New Junior Developers Can’t Actually Code.
New Junior Developers Can’t Actually Code.
Something’s been bugging me about how new devs and I need to talk about it. We’re at this weird inflection point in software development. Every junior dev I talk to has Copilot or Claude or GPT running 24/7. They’re shipping code faster than ever. But when I dig deeper into their understanding of wh...
The problem is not only the coding but the thinking. The AI revolution will give birth to a lot more people without critical thinking and problem solving capabilities.
apart from that, learning programming went from something one does out of calling, to something one does to get a job. The percentage of programmers that actually like coding is going down, so on average they're going to be worse
This is true for all of IT. I love IT - I've been into computer for 30+ years. I run a small homelab, it'll always be a hobby and a career. But yeah, for more and more people it's just a job.
That's the point.
Along with censorship.
As someone who has interviewed candidates for developer jobs for over a decade: this sounds like “in my day everything was better”.
Yes, there are plenty of candidates who can’t explain the piece of code they copied from Copilot. But guess what? A few years ago there were plenty of candidates who couldn’t explain the code they copied from StackOverflow. And before that, there were those who failed at the basic programming test we gave them.
We don’t hire those people. We hire the ones who use the tools at their disposal and also show they understand what they’re doing. The tools change, the requirements do not.
I think that LLMs just made it easier for people who want to know but not learn to know. Reading all those posts all over the internet required you to understand what you pasted together if you wanted it to work (not always but the barr was higher). With ChatGPT, you can just throw errors at it until you have the code you want.
While the requirements never changed, the tools sure did and they made it a lot easier to not understand.
Have you actually found that to be the case in anything complex though? I find it just forgets parts to generate something. Stuck in an infuriating loop of fucking up.
It took us around 2 hours to run our coding questions through chatgpt and see what it gives. And it gives complete shit for most of them. One or two questions we had to replace.
If a company cannot invest even a day to go through their hiring process and AI proof it, then they have a shitty hiring process. And with a shitty hiring process, you get shitty devs.
And then you get people like OP, blaming the generation while if anything its them and their company to blame... for falling behind. Got to keep up folks. Our field moves fast.
But how do you find those people solely based on a short interview, where they can use AI tools to perform better if the interview is not held in person?
And mind you the SO was better because you needed to read a lot of answers there and try to understand what would work in your particular case. Learn how to ask smartly. Do your homework and explain the question properly so as not to get gaslit, etc. this is all now gone.
That's simple. They use an LLM to find the right people for the job /s
Pretty easy to come up with problems that chatGPT is useless at. You can test it pretty easily. Throw enough constraints at it and the transformer starts to loose attention and forget vital parts.
With a bit of effort you can make problems where chatGPT will actuallt give a misleading answer and candidates have to think critically.
Just like in the past it was pretty easy to come up with problems which werent easily found on SO.
Same landscape. If you put in the time and the effort to have a solid recruitment process, you get solid devs. If you have a lazy and shitty process, you get shitty devs.
Evil me: Ask questions to which there is no solution but ChatGPT will happily give incorrect solutions to and will run itself in circles trying to answer correctly as you feed it error messages.
I am not a professional coder, just a hobbyist, but I am increasingly digging into Cybersecurity concepts.
And even as an "amature Cybersecurity" person, everything about what you describe, and LLM coders, terrifies me, because that shit is never going to have any proper security methodology implemented.
On the bright side, you might be able to cash in on some bug bounties.
I've said it before, but this is a 20-year-old problem.
After Y2K, all those shops that over-porked on devs began shedding the most pricey ones; worse in 'at will' states.
Who were those devs? Mentors. They shipped less code, closed fewer tickets, cost more, but their value wasn't in tickets and code: it was investing in the next generation. And they had to go because #numbersGoUp
And they left. And the first gen of devs with no mentorship joined and started their careers. No idea about edge cases, missing middles or memory management. No lint, no warnings, build and ship and fix the bugs as they come.
And then another generation. And these were the true 'lost boys' of dev. C is dumb, C++ is dumb, perl is dumb, it's all old, supply chain exploits don't exist, I made it go so I'm done, fuck support, look at my numbers. It's all low-attention span, baling wire and trophies because #numbersGoUp.
And let's be fair: they're good at this game, the new way of working where it's a fast finish, a head-pat, and someone else's problem. That's what the companies want, and that's what they built.
