be an avid reader as a child, even as a teenager. That was a long time ago. I'm looking forward to that time when I will have the mental capacity to read long prose again.
But besides that, it's interesting so many people are willing to tailor their entire workflow and product to indeterminate machines and business culture.
I recommend everyone stop using these infernal cloud devices and start with a nice local model that doesn't instantly give you everything, but is quite capabable of removing a select amount of drudgery that is rather relaxing. And as soon as you get too lazy to do enough specifying or real coding, it fucks up your dev environment and you slap yuorself a hundred times wondering why you ever trusted someone else to properly build your artifaces.
There's definitely some philosophy being edged into our spaces that need to be combatted.
The local models are only going to get better, and the improvement curve has to top out eventually. Maybe the cloud models will still give you a few extra percentage points of performance, especially if they're based on data sets that aren't available to the public, but it won't make much difference on most tasks and the local models will have a lot of advantages too.
Most people are outsourcing thinking instead of using it to go deeper. The tools aren’t the problem, the default behavior is.
I have a friend who uses Google Maps to find places, then memorizes the route there and closes the app to navigate because he wants to build a better mental map of our city. Meanwhile, I just check the app every five seconds like a dummy, and my hippocampus stays small.
Really all the research telling us about AI skills atrophy.. We should have guessed from previous experience.
But I’ve never seen anyone follow a GPS so religiously into so many obvious dead ends than elderly Uber drivers.
You’ve let them in and given them power in many aspects of your life without even a whimper of resistance. Of course you’ll accept them as your lords.
> Stay active and engaged, and you’ll begin to stand out among your peers.
Here’s how the rat race looks in the age of AI and how you can stay ahead.
For the record I'm not an ai doomer, but I am pragmatic, and the lack of hope is merely a foundation.
We're obviously in an era where "good enough" is taken so far that, what used to be the middle of the fictional line is not the middle point anymore but a new extreme. You're either someone who cares for the output or someone who cares how readable and easy to extend the code is.
I can only assume this is done on hopeful purpose, with the hope that the LLM's will "only keep improving linearly" to the point where readability and extendability is not my problem by it's "tomorrow's LLM" problem.
You'll still come here, read the comments, see something engaging and want to reply and... feel sad because shakes fist at [datacenter] clouds it's all just bots talking to each other anyway.
Seems lame. Keep talking anyway.
Soon to remove my access entirely to this website.
Turns out it sucks to produce original works when you know that, whereas previously a few people at best might see your work, now it’s a bunch of omniscient robots and maybe half of those original people are using the robots instead.
I'm curious: would you say the feeling of being watched online is making you afraid of some repercussion, or is it something else?
I get a feeling from overall anti-AI sentiment online that a lot of people feel they're entitled to 100% of value created by anything even tangentially related to their person, whether that's some intentional contribution or a random brain fart that happened in the vicinity of someone else doing something useful - and then become resentful they're not "getting their share".
There's hardly any other way to read all the proclamations of quitting to do anything because "cognitive dark forest" (itself a butchering of the original idea of "dark forest" across so many orthogonal dimensions in parallel, that it starts to look like a latent space of a transformer model).
Downloading public stuff off the internet with no regard for the creator's wishes or license is bad enough, but we have many people here who defended AI companies seeding models with pirated content.
The internet is a social contract. AI is not the first thing to try and erode it for profit, but it's by far the most aggressive one.
Licenses are legal documents and are usually treated as such, but "the creator's wishes" are irrelevant without case law, legislation, or licensing to back it up. And jurisdiction - show me a license that doesn't stand up in court in my home jurisdiction and I'll show you a license I won't care if I break or not.
Rather, I don't like that the terms I released my work under aren't being respected. I believe LLMs are derivative works of the pieces they are trained on. I spent more than ten years working on open source code, and now the models that were trained on my GPL'd code are being used to make proprietary code against the terms of the license. I find this reprehensible.
While it wasn't an explicit term of release, generally I did not expect anyone to get any kind of financial value from the blog posts I wrote. I just wrote them for fun & maybe others would find them interesting. Now, LLMs have been trained on my blog posts and are generating financial value for some of the worst human beings on the planet who are using their money to murder, demean, and maim other humans.
