this post was submitted on 11 Jul 2025
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Experienced software developer, here. "AI" is useful to me in some contexts. Specifically when I want to scaffold out a completely new application (so I'm not worried about clobbering existing code) and I don't want to do it by hand, it saves me time.
And... that's about it. It sucks at code review, and will break shit in your repo if you let it.
Same. I also like it for basic research and helping with syntax for obscure SQL queries, but coding hasn't worked very well. One of my less technical coworkers tried to vibe code something and it didn't work well. Maybe it would do okay on something routine, but generally speaking it would probably be better to use a library for that anyway.
Important thing they left out here being a broad news source reporting tech stuff is that this was specifically bug fixing tasks. If you’re familiar with using it for coding you’ll know it’s horrendous at that sort of thing. It can typically only provide the broadest of advice and it’s largely incapable of tackling things holistically.
Not a developer per se (mostly virtualization, architecture, and hardware) but AI can get me to 80-90% of a script in no time. The last 10% takes a while but that was going to take a while regardless. So the time savings on that first 90% is awesome. Although it does send me down a really bad path at times. Being experienced enough to know that is very helpful in that I just start over.
In my opinion AI shouldn’t replace coders but it can definitely enhance them if used properly. It’s a tool like everything. I can put a screw in with a hammer but I probably shouldn’t.
Like I said, I do find it useful at times. But not only shouldn't it replace coders, it fundamentally can't. At least, not without a fundamental rearchitecturing of how they work.
The reason it goes down a "really bad path" is that it's basically glorified autocomplete. It doesn't know anything.
On top of that, spoken and written language are very imprecise, and there's no way for an LLM to derive what you really wanted from context clues such as your tone of voice.
Take the phrase "fruit flies like a banana." Am I saying that a piece of fruit might fly in a manner akin to how another piece of fruit, a banana, flies if thrown? Or am I saying that the insect called the fruit fly might like to consume a banana?
It's a humorous line, but my point is serious: We unintentionally speak in ambiguous ways like that all the time. And while we've got brains that can interpret unspoken signals to parse intended meaning from a word or phrase, LLMs don't.
Not quite true - GitHub Copilot in VS for example can be given access to your entire repo/project/etc and it then "knows" how things tie together and work together, so it can get more context for its suggestions and created code.
That's still not actually knowing anything. It's just temporarily adding more context to its model.
And it's always very temporary. I have a yarn project I'm working on right now, and I used Copilot in VS Code in agent mode to scaffold it as an experiment. One of the refinements I included in the prompt file to build it is reminders throughout for things it wouldn't need reminding of if it actually "knew" the repo.
I'm not saying it wasn't helpful. It probably cut 20% off the time it would have taken me to scaffold out the app myself, which is significant. But it certainly couldn't keep track of the context provided by the repo, even though it was creating that context itself.
Working with Copilot is like working with a very talented and fast junior developer whose methamphetamine addiction has been getting the better of it lately, and who has early onset dementia or a brain injury that destroyed their short-term memory.
Adding context is “knowing more” for a computer program.
Maybe it’s different in VS code vs regular VS, because I never get issues like what you’re describing in VS. Haven’t really used it in VS Code.
Are you using agent mode?
I have limited AI experience, but so far that's what it means to me as well: helpful in very limited circumstances.
Mostly, I find it useful for "speaking new languages" - if I try to use AI to "help" with the stuff I have been doing daily for the past 20 years? Yeah, it's just slowing me down.
I like the saying that LLMs are good at stuff you don’t know. That’s about it.
They're also bad at that though, because if you don't know that stuff then you don't know if what it's telling you is right or wrong.
Like search engines, and libraries...
Everyone on Lemmy is a software developer.
I've found it to be great at writing unit tests too.
I use github copilot in VS and it's fantastic. It just throws up suggestions for code completions and entire functions etc, and is easily ignored if you just want to do it yourself, but in my experience it's very good.
Like you said, using it to get the meat and bones of an application from scratch is fantastic. I've used it to make some awesome little command line programs for some of my less technical co-workers to use for frequent tasks, and then even got it to make a nice GUI over the top of it. Takes like 10% of the time it would have taken me to do it - you just need to know how to use it, like with any other tool.
Exactly what you would expect from a junior engineer.
Let them run unsupervised and you have a mess to clean up. Guide them with context and you’ve got a second set of capable hands.
Something something craftsmen don’t blame their tools
AI tools are way less useful than a junior engineer, and they aren't an investment that turns into a senior engineer either.
They're tools that can help a junior engineer and a senior engineer with their job.
Given a database, AI can probably write a data access layer in whatever language you want quicker than a junior developer could.
AI tools are actually improving at a rate faster than most junior engineers I have worked with, and about 30% of junior engineers I have worked with never really "graduated" to a level that I would trust them to do anything independently, even after 5 years in the job. Those engineers "find their niche" doing something other than engineering with their engineering job titles, and that's great, but don't ever trust them to build you a bridge or whatever it is they seem to have been hired to do.
Now, as for AI, it's currently as good or "better" than about 40% of brand-new fresh from the BS program software engineers I have worked with. A year ago that number probably would have been 20%. So far it's improving relatively quickly. The question is: will it plateau, or will it improve exponentially?
Many things in tech seem to have an exponential improvement phase, followed by a plateau. CPU clock speed is a good example of that. Storage density/cost is one that doesn't seem to have hit a plateau yet. Software quality/power is much harder to gauge, but it definitely is still growing more powerful / capable even as it struggles with bloat and vulnerabilities.