They say now that relying on Ai makes one never really exercise critical thought and problem-solving, and I see it when I'm forced to write fucking YAML for fucking Ansible. I let the GPTs do that for me, without worrying that I won't learn to code YAML for Ansible. Coding YAML for Ansible is NEVER going to be on my list of things I want to remember. But we're seeing people do that with actual work; with go and rust code, and yeah, no concept of why we want to check for completeness let alone a concept of how.
What do we do, though?
If we're in a position to do so, FAIL some code reviews on corner cases. Fail some reviews on ISO27002 and supply chain and role sep. Fail some deployments when they're using dev tools in prod. And use them all as teachable moments. Honestly, some of them got no mentorship in college if they went, and no mentorship in their first ten years as a pro. It's going to be hard getting over themselves, but the sooner they realise they still have a bunch to learn, the better we can rebuild coders. The hardest part will be weaning them off GPT for the cheats. I don't have a solution for this.
One day these new devs will proudly install a patch in the RTOS flashed into your heart monitor and that annoying beep will go away. Sleep tight.
I have seen this too much. My current gripe isn't fresh devs, as long as they are teachable and care.
My main pain over the last several years has been the bulk of 'give-no-shit' perms/contractors who don't want to think or try when they can avoid it.
They run a web of lies until it is no longer sustainable (or the project is done for contractors) and then again its someone else's problem.
There are plenty of 10/20 year plus and devs who don't know what they are doing and don't care whose problem it will be as long as it isnt theirs.
I'm sick of writing coding 101 standards for 1k+ a day 'experts'. More sick of PR feedback where it's a battle to get things done in a maintainable manner from said 'experts'.
that is your leaderships fault
No one wants mentors. The way to move up in IT is to switch jobs every 24 months. So when you're paying mentors huge salaries to train juniors who are velocity drags into velocity boosters, you do it knowing they are going to leave and take all that investment with them for a higher paycheck.
I don't say this is right, but that's the reality from the paycheck side of things and I think there needs to be radical change for both sides. Like a trade union or something. Union takes responsibility for certifying skills and suitability, companies can be more confident of hires, juniors have mentors to learn from, mentors ensure juniors have aptitude and intellectual curiosity necessary to do the job well, and I guess pay is more skill/experience based so developers don't have to hop jobs to get paid what they are worth.
Fixed typos due to my iPhone hating me.
Yeah those job hoppers are the worst. You can always tell right away what kind of person those are. I've had to work with a "senior" dev who had 15 years of experience and to be honest he sucked at his job. He couldn't do simple tasks, didn't think before he started writing code and often got stuck asking other people for help. But he got paid big bucks, because all he did his entire career was work somewhere for 2-3 years and then job hop and trade up. By the time the company figured out the dude was useless, he went on to the next company.
Such a shitty attitude, which is a shame because he was a good dude otherwise. I got along with him on a personal level. And honestly good on him for making the most he can, fuck the company. But I personally couldn't do that, I take pride in my work.
I let the GPTs do that for me, without worrying that I won’t learn to code YAML for Ansible.
And this is the perfect use case. There's a good chance someone has done exactly what you want, and AI can regurgitate that for you.
That's not true of any interesting software project though.
FAIL some code reviews on corner cases. Fail some reviews on ISO27002 and supply chain and role sep. Fail some deployments when they’re using dev tools in prod. And use them all as teachable moments.
Fortunately, I work at an org that does this. It turns out that if our product breaks in prod, our customers could lose millions, which means they could go to a competitor. We build software to satisfy regulators, regulators that have the power to shut down everything if the ts aren't crossed just so.
Maybe that's the problem, maybe the stakes are low enough that quality isn't important anymore. Idk, what I do know is that I go hard on reviews.
and I see it when I'm forced to write fucking YAML for fucking Ansible. I let the GPTs do that for me, without worrying that I won't learn to code YAML for Ansible. Coding YAML for Ansible is NEVER going to be on my list of things I want to remember.
Feels like this is the attitude towards programming in general nowadays.
To be fair, YAML sucks. It's a config language that someone thought should cover everything, but excel at nothing.
Just use TOML, JSON, or old-school INI. YAML will just give you an aneurism. Use the best tool for the job, which is often not the prettiest one.
Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.
Antoine de Saint-Exupéry
Kids these days with their fancy stuff, you don't need all that to write good software. YAML is the quintessential "jack of all trades, master of none" nonsense. It's a config file, just make it easy to parse and document how to edit it. That's it.
While there is some truth to what you said, it sounded to me too much like "old man yells at clouds" because you are over-generalizing. Not everything new is bad. Don't get stuck in the past, that's just as dumb as relying on AI.
You and I read a very different comment, apparently. There was nothing there saying new is bad. Maybe read it again.
What are you guys working on where chatgpt can figure it out? Honestly, I haven't been able to get a scrap of working code beyond a trivial example out of that thing or any other LLM.
Agreed. I wanted to test a new config in my router yesterday, which is configured using scripts. So I thought it would be a good idea for ChatGPT to figure it out for me, instead of 3 hours of me reading documentation and trying tutorials. It was a test scenario, so I thought it might do well.
It did not do well at all. The scripts were mostly correct but often in the wrong order (referencing a thing before actually defining it). Sometimes the syntax would be totally wrong and it kept mixing version 6 syntax with version 7 syntax (I'm on 7). It will also make mistakes and when I point out the mistake it says Oh you are totally right, I made a mistake. Then goes on to explain what mistake it did and output new code. However more often than not the new code contained the exact same mistake. This is probably because of a lack of training data, where it is referencing only one example and that example just had a mistake in it.
In the end I gave up on ChatGPT, searched for my testscenario and it turned out a friendly dude on a forum put together a tutorial. So I followed that and it almost worked right away. A couple of minutes of tweaking and testing and I got it working.
I'm afraid for a future where forums and such don't exist and sources like Reddit get fucked and nuked. In an AI driven world the incentive for creating new original content is way lower. So when AI doesn't know the answer, you are just hooped and have to re-invent the wheel yourself. In the long run this will destroy productivity and not give the gains people are hoping for at the moment.
It's like useful information grows as fruit from trees in a digital forest we call the Internet. However, the fruit spoils over time (becomes less relevant) and requires fertile soil (educated people being online) that can be eroded away (not investing in education or infrastructure) or paved over (intellectual property law). LLMs are like processed food created in factories that lack key characteristics of more nutritious fresh ingredients you can find at a farmer's market. Sure, you can feed more people (provide faster answers to questions) by growing a monocrop (training your LLM on a handful of generous people who publish under Creative Commons licenses like CC BY-SA on Stack Overflow), but you also risk a plague destroying your industry like how the Panama disease fungus destroyed nearly all Gros Michel banana farming (companies firing those generous software developers who “waste time” by volunteering to communities like Stack Overflow and replacing them with LLMs).
There's some solar punk ethical fusion of LLMs and sustainable cultivation of high quality information, but we're definitely not there yet.
This is probably because of a lack of training data, where it is referencing only one example and that example just had a mistake in it.
The one example could be flawless, but the output of an LLM is influenced by all of its input. 99.999% of that input is irrelevant to your situation, so of course it's going to degenerate the output.
What you (and everyone else) needs is a good search engine to find the needle in the haystack of human knowledge, you don't need that haystack ground down to dust to give you a needle-shaped piece of crap with slightly more iron than average.
When I had to get up to speed on a new language, it was very helpful. It's also great to write low to medium complexity scripts in python, powershell, bash, and making ansible tasks. That said I've been programming for ~30 years, and could have done those things myself if I needed, but it would take some time (a lot of it being looking up documentation and writing boilerplate code).
It's also nice for writing C# unit tests.
However, the times I've been stuck on my main languages, it's been utterly useless.
ChatGPT is extremely useful if you already know what you're doing. It's garbage if you're relying on it to write code for you. There are nearly always bugs and edge cases and hallucinations and version mismatches.
It's also probably useful for looking like you kinda know what you're doing as a junior in a new project. I've seen some shit in code reviews that was clearly AI slop. Usually from exactly the developers you expect.
I love asking AI to generate a framework / structure for a project that I then barely use and then realize I shoulda just done it myself
I've been using (mostly) Claude to help me write an application in a language I'm not experienced with (Rust). Mostly with helping me see what I did wrong with syntax or with the borrow checker. Coming from Java, Python, and C/C++, it's very easy to mismanage memory the exact way Rust requires it.