I now know that blog posts I wrote for fun are putting money in some sociopath's bank account, and the GPL'd code I wrote is being used to create software to exploit me & other users. If I continue to create things publicly, it will be used against me and other people, and there's nothing I can do to stop it except to stop creating things. It's all very disrespectful & demoralizing.
Writing a blog yes, feeding the beast no.
Isn't this what the free software movement wanted? Code available to all?
Yes, code is cheap now. That's the new reality. Your value lies elsewhere.
You can lament the loss of your usefulness as a horse buggy mechanic, or you can adapt your knowledge and experience and use it towards those newfangled automobiles.
But this is not that. The current situations is closer to "what's yours is mine and what's mine is mine".
I have been releasing my writings under a Creative Commons Attribution-ShareAlike license which requires attribution and that anything built upon the material to be distributed "under the same license as the original". And yet I have no access to OpenAI's built-upon material (I know for a fact they scrape my posts) while they get my data for free. This is so far legal, but it's probably not ethical and definitely not what the free software movement wanted.
Available to all yes. Not available to the giant corpos while the lone hobbyist still fears getting sued to oblivion. In fact that's pretty much the opposite of what the free software movement wanted.
Also the other thing the free software movement wanted was to be able to fix bugs in the code they had to use, which AI is pulling us further and further away from.
Decompiling and re-engineering proprietary code has never been easier. You almost don't even need the source code anymore. The object code can be examined by your LLM, and binary patches applied.
Closed source is no longer the moat it was, and so keeping the source code to yourself is only going to hurt you as people pass you over for companies who realize this, and strive to make it easier for your LLM to figure their systems out.
Jesus christ.
"The people who wanted everyone to have a home should be happy with the invention of the lockpick. You can just find a nice house and open the lock and move in. Ignore the lockpick company charging essentially whatver they want for lockpicks or how they got accesss to everyones keyfob, or the danger of someone breaking into your house"
That is basically your argument. Like AI is a copyright theft machine, with companies owning the entire stack and being able to take away at will, and comitting crimes like decompiling source code instead of clean room is not a selling point either...
The open source community wants people to upskill, people become tech literate, free solutions that grow organically out of people who care, features the community needs and wants and people having the freedom to modify that code to solve their own circumstances.
Stop trying to make this into some abstract argument. It's not an argument anymore. It's already happened.
How one might choose to characterize the reality, is irrelevant. A vast (and growing) amount of source code is more open, for better or worse. Granted, this is to the chagrin of subgroups that had been pushing different strategies.
Agreed.
> Stop trying to make this into some abstract argument.
As you mentioned, it's not an abstract argument. It's statements of fact.
> A vast (and growing) amount of source code is more open...
No, not at all.
1) If you honestly believe that major tech companies will permit both copyright- and license-washing of their most important proprietary code simply because someone ran it through an LLM, you're quite the fool. If someone "trained" an LLM on -say- both Windows 11 and ReactOS, and then used that to produce "ReactDoze" while being honest about how it was produced, Microsoft would permanently nail them to the wall.
2) The LLMs that were trained on the entirety of The Internet are very, very much not open. If "Open"AI and Anthropic were making available the input data, the programs and procedures used to process that data, and all the other software, input data, and procedures required to reproduce their work, then one could reasonably entertain the claim that the system produced was open.
That ship has sailed. The revolution is happening. We live in a new reality now, one where we're still trying to figure out what rules should even be.
And there will be winners and losers, and copyright and patent law will be modified in an attempt to tame the chaos, with mixed results because of all of the powerful players on both ends.
You can live on the front of it for high risk/reward, or at the back for safety. But either way, you're going to exist in this new reality and you need to decide your risk appetite.
yes and lockpicks also exist. Promotting the ability to break into homes when people are talking about the housing crisis is a crazy, short sighted and frankly embarrasing position to take.
And mischaracterising the people in the open source community as belonging to that ideology is insulting.
> A vast (and growing) amount of source code is more open
You are missusing the word open here, for accesible. Having an open house, and breaking into someone's home are not the same thing, even if the door ends up open either way.
> Granted, this is to the chagrin of subgroups that had been pushing different strategies.
Taking unethical shortcuts that ultimately lead to an even worse outcome is not a cause of chagrin, its a cause of deep and utter terror and embarrasment.
