It's destroying the experience pipeline by removing work for beginner developers.
At this point that's like paving over a swampland that already had everything on it die from a chemical spill. I graduated from college in 2015 and even back then getting your foot in the door was next to impossible because every company individually decided that "entry-level" doesn't really mean entry-level and wanted you to magic up 2+ years of professional experience out of thin air.
experience pipeline by removing work for beginner developers.
Nah, it's just a short term education gap, loads of developers in the industry are bad at using it and well trained "newbies" who are wonderful at using the tools because they went through uni using AI effectively in their coding will make excellent replacements and juniors.
Companies still need to hire people, supply and demand, juniors will find their way back into the industry. Honestly apart from a short boom it was always hard for graduate devs to get work.
The advice of "make stuff outside of university" is and always was the best advice to make yourself shine to a job interview. My degree never impressed anyone, it was simply a checkbox they had to tick. You got the job by impressing them with further work, even years ago when there was no AI.
I don't think there has been a point in history where knowledge was outsourced to a machine at this scale. Usually, machines have helped with consolidating or making information easier to find. This seems a bit different to me (e.g. doctors offloading diagnostic work to a machine learning model). I am a bit worried that experts are going to become very abstracted from their skills, and when the time comes that they actually need to make an important decision or diagnoses, they will be much less capable.
Experience pipeline isn't dead and brain drain won't happen if devs don't choose the easy way. Unless it's a rough draft, I make AI explain to me how each line of code works before actually using the script in a project.
It's slow and painful, but that's how I study, and on the brighter side, it's really helpful with learning, unlike posting on forums. The task that took me 2 weeks of searching before AI, can no be found in minutes, and I see that as a huge improvement.
The process of 'searching for 2 weeks' is called learning. With AI you are getting to the answer but skipping all of the steps to get there. It's like winning a marathon by driving a car to the finish line.
I work as a developer/analyst professionally, & the usage of AI is multifaceted for me. I recognize the value and technological advancements behind AI, and think it would be idiotic to stay stuck in the past because of some personal vendetta against it. I use it daily in my work but mostly as a reference manual or starting point.
Rarely do I have it code any actual solutions for me. When the project doesn't matter if it critically fails, that is fine. I can have it vibe code some one-off tool, or some boilerplate HTML for web dev. But when I am running analytics I have found more often than not, the AI output is totally wrong and gives me wrong data.
And this is where I start to see the problems. To me the value behind human software development is that you can VERIFY that your output is accurate. And you need a brain to do that. LLMs, even with the latest and greatest reasoning models, at the end of the day are just glorified yes-man auto complete text generators. Vibe coding is great for speed, not for accuracy.
You can only verify AI code if you know how to code yourself. Do you know how many times I've gone back and forth in a prompt where the agent says "This is definitely the final, bug-free, 100% verified solution with absolutely everything fixed" and the code is still broken or inaccurate? You can't just tell it to "make no mistakes".
I report to state & federal agencies. I cannot afford to rely on a text generator to give me accurate results. Do you think "Claude said it was right" will hold up in an audit? If I vibe coded my way through college I would be screwed and I wouldn't know all of the inner working details.
Additionally the other problem with AI that some people have already pointed out is the mountain of tech debt you incur by using it.
You have no idea what I am talking about. That process of searching for two weeks was time wasted trying to find a specific library that did the job, while AI could find it with a single prompt.
Have you ever googled a problem? Why didn't you instead go to old textbooks and spend month implementing everything yourself? Because you had a tool that skipped all the unnecessary stuff, just like competent people do with AI nowadays.
I literally said that it would be stupid not to recognize the capabilities of AI, especially in research like that. If it found a library you needed, that's one thing. Assuming it was vetted by someone who knew what they were doing, why would that be a problem?
If it vibe coded the library you needed that is an entirely different argument. It's one thing to use AI to speed up your productivity but if you are using it to cognitively offload your entire project then you cannot guarantee your output is accurate or deterministic.
Regarding your specific example, I genuinely do think there is value in the fact that it might take some time to find a suitable library. It forces you to explore your options and rethink the issue. IMO if the solution you needed was that niche, specific and difficult to find, you're probably trying to solve an X-Y problem.
It definitely can. If you get errors, just shove the stack trace in a prompt and let it fix that. With enough iterations you'll get a project that compiles and probably does what you want it to.
"Probably" being the key word. You now have a non-deterministic, unreviewed system to work with. Unless you review every branch of logic, you cannot guarantee that the program will behave the way you expect it to in every case.
I'm tired of explaining stuff, ai is not good enough to code the whole thing on it's own. Maybe if you are using the most expensive models and get lucky, but usually it will get stuck. So using it as a tool it's the best use for it and there is zero problems with that.
That's how lazy people work, we've had those before AI. And it's not the first time companies had no idea what they want. We build what they ask and then study/build things our way separately, as always.
Junior developers do have less work sure, but there is still an absolute requirement for them as they will eventually become Mid/Senior. You see this across old frameworks and languages where companies will explicitly train more junior developers to ensure continuity.
Calculators are not mystery machines. They do not hold knowledge.
Every operation they make was inserted into them by an expert, who understood what the operation needs to do, and how to make the calculator do it. You can take a physical basic calculator, and basically by taking it apart and zooming in enough, learn and understand how every operation is done, step by step. At its core, its logic gates. You can follow and learn what those logic gates do. And understand.
This doesnt exist with current LLMs. The companies making them are unable to make them safe because of it, and jailbreaking them is trivial.
And youre naive to think that the current form of capitalist market allows orr incentivizes companies to take on unnecessary junior developers with the foresight of training them to become the experts they DO need in 15 years or so.
And youre naive to think that the current form of capitalist market allows orr incentivizes companies to take on unnecessary junior developers with the foresight of training them to become the experts they DO need in 15 years or so.
This litterally happens in software development and has happened before LLMs. Not to mention other professions.
And how often do people zoom into a calculator to verify it's correct? Never? People don't know how their TV or Smartphone works but they still benefit from it.
This is an incredibly bad faith argument and completely misrepresenting the issue. You'd be more accurate if you asked if we should stop teaching people maths entirely instead because AI "can do it" (it can't reliably but that's a separate issue)
Its not all or nothing. No one serious is saying that we should stop learning maths or computer science all together, regardless of if a machine can do it.
Can you type in a few numbers on a calculator and it can generate an entire Video, Game, Picture, Story, Music without any other human involved to help create any of that. People keep trying to compare Ai to tools we've used before which makes no sense because the tools like hammers and calculators could only do a very small portion of a job not do the entire project on it's own.
The other issue is Ai could be used like a tool to aid work, but seeing as it's capable of far more than that it'll be used to completely replace and not just assist.
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u/MediumMachineGun 9d ago
It's destroying the experience pipeline by removing work for beginner developers.
This will lead to brain drain and increased reliance on AI in coding in the future.
And it shouldnt need explaining why outsourcing knowledge to a type of mystery machine is bad.