That being said, any new code that generates for me I end up having to fix 9 times out of 10. So in a weird way I've been learning more about Rust from having to correct code that's been generated by an LLM.
I still think LLMs for the next while will be mostly useful as a hyper-spell checker for code, and not for generating new code. I often find that I would have saved time if I just tackled the problem myself and not tried to reply on an LLM. Although sometimes an LLM can give me an idea on how to solve a problem.
Same. It can generate credible-looking code, but I don't find it very useful. Here's what I've tried:
- describe a function - takes longer to read the explanation than grok the code
- generate tests - hallucinates arguments, doesn't do proper boundary checks, etc
- looking up docs - mostly useful to find search terms for the real docs
The second was kind of useful since it provided the structure, but I still replaced 90% of it.
I'm still messing with it, but beyond solving "blank page syndrome," it's not that great. And for that, I mostly just copy something from elsewhere in the project anyway, which is often faster than going to the LLM.
I'm really bad at explaining what I want, because by the time I can do that, it's faster to just build it. That said, I'm a senior dev, so I've been around the block a bit.
ChatGPT is perfect for learning Delphi.
I used it a few days ago to translate a math formula into code.
Here is the formula: https://wikimedia.org/api/rest_v1/media/math/render/svg/126b6117904ad47459ad0caa791f296e69621782
It's not the most complicated thing. I could have done it. But it would take me some time. I just input the formula directly, the desired language and the result was well done and worked flawlessly.
It saved me some time typing around. And searching online a few things.
Lately I have been using it for react code. It seems to be fairly decent at that. As a consequence when it does not work I get completely lost but despite this I think I have learned more with it then I would have without.
To be fair, most never could. I've been hiring junior devs for decades now, and all the ones straight out of university barely had any coding skills .
Its why I stopped looking at where they studied, I always first check their hobbies. if one of the hobbies is something nerdy and useless, tinkering with a raspberry or something, that indicates to me it's someone who loves coding and probably is already reasonably good at it
Nevermind how cybersecurity is a niche field that can vary by use case and environment.
At some level, you'll need to learn the security system of your company (or the lack there of) and the tools used by your department.
There is no class you can take that's going to give you more than broad theory.
Not in any way a new phenomenon, there's a reason fizzbuzz was invented, there's been a steady stream of CS graduates who can't code their way out of a wet paper bag ever since the profession hit the mainstream.
Actually fucking interview your candidates, especially if you're sourcing candidates from a country with for-profit education and/or rote learning cultures, both of which suck when it comes to failing people who didn't learn anything. No BS coding tests go for "explain this code to me" kind of stuff, worst case they can understand code but suck at producing it, that's still prime QA material right there.
We do two "code challenges":
- Very simple, many are done in 5 min; this just weeds out the incompetent applicants, and 90% of the code is written (i.e. simulate working in an existing codebase)
- Ambiguous requirements, the point is to ask questions, and we actually have different branches depending on assumptions they made (to challenge their assumptions); i.e. simulate building a solution with product team
The first is in the first round, the second is in the technical interview. Neither are difficult, and we provide any equations they'll need.
It's much more important that they can reason about requirements than code something quick, because life won't give you firm requirements, and we don't want a ton of back and forth with product team if we can avoid it, so we need to catch most of that at the start.
In short, we're looking for actual software engineers, not code monkeys.
Those are good approaches, I would note that the "90% is written" one is mostly about code comprehension, not writing (as in: Actually architect something), and the requirement thing is a thing that you should, IMO, learn as a junior, it's not a prerequisite. It needs a lot of experience, and often domain knowledge new candidates have no chance of having. But, then, throwing such stuff at them and then judging them by their approach, not end result, should be fair.
The main question I ask myself, in general, is "can this person look at code from different angles". Somewhat like rotating a cube in your mind's eye if you get what I mean. And it might even be that they're no good at it, but they demonstrate the ability when talking about coffee making. People who don't get lost when you're talking about cash registers having a common queue having better overall latency than cash registers with individual queues. Just as a carpenter would ask someone "do you like working with your hands", the question is "do you like to rotate implication structures in your mind".
Most hiring managers are looking for unicorns
This isn't a new thing. Dilution of "programmer" and "computer" education has been going on for a long time. Everyone with an IT certificate is an engineer th se days.