Wanting people to own their skills and tech stack and be informed, smart and engaged is a goal that "just ask the robot you dont control to break into a corporate codebase and copy it" is not even remotely close to helping get close to.
The reproduction of the object is essentially free in the internet, but the labour to produce it isn't.
If I spent 3 years making my codebase, and you copy paste the git repo, yeah your access to the information is not going to replace the original. But your labour cost is 0 and you can undercut the 3 years of expense, loans or debt I adquired to produce it.
Btw the FBI murdered Aaron Swartz for attempting to open access to research papers, Mark Zuckemberg admitted to stealing those ssame papers through libgen and showed off the results of Llama and his stock price went up.
I think the piracy argument falls apart when the class warfare and 2 tier justce system is openly weaponised towards open access
Or Oracle for databases.
Or Microsoft for operating systems.
Or DEC for computers.
There are perfectly good open source LLMs and agents out there, which are getting better by the day (especially after the recent leak!)
I want to support RISC V over Intel.
I want other things too, and on balance, Intel+Anthropic is most compliant with my various preferences, even if they're not perfect.
they’re not free in any sense of the word. from price to openness of the models. would openai cry if every bit of their models were wide open for us to use however we see fit? if so, then it’s not free, again, in any definition of the word.
Me boycotting some company's product due to bad practices (slavery, etc).
Response: You know your boycotting isn't going to change anything, right?
Me: Yes, and ....? I'm not trying to change the world.
I don't use FF as some form of protest. It's just a browser I like more.
I'm not anti-AI the way much of HN is, but let's pretend I am. If I ban AI generated content on my site[1], I'm not trying to change the world. Just controlling my site.
Getting more to your sentiment: The world/Internet is a vast place. If even 1000 people think like me, it's more than enough. For a number of years I had valuable online interactions via BBS's with a population < 1000. As long as I get 1000 people, let the rest of the world burn!
It's like the constant "Emacs is dying" threads we used to have on HN, because the percentage of SO users using it kept dropping. When in reality, the absolute numbers kept increasing. Who cares if the world has moved on to VS Code? Emacs as an ecosystem was/is thriving!
[1] Assuming I live in a fantasy world where I can classify content accurately...
I think people are so afraid to do a hecking racism that they start comparing any normal thing to racism. I also think there’s an incentive here: by comparing to racism they potentially gain some social status points like - I’m more morally superior to you because I didn’t do a hecking racism like you.
But it can backfire, like with your comment. People are catching up to how ridiculous this comparison is
Posting your most provocative and strong opinions in reaction to the latest controversy-of-the-week is what fuels the internet and culture more than anything these days. The attention economy demands hot takes mixed with preaching about every new thing.
> (Regardless, why do I keep being told it’s an ‘extreme’ stance if I decide not to buy something?)
> The 1% utility AI has is overshadowed by the overwhelming mediocracy it regurgitates.
This sort of reasoning is why you might have been called extreme.
It's less extreme to say "many people see and/or get lots of benefit, but it's wrong to use the tool due to the harms it has".
There's nothing wrong with extreme, but since you asked.
I was an AI sceptic for a long time until toward the end of last year when I seriously evaluated them, and came to realise it could add tremendous value.
When someone comes along and declares that it's all hype, it goes against my experience that it's getting things done.
I can also see the harm it does, and I hope the tooling improves to reduce that harm. For example, there's a significant lack of caching in the tooling. It's constantly re-reading the same files every day, and more harmfully, constantly fetching the same help pages and blog-posts from the web.
If it had a generous built in HTTP cache, and instruction to maximise use of the cache, then it could avoid a lot of re-fetching of content, which would help reduce the harms.
Declaring my experience to be invalid and based on nothing but hype doesn't engage people like me at all.
And it's the people like me, the middle-of-the-road developer working on enterprise software, that either need convincing to not use the tools, or for our habits to change to minimise the harm.
Because otherwise we're quietly getting on with using it, potentially destroying forests and lakes as we do.
I think the position that ai is morally troubling enough that the downsides out way the positives is perfectly defensible. But the entire argument becomes a joke when you can’t accurately catalog the positives.
While this is a great idea, the harms are somewhat overblown. The big scare number for water consumption includes water used in power generation which itself includes evaporation from hydroelectric power.
Now i still show clean code videos from bob and other old things to new hires and young collegues.