The question I have is: will AI continue to write "human compatible" software, or is it going to start writing code that only AI understands, but people rely on anyway? After all, the code that humans write is incomprehensible to 90%+ of the humans that use it.
I’m seeing exactly the opposite. It used to be the junior engineers understood they had a lot to learn. However with AI they confidently try entirely wrong changes. They don’t understand how to tell when the ai goes down the wrong path, don’t know how to fix it, and it takes me longer to fix.
So far ai overall creates more mess faster.
Don’t get me wrong, it can be a useful tool you have to think of it like autocomplete or internet search. Just like those tools it provides results but the human needs judgement and needs to figure out how to apply the appropriate results.
My company wants metrics on how much time we’re saving with ai, but
I've always had problems with junior engineers (self included) going down bad paths, since before there was Google search - let alone AI.
Maybe it is moving faster, maybe they do bother the senior engineers less often than they used to, but for throw-away proof of concept and similar stuff, the juniors+AI are getting better than the juniors without senior support used to be... Is that a good direction? No. When the seniors are over-tasked with "Priority 1" deadlines (nothing new) does this mean the juniors can get a little further on their own and some of them learn from their own mistakes? I think so.
Where I started, it was actually the case that the PhD senior engineers needed help from me fresh out of school - maybe that was a rare circumstance, but the shop was trying to use cutting edge stuff that I knew more about than the seniors. Basically, everything in 1991 was cutting edge and it made the difference between getting something that worked or having nothing if you didn't use it. My mentor was expert in another field, so we were complimentary that way.
My company (now) wants metrics on a lot of things, but they also understand how meaningless those metrics can be.
https://clip.cafe/monsters-inc-2001/all-right-mr-bile-it/
Shame. There was a time that people dug out of their own messes, I think you learn more, faster that way. Still, I agree - since 2005 I have spend a lot of time taking piles of Matlab, Fortran, Python that have been developed over years to reach critical mass - add anything else to them and they'll go BOOM - and translating those into commercially salable / maintainable / extensible Qt/C++ apps, and I don't think I ever had one "mentee" through that process who was learning how to follow in my footsteps, the organizations were always just interested in having one thing they could sell, not really a team that could build more like it in the future.
Yep.
Speaking of meaningless metrics, how many people ask you for Lines Of Code counts, even today?___
Yes, that’s how we became senior guys. But when you have deadlines that you’re both on the hook for and they’re just floundering, you can only give them so much opportunity. I’ve had too many arguments with management about letting them merge and I’m not letting that ruin my code base
We have a new VP collecting metrics on everyone, including lines of code, number of merge requests, times per day using ai, days per week in the office vs at home
I guess I'm lucky, before here I always had 100% control of the code I was responsible for. Here (last 12 years) we have a big team, but nobody merges to master/main without a review and screwups in the section of the repository I am primarily responsible for have been rare.
I have been getting actively recruited - six figures+ - for multiple openings right here in town (not a huge market here, either...) this may be the time...
Interesting idea… we actually have a plan to go public in a couple years and I’m holding a few options, but the economy is hitting us like everyone else. I’m no longer optimistic we can reach the numbers for those options to activate
LOL sure
I'm not talking about the ones that get hired in your 'leet shop, I'm talking about the whole damn crop that's just graduated.
Is “way less useful” something you can cite with a source, or is that just feelings?
It is based on my experience, which I trust immeasurably more than rigged "studies" done by the big LLM companies with clear conflict of interest.
Understood, thanks for being honest
Yeah but a Claude/Cursor/whatever subscription costs $20/month and a junior engineer costs real money. Are the tools 400 times less useful than a junior engineer? I’m not so sure…
The point is that comparing AI tools to junior engineers is ridiculous in the first place. It is simply marketing.
This line of thought is short sighted. Your senior engineers will eventually retire or leave the company. If everyone replaces junior engineers with ai, then there will be nobody with the experience to fill those empty seats. Then you end up with no junior engineers and no senior engineers, so who is wrangling the ai?
This isn’t black and white. There will always be some junior hires. No one is saying replace ALL of them. But hiring 1 junior engineer instead of 3? Maybe…and that’s already happening to some degree.
Even at $100/month you’re comparing to a > $10k/month junior. 1% of the cost for certainly > 1% functionality of a junior.
You can see why companies are tripping over themselves to push this new modality.
I was just ballparking the salary. Say it’s only 100x. Does the argument change? It’s a lot more money to pay for a real person.
Wasn’t it clear that our comments are in agreement?
It wasn’t, but now it is.
❤️
The difference being junior engineers eventually grow up into senior engineers.
Does every junior eventually achieve becoming a senior?
No, but that's the only way you get senior engineers!
I agree, but the goal of CEOs is “line go up,” not make our eng team stronger (usually)
Capitalism, shortsighted? Say it ain’t so!
Except junior engineers become seniors. If you don't understand this ... are you HR?
They might become seniors for 99% more investment. Or they crash out as “not a great fit” which happens too. Juniors aren’t just “senior seeds” to be planted
Interesting downvotes, especially how there are more than there are upvotes.
Do people think "junior" and "senior" here just relate to age and/or time in the workplace? Someone could work in software dev for 20 years and still be a junior dev. It's knowledge and skill level based, not just time-in-industry based.