For millennials, a "dev" was pretty much anyone with reasonable intelligence who wanted to write code - it is actually very easy to learn the basics and fake your way into it with no formal education. Now we are even moving on from that to where a "dev" is anyone who can use an AI. "Prompt Engineering."
"Prompt Engineer" makes a little vomit appear in the back of my mouth.
This post is literally an ad for AI tools.
No, thanks. Call me when they actually get good. As it stands, they only offer marginally better autocomplete.
I should probably start collecting dumb AI suggestions and gaslighting answers to show the next time I encounter this topic...
Of course they don't. Hiring junior devs for their hard skills is a dumb proposition. Hire for their soft skills, intellectual curiosity, and willingness to work hard and learn. There is no substitute for good training and experience.
I'm a little defeatist about it. I saw with my own 3 eyes how a junior asked ChatGPT how to insert something into an
std::unordered_map. I tell them about cppreference. The little shit tells me "Sorry unc, ChatGPT is objectively more efficient". I almost blew a fucking gasket, mainly cuz I'm not that god damn old. I don't care how much you try to convince me that LLMs are efficient, there is no shot they are more efficient than opening a static page with all the info you would ever need. Not even considering energy efficiency. Utility aside, the damage we have dealt to developing minds is irreversible. We have convinced them that thought is optional. This is gonna bite us in the ass. Hard.I work in a small company that doesn't hire hardly at all... Stories like this scare me because I have no way to personally quantify how common that kind of attitude might be.
Look, ultimately the problem is the same as it has always been: juniors doing junior shit. There's just more of it going on. If you're hiring one, you put a senior on them ready to extinguish fires. A good review process is a must.
Now that I think about it, there was this one time the same young'un I was talking about tried to commit this insane subroutine that was basically resizing a vector in the most roundabout way imaginable. Probably would have worked, but you can also just use the
resizemethod, y'know? In retrospect, that was probably some Copilot bullshit, but because we have a review process in place, it was never an issue.
I work at a software development school, and ChatGPT does a lot of damage here too. We try to teach that using it as a tool to help learning is different from using it as a "full project code generator", but the speed advantages it provides makes it irresistible from many students' perspective. I've lost many students last year because they couldn't pass a simple code exam (think FizzBuzz difficulty level) because they had no access to internet, and had to code in Emacs. We also can't block access to it because it starts an endless game where they always find a way to access it.
Damn, I forgot about the teaching aspect of programming. Must be hard. I can't blame students for taking shortcuts when they're almost assuredly swamped with other classwork and sleep-deprived, but still. This is where my defeatist comment comes in, because I genuinely think LLMs are here to stay. Like autocomplete, but dumber. Just gotta have students recognize when ChatGPT hallucinates solutions, I guess.
It's going to get worse. I suspect that this'll end with LLM taking the part of a production programs. Juniors just feeding it scenarios to follow, hook the thing up to a database and web page and let it run. It'll gobble power like there's no tomorrow and is just a nightmare to maintain, but goes live in a quarter if the time so every manager goes with that.
How is it more efficient than reading a static page? The kids can't read. They weren't taught phonics, they were taught to guess the word with context clues. It's called "whole language" or "balanced reading"
I don't think phonics are the most critical part of why the kids can't read.
It's proven that people who read primarily books and documents read thoroughly, line by line and with understanding, while those that primarily read from screens (such as social media) skip and skim to find certain keywords. This makes reading books (such as documentation) hard for those used to screens from a young age and some believe may be one of the driving forces behind the collapse in reading amongst young people.
If you're used to the skip & skim style of reading, you will often miss details, which makes finding a solution in a manual infinitely frustrating.
Really? My kids are hitting the rules hard. In 1st grade, they're learning pronunciation rules I never learned (that's phonics, right?). My 2nd grader is reading the 4th Harry Potter book, and my 5th grader finished the whole series in 3rd grade and is reading at a 7th or 8th grade level.
I did teach them to read before kindergarten (just used a book for 2-3 months of 10 min lessons), but that's it, everything else is school and personal interest. They can both type reasonably well because they use the Minecraft console and chat. They're great at puzzles, and my 5th grader beat me at chess (I tried a wonky opening, and he punished me), which they learned at school (extra curricular, but run by a teacher).