Java got more features, given but the golden area of discovery is over.
The new big thing is ai and i'm curious to see how it will feel to write real agents for my company specific use cases.
But i'm also seeing people so bad in their daily jobs, that I wish to get their salary as tokens to use. It will change and it changes our field.
Btw. "Is there anything, in the entire recorded history of human creation, that could have possibly mattered less than the flatulence Sora produced? NFTs had more value." i disagree, video generation has a massive impact on the industry for a lot of people. Don't down play this. NFTs btw. never had any impact besides moving money from a to b
Oof. The modern "Go away or I will replace you with a very small shell script"
But yeah there is one person made of teflon. Nothing sticks. And i could tell you that teflon person in every company i worked so far.
I’ve never found a way around it, and I don’t want to believe that some people can’t grok this field, but that is what I’ve experienced. Maybe other people can educate better.
I’ve just found that at some point you have to limit the blast radius and move onto more productive uses of your own time.
So while I do worry about AI's impact on blogging/writing/etc., I do think to some extent, you either love the process or you don't. If you only write in order to have readers, you're in the wrong game.
For the vast majority of history it was all community theater, carnies, and “that guy in the square guy who knows the lute”.
Fun fact, in medieval Europe acting was considered a sin so great you could not get a Christian burial, as you were channeling the spirit of others. Realpolitik it was probably because actors were mostly queer in the cities and Roma in the countryside. What’s old is new…
Suppose that I have discovered a novel algorithm that solves an important basic problem much more efficiently than current techniques do. How do I hide it from the web scrapers that will steal it if I put it on GitHub or elsewhere? Should I just write it up as a paper and be content with citations and minor glory? Or should I capture AI search results today for "write me code that does X", put my new code up under a restrictive license, capture search results a day later, demonstrate that an AI scraper has acquired the algorithm in violation of the license, and seek damages?
Unfortunately, that would be considered heresy on forums like HN, and people will continue to rail against AI and whatever it's causing and patents, instead of realizing that one is the only available leverage against the other.
I don't see any proof that software development is not dead. Software engineering is not, and it's much more than writing code, and it can be fun. But writing code is dead, there is no point of doing it if an LLM can output the same code 100x faster. Of course, architecture and operations stays in our hands (for now?).
Initially I was very sceptic, first versions of ChatGPT or Claude were rather bad. I kept holding to a thought that it cannot get good. Then I've spend a few months evaluating them, if you know how to code, there is no point of coding anymore, just instruct an LLM to do something, verify, merge, repeat. It's an editor of some sorts, an editor where you enter a thought and get code as an output. Changes the whole scene.
on the other hand, i can't help but think about ASM coders lamenting C and especially C++. Also, god help you if you tell an embedded developer you use micropython instead of C. Maybe a current chapter is closing and a new one is beginning and my part was in the last chapter just like them.
i'll end with saying i really like using AI for code, it's got me excited about technology again. So many projects that were out of reach due to time ( i have a family + stressful career ) are now back on the table like when i was in college with nothing but time on my hands.
I agree that LLMs produce code that is less good than what a good developer could write, but most developers are not good developers, and even the good developer gets tired and must sleep eventually.
Arguments against LLMs are like the old arguments against high level languages like C. People argued that the compiler wrote trash code, that humans could do better, that the costs weren't worth it. None of that mattered and it's the same story here.
They're not perfect by any stretch but if they're being likened to slot machines for code, I'll take those odds almost every day.
For any serious system you still need to understand and guide the code, and unless you do some of the coding.. You won't. It's just novelty right now is skewing our reasoning.
Also, yes, I know the origin is Star Wars, but it went viral recently a very specific way.
The power of edgelord memes.
Was this how other professionals dealt with their grief? Like a translator in the advent of ML based translations? Like a lift man?
I've come up with a set of rules that describe our reactions to technologies: 1. Anything that is in the world when you’re born is normal and ordinary and is just a natural part of the way the world works. 2. Anything that's invented between when you’re fifteen and thirty-five is new and exciting and revolutionary and you can probably get a career in it. 3. Anything invented after you're thirty-five is against the natural order of things.
A lot of the dissonance on this forum is probably age based.
