AI slows down some experienced software developers, study finds
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My fear for the software industry is that we'll end up replacing junior devs with AI assistance, and then in a decade or two, we'll see a lack of mid-level and senior devs, because they never had a chance to enter the industry.
100% agreed. It should not be used as a replacement but rather as an augmentation to get the real benefits.
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Explain this too me AI. Reads back exactly what's on the screen including comments somehow with more words but less information
Ok....Ok, this is tricky. AI, can you do this refactoring so I don't have to keep track of everything. No... Thats all wrong... Yeah I know it's complicated, that's why I wanted it refactored. No you can't do that... fuck now I can either toss all your changes and do it myself or spend the next 3 hours rewriting it.
Yeah I struggle to find how anyone finds this garbage useful.
I have asked questions, had conversations for company and generated images for role playing with AI.
I've been happy with it, so far.
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"Using something that you're not experienced with and haven't yet worked out how to best integrate into your workflow slows some people down"
Wow, what an insight! More at 8!
As I said on this article when it was posted to another instance:
AI is a tool to use. Like with all tools, there are right ways and wrong ways and inefficient ways and all other ways to use them. You can’t say that they slow people down as a whole just because some people get slowed down.
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Explain this too me AI. Reads back exactly what's on the screen including comments somehow with more words but less information
Ok....Ok, this is tricky. AI, can you do this refactoring so I don't have to keep track of everything. No... Thats all wrong... Yeah I know it's complicated, that's why I wanted it refactored. No you can't do that... fuck now I can either toss all your changes and do it myself or spend the next 3 hours rewriting it.
Yeah I struggle to find how anyone finds this garbage useful.
Sounds like you just need to find a better way to use AI in your workflows.
Github Copilot in Visual Studio for example is fantastic and offers suggestions including entire functions that often do exactly what you wanted it to do, because it has the context of all of your code (if you give it that, of course).
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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.
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.
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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.
The reason it goes down a “really bad path” is that it’s basically glorified autocomplete. It doesn’t know anything.
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.
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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.
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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.
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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.
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Explain this too me AI. Reads back exactly what's on the screen including comments somehow with more words but less information
Ok....Ok, this is tricky. AI, can you do this refactoring so I don't have to keep track of everything. No... Thats all wrong... Yeah I know it's complicated, that's why I wanted it refactored. No you can't do that... fuck now I can either toss all your changes and do it myself or spend the next 3 hours rewriting it.
Yeah I struggle to find how anyone finds this garbage useful.
You shouldn't think of "AI" as intelligent and ask it to do something tricky. The boring stuff that's mostly just typing, that's what you get the LLMs to do. "Make a DTO for this table <paste>" "Interface for this JSON <paste>"
I just have a bunch of conversations going where I can paste stuff into and it will generate basic code. Then it's just connecting things up, but that's the fun part anyway.
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The reason it goes down a “really bad path” is that it’s basically glorified autocomplete. It doesn’t know anything.
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 had to constantly remind it that it's a yarn project, otherwise it would inevitably start trying to use NPM as it progressed through the prompt.
- For some reason, when it's in agent mode and it makes a mistake, it wants to delete files it has fucked up, which always requires human intervention, so I peppered the prompt with reminders not to do that, but to blank the file out and start over in it.
- The frontend of the project uses TailwindCSS. It could not remember not to keep trying to downgrade its configuration to an earlier version instead of using the current one, so I wrote the entire configuration for it by hand and inserted it into the prompt file. If I let it try to build the configuration itself, it would inevitably fuck it up and then say something completely false, like, "The version of TailwindCSS we're using is still in beta, let me try downgrading to the previous version."
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.