We love our charter school, though I don't think it's that different from the public school.
Holy shit just like an LLM
Make the junior put it to the test John Henry style. You code something while they use gpt and see who comes up with a working version first
I could barely code when I landed my job and now I’m a senior dev. It’s saying a plumber’s apprentice can’t plumb - you learn on the job.
You're not learning anything if Copilot is doing it for you. That's the point.
100% agree.
I dont think there is no place for AI as an aid to help you find the solution, but i dont think it's going to help you learn if you just ask it for the answers.
For example, yesterday, i was trying to find out why a policy map on a cisco switch wasn't re-activating after my radius server came back up. Instead of throwing my map at the AI and asking whats wrong l, i asked it details about how a policy map is activated, and about what mechanism the switch uses to determine the status of the radius server and how a policy map can leverage that to kick into gear again.
Ultimately, AI didn't have the answer, but it put me on the right track, and i believe i solved the issue. It seems that the switch didnt count me adding the radius server to the running config as a server coming back alive but if i put in a fake server and instead altered the IP to a real server then the switch saw this as the server coming back alive and authentication started again.
In fact, some of the info it gave me along the way was wrong. Like when it tried to give me cli commands that i already knew wouldn't work because i was using the newer C3PL AAA commands, but it was mixing them up with the legacy commands and combining them together. Even after i told it that was a made-up command and why it wouldn't work, it still tried to give me the command again later.
So, i dont think it's a good tool for producing actual work, but it can be a good tool to help us learn things if it is used that way. To ask "why" and "how" instead of "what."
That’s true, it can only get you so far. I’m sure we all started by Frankenstein-ing stack overflow answers together until we had to actually learn the “why”
Stack Overflow and Google were once the "AI" of the previous generation. "These kids can't code, they just copy what others have done"
Yeah, and copy-pasting SO answers with no thought is just as bad.
And when copy-pasting didn't work, those who dared to rise above and understand it, became better. Same with AI, those of the new generation who see through the slop will learn. It's the same as it has always been. Software engineering is more accessible than ever, say what you will about the current landscape of software engineering but that fact remains undeniable.
As someone who can't code (not a developer) but occasionally needs to dip my toes in it. I've learned quite a bit from using chatgpt and then picking apart whatever it shat out to figure out why it's not working. It's still better than me starting from scratch on whatever it is I'm working on because usually I don't even know where to begin.
To me, I feel like this is a problem perpetuated by management. I see it on the system administration side as well -- they don't care if people understand why a tool works; they just want someone who can run it. If there's no free thought the people are interchangeable and easily replaced.
I often see it farmed out to vendors when actual thought is required, and it's maddening.
i always found this to be upsetting as an IT tech at a former company - when a network or server had an issue and i was sent to resolve it, it was a "just reboot it" fix, which never kept the problem from recurring and bringing the server down at 07:00 the next Monday.
the limitations on the questions i could ask hurt that SLA more than any network switch's memory leak ever did, and i felt as if my expertise meant nothing as a result.
Unless AI dramatically improves from where LLMs are today (in ways that it so far hasn't), as a worker, I'm looking forward to the drastic shortage of experienced senior devs in a few years time.
On the flipside, I'm discouraging people from entering CS. The passionate devs will ignore me anyway, and those that'll listen won't stand a chance against the hordes of professional BS "devs" that'll master AI and talk much prettier than them.
Don't get into CS unless you're passionate about the craft. If you're passionate, you'll succeed in pretty much regardless of the field.
Junior Devs could never code, yes including us
Agreed. A few year back the devs looking for quick fixes would go over to StackOverflow and just copy answers without reading explanations. This caused the same type of problems that OP is talking about. That said, the ease of AI might be making things even worse.
Hell, I would copy the question sometimes :P
Agreed. I was hired for my first job due to an impressive demo, and making that demo became my job. I got there, but I produced a ton of tech debt in the process.
Oddly enough, on my first development project I was paired with a "senior dev" who turned out just to be a guy in his 60s who had never actually coded before, so... just a senior.
I ended up doing 100% of the coding, but the guy managed to keep his job for a few months.
Recently my friend was trying to get me to apply for a junior dev position. "I don't have the right skills," I said. "The biggest project I ever coded was a calculator for my Java final, in college, a decade and a half ago."