You can try to avoid consuming AI-generated material, but of course part-way through a lot of things you may wonder whether it is partly AI-generated, and we don't yet have a credible "human-authored" stamp. But you can't really keep them from using your work to make cheap copies of you, or at least reducing your audience by including information or insights from your work in the chat sessions of people who otherwise might have read your work.
For the article it was nice, but the font is really what got me.
Alas I think tech crowd have collectively painted humanity into a corner where not playing is not an option anymore.
The combination of having subverted copyright and enabled cheap machine replication kills large swaths of creativity. At least as a viable living. One can still do many things on an artisanal level certainly and as excited as I am about AI it’s hard not to see it as a big L for humanity’s creative output
There is perhaps some relevance to the analogy however, because the US is designed in such a way that makes walking difficult to impossible. I am already seeing this pattern in vibe-coded areas where engineers will just use AI because it's too difficult to parse and edit by hand.
I didn't. Yesterday I walked 11 km for errands. Today I took a detour when walking to work, a more scenic route with less traffic.
For me walking is not much slower than using public transport (you need to get to it, then from it to the point of your destination), and not much slower than a car (stuck in traffic, finding parking, not to mention the road rage). I'd be faster on a bicycle but I'm not in a hurry and enjoy my walks.
They literally made it a crime to walk down the street.
It's also a crime to jog on the railroad tracks.
"Fighting Traffic" by Peter D. Norton talks about this at length.
The suburbs didn't exist when automobiles hit the market. Most people lived in cities because that's where the jobs were and transportation (outside of whatever public transportation options the cities provided) was limited. Kids and adults used the streets freely (which were for horses, though they were widened as automobiles started growing in popularity).
This changed as cars killed kids (and adults) who didn't know that cars were much faster than cars and didn't react in time. Traffic deaths were so numerous, cities invested lots of money in "safety parades" that were kind of gruesome, actually (like showing tombstones of the future deceased). [^0] Jaywalking was a crime that was invented to deal with exactly this phenomenon.
People fought HARD to keep the streets free (where else are kids going to play). People lost that battle, as we know.
[^0] https://www.bloomberg.com/news/features/2022-06-10/how-citie...
If a wagon or trolley hit someone that was considered the fault of the driver, every time.
When cars started arriving and being driven around by people who were wreckless and bad at it, you started getting manufacturers and "motorists" lobbying for the concept and laws around jay-walking. Even the word was a way to delegitimize what used to be normal. "Jay" was negative slang for country-person (think red-neck). The idea was "modern city people stay out of the streets!"
> The 1% utility AI has is overshadowed by the overwhelming mediocracy it regurgitates.
The only way to write like that is to have a real theory of mind for the two characters and understand that they are four processing speeds: that of both speakers, that of the narrator, and that of the reader.
You don't have to give up on everything to participate, but it can be a space to go to if you're tired of every social interaction being mediated by (I'm being glib) hustlers
In what world is "the media" not an integral, tightly-bound part of the ratchet mechanism that seeks to suppress all distinction?
According to the author AI is 99% hype.
That 1% of AI utility can unlock more for humanity than 99.999% of blogs; static text hosted from a laptop in a closet.
Odd ball position that cheap publishing via the web is a path to The Next Generation for humanity is 100% hype.
Other than feeding dopamine addiction humanity has not improved greatly since we read all those insipid posts on GeoCities no one remembers today.
It's all been 99%+ hype to feed Wall Street. Young GenX and older Millennials with tech jobs were temporary political pawns and gonna end up bag holders like may older GenXers and Boomers who lived through the car boom, the housing boom, the retail boom.
Same old human shit, different hype.
The supposedly starved don't seem to care much for such food. Blogs are kind of a wasteland.
I think most people cannot destinguish between "genuine" creativity and an artificial almalgamation of training data and human provided context. For one, I do not know what already exsists. Some work created by AI may be an obvious rip off of the style of a particular artist, but I wouldnt know. To me it might look awesome and fresh.
I think many of the more human centric thinkers will be disappointed at how many people just wont care.
Pop music is often composed by dozens of people who specialize in a thin sliver of the track - lyrics, vocals, drums, &c. - and then it's given a pretty face and makes the charts. That's really no different than something like Suno.
I think AI is forcing people who thought that THEIR thing was too nuanced or too complex to be replaced by technology to reckon with what makes them special.