It did not occur to me that showing up without the skills and using a LLM to half ass it was an option!
I could have been a junior dev that could code. I learned to do it before ChatGPT. I just never got the job.
Im in uni learning to code right now but since I'm a boomer i only spin up oligarch bots every once in a while to check for an issue that I would have to ask the teacher. It's far more important for me to understand fundies than it is to get a working program. But that is only because ive gotten good at many other skills and realize that fundies are fundamental for a reason.
They never could
Exactly, the jr dev that could write anything useful is a rare gem. Boot camps cranking out jr dev by the dozens every couple of months didn’t help the issue. Talent needs cultivation, and since every tech company has been cutting back lately, they stopped cultivating and started sniping talent from each other. Not hard given the amount of layoffs lately. So now we have jr devs either unable to find a place to refine them, or getting hired by people who just want to save money and don’t know that you need a senior or two to wrangle them. Then chat gpt comes along and gives the illusion of sr dev advice, telling them how to write the wrong thing better, no one to teach them which tool is the right one for the job.
Our industry is in kind of a fucked state and will be for a while. Get good at cleaning up the messes that will be left behind and that will keep you fed for the next decade.
No wonder open source software becomes more efficient than proprietary one.
Poisoning AI with backdoored code is surely a real risk now? I can see this getting quite nasty.
All I hear is "I'm bad at mentoring"
There is only so much mentoring can do though. You can have the best math prof. You still need to put in the exercise to solve your differential equations to get good at it.
You get out of education what you put into it. You won't be an artist from the best art school if you do the bare minimum to pass. You can end up as a legend of the industry coming from a noname school.
And some sort of "no one wants to work any more".
I know young brilliant people, maybe they have to be paid correctly?
One can classify approaches to progress in at least four most popular ways:
The most dumb clueless jerks think that it's replacing something known with something known and better. Progress enthusiasts, not knowing a single thing from areas they are enthusiastic about, are usually here.
The careful and kinda intellectually limited people think that it's replacing something known with something unknown. They can sour the mood, but are generally safe for those around them.
The idealistic idiots think that it's replacing something unknown with something known, that's "order bringers" and revolutionaries. Everybody knows how revolutionaries do things, who doesn't can look at Musk and DOGE.
The only sane kind think that it's replacing something unknown with something unknown. That is, that when replacing one thing with another thing you are breaking not only what you could see and have listed for replacement. Because nature doesn't fscking care what you want to see.
I honestly don't know how anyone's been able to code anything predominantly using AI that's production worthy.
Maybe it's the way I'm using AI, and to be honest I've only used chatGPT so far, but if I ask it to generate a bit of code then ask it to build on it and do the next thing, by about the third or fourth iteration it's forgotten half of what we talked about and missed out bits of code.
On a number of occasions it's given me a solution and when I questions it about the accuracy of it and why a bit of it probably won't work I just get oh yes let me adjust that for you.
Maybe I'm doing AI wrong I don't know, but quite frankly I'll stick with stack overflow thanks.
It's only useful for stuff that's been done a million times before in my experience. As soon as you do anything outside of that, it just starts hallucinating.
It's basically like how junior devs used to go to stack overflow, grabbed whatever code looked like it would work and just plopped it in the codebase.
I frankly only used those to generate pictures and sometimes helloworlds for a few languages, which didn't work and didn't seem to make sense. It was long enough ago.
Also I have ASD, so it's hard enough for me to make consistent clear sense from something small. A machine-generated junk to give ideas is the last thing I need, my thought process is different.
Has anyone else clicked the chat.com url in the article …
that s the point of being junior. Then problems show up and they are forcing them to learn to solve them
Very "back in my day" energy.
I do not support AI but programming is about solving problems and not writing code.
If we are concentrating on tool, no developers and use punched card as well. Is that a bad thing?
You're right in that the goal is problem solving, you're wrong that inability to code isn't a problem.
AI can make a for loop and do common tasks but the moment you have something halfway novel to do, it has a habit of shitting itself and pretending that the feces is good code. And if you can't read code, you can't tell the shit from the stuff you want.
It may be able to do it in the future but it can't yet
Source: data engineer who has fought his AI a time or two.
Of course I use as well on a daily basis for coding and AI is shit.
Again, I in no way support AI, I just think that the argument made in the article is also not good.