And can or will AI create it?
AI is perfect for that. It reveal, perhaps to the dismay of those who revel in high art, that it might be an illusion that art has genuine creativity, if most people find ai to produce acceptable output.
Without AI I would probably never get to them because realistically, I do not have dozens, or hundreds of personal hours to devote to fun, but unnecessary projects.
The back and forth is more annoying now as well. Instead of trying different approaches to code to produce an outcome, I'm prompting "this is broken; can you fix it?" or "this almost works! can you do $x instead" and doing stuff in another window while Claude churns. This isn't fun or stimulating at all for me. It's like carrying a dog to a ball instead of making them run for it.
Using it also reminds me that a big part of the experience I've spent years accumulating is (or feels) no longer useful. That everyone can "write" (produce) code now is a good thing, but SO MUCH TIME AND ENERGY was spent on putting writing and understanding code on a pedestal (especially on this site), and seeing that get torn down while gaslighting us into thinking that this never happened has been affecting my psyche for sure.
There's also the dirty feeling I get from abdicating more and more of my skills to a big company that is probably salivating at the idea of developers not being able to write code without Claude Code anymore.
I have a handful of projects I'd like to work on, but I'd rather leave them on the shelf until I can hand-write them than use agents to finish them and, in doing so, create a codebase that I'm less likely to be able to maintain without agents.
I guess I can turn the question back at you: how aren't you not losing your mind at becoming a glorified spec writer?
The broader corporate world has never wanted code monkeys. They want "boring" reliability and pay a reasonable wage for it. On the other hand, they also won't tolerate contrarians who can't deliver, so maybe some of the fear from people posting this sort of thing really is justified.
I'm really getting tired of the programming obituaries. As if LLMs didn't fail at any complex task, as if they didn't vomit shit code and as if they didn't just copy patterns surrounding the new code, and as if they didn't hallucinate and downright write wrong code or made up libraries. Yet for some reason, every time you bring it up, someone will come along and say "You're not using it right then.", Is it that, or is it just that they're only doing toy projects? I'm led to believe the latter.
At this point I don't know what's organic and what's not. Reddit is filled with astroturfing for big LLM. Maybe this place is too? Even if that was not the case, I'm led to believe that it isn't uncommon for people to swallow up all of the big LLM propaganda and fall into despair, or fall into unrealistic expectations, and just parrot it everywhere else. One thing is for certain, LLM evangelism has all the money of the world, and LLM denial doesn't. It's only natural to think that the balance is tilted in terms of media presence.
Even at the best, or worst, LLMs can't do anything you couldn't do yourself better with a scaffolding prompt + manual editing, and at the end of the day, you still need the cognitive energy to review, veto, come up with, the implementation. What does this exactly do anyways other than saving you a bunch of keypresses? I wonder if the people touting it to be all that really didn't think before LLMs, of just switched their brain off on them.
I used to really like this site, but I think that just consuming the RSS feed is enough for me. I think that lobster.rs has less "trend chasing" point of views these days, and I do wonder if it might be on here there's larger amounts of non technical people jumpy to call for the funeral of things.
You seriously need to go outside and touch grass if you are so defeated by another chess winning machine
Nobody wants to Watch AI play chess, nobody wants to read ai blogposts
AI makes human writing more valuable, not less.
I will pay good money for pure human made books certified as made without a single word auto generated whether in original or during process of Translation.
What AI represents to me is a teacher! I have so long lacked a music teacher and musical tools. I spent my entire career doing invisible software at the lowest levels and now I can finally build cool tools that help me learn and practice and enjoy playing music! Screw all the haters; if you're curious about a wide range of topics and already have some knowledge, you can galavant across a vast space and learn a lot along the way.
AI is a bit of a bullshitter but don't take its bullshit as truth, like you should never take anything your teacher says as gospel. How do we know what's true? The truth of the universe and the world is that underneath it all, it is self consistent, and we keep making measurement errors. The AI is an enormous pot of magic that it's up to you to organize with...your own skills.
You have to actively resist deskilling by doing things. AI should challenge you and reward you, not make you passive.
Use AI to teach yourself by asking lots of questions and constantly testing the results against reality.
For me right now, that's the fretboard.
Therefore, things like writing, film, sales, etc are less productively scalable by bots
And things like code, where people don't care how the sausage is made as long as it "works" are more productively scalable by bots
And even in the situation of code, the job description leans more on defining what "works" which requires the human touch
Setting aside the self delusion that makes a considerable number to erroneously rate themselves above average, the reason you create blog posts should not be for the attention you might gain, there simply are not the eyeballs. You create as a form of self expression, to organise your thoughts, to create a record of them.
AI can never challenge in those areas because it is, as it has always been, the act of creation is the goal.
Might be just me though, but I definitely don’t get why blogging should be the solution.
Imagine having 6 software engineering jobs, each paying maybe $150k a year, all being done by agents.
Hell, I might even do this secretly without their consent. If I can hold just 10 jobs for about 3 or 4 years, I can retire and leave the industry before it all comes crumbling down in 2030.
The problem of course, is securing that many jobs. But maybe agents can help with applying for jobs.
I mean, to put a price tag on enabling vastly more creation than would otherwise have occurred!
Everyone wants to be a famous author, or at least a published/somewhat acknowledged one; few are willing to write their novel and be satisfied with zero or near-zero sales/readings.
But that is exactly what you need to do, especially in the age of AI. Everyone who was "in it to win it" (think linkedinslop which existed before AI) is going to certainly use AI - because they do not give a shit about the quality of themselves - they just want the result.
And you can only become a writer (unpublished, unread, or no) by doing the writing - it takes time (10,000 hours?) that cannot be replaced by AI, just like you can't have the body of a marathon runner without running (yes, yes, the joke). You may be able to get 26 miles and change away, even very fast, but unless you personally do the running of that distance without cheating, you will not get the inherent benefits.
And if you instruct an AI, or another human even, to write for you, you may get some of the results you want, but you won't have changed to become a writer.
We shouldn't celebrate the successful blogs; they're already rewarded enough. It's celebrating the unsuccessful blogs that is needed - even if, frankly, the vast majority of them are sub-AI levels of crap it is still a human changing and progressing behind them.
Babies fall over a lot but unless you take them out of the stroller and let them do so, they'll never progress to crawling, walking, running.
More pretentious gatekeeping from luddites who like to yell at clouds. This is someone who would love a piece of artwork created using ai tools right up until someone told them it was created using ai tools.
There is nothing new about using machinery to automate boring / repetitive tasks, including the wall of resistance that comes up. But it should be clear that genuinely useful tooling and automation tends to become a normal part of life, from the plow, to the printing press, to the dishwasher, to digital video editing, to autocorrect, and now to large language models.
There's a lot that has to be worked out with LLMs in particular as they are now encroaching heavily upon human creativity and thought. This is an extremely important topic. But rants like these with terms like "the plagarism machine" and "the solution is that we all must vow to never use AI in any shape or form" are not really contributing.
Mixed messages fr
Hot take, folks packing it in because of AI probably were not difference makers before AI, and wouldn't be difference makers after it either.
I agree with the author, keep writing. It helps hone your ability to communicate effectively which we all need for some time to come (at least until we become batteries).
Anecdotal but I’ve been seeing a lot of the opposite. Some of those leaning in strongly are being propped up by the tools. Holding onto them like a lifeboat when they would have fallen off earlier.
Thats generated audio. It may not be LLM generated but it's not read by a human.
To draw an arbitrary line between _this kind_ of generated content but not _that kind_ is seemingly a matter of perspective and preferences.
- spend tons of tokens on useless stuff at work (so your boss knows it’s not worth it)
- be very picky about AI generated PRs: add tons of comments, slow down the merge, etc.
Eventually you are faced with company culture that sees review as a bottleneck stopping you from going 100x faster rather than a process of quality assurance and knowledge sharing, and I worry we'll just be mandated to stop doing them.
But the Kool aid has been drunk, and the philosophy of silicon valley cemented in your field. It will take a lot of pain or work to get it to change.
But that's the opposite of sabotage, you're actually helping your boss use AI effectively!
> spend tons of tokens on useless stuff at work (so your boss knows it’s not worth it)
Yes, but the "useless" stuff should be things like "carefully document how this codebase works" or "ruthlessly critique this 10k-lines AI slop pull request, and propose ways to improve it". So that you at least get something nice out of it long-term, even if it's "useless" to a clueless AI-pilled PHB.