I’ve seen a few articles saying that instead of hating AI, the real quiet programmers young and old are loving it and have a renewed sense of purpose coding with llm helpers (this article was also hating on ed zitiron, which makes sense why it would).
Is this total bullshit? I have to admit, even though it makes me ill, I’ve used llms a few times to help me learn simple code syntax quickly (im and absolute noob who’s wanted my whole life to learn code but cant grasp it very well). But yes, a lot of time its wrong.
From my experience it’s great at doing things that have been done 1000x before (which makes sense given the training data), but when it comes to building something novel it really struggles, especially if there’s 3rd party libraries involved that aren’t commonly used. So you end up spending a lot of time and money hand holding it through things that likely would have been quicker to do yourself.
the 1000x before bit has quite a few sideffects to it as well.
- lesser used languages suffer because there’s not enough training data. this gets annoying quickly when it overrides your static tools and suggests nonsense.
- larger training sets contain more vulnerabilities as most code is pretty terrible and may just be snippets that someone used once and threw away. owasp has a top 10 for a reason. take input validation for example, if I’m working on parsing a string there’s usually context such as is this trusted data or untrusted? if i don’t have that mental model where I’m thinking about the data i might see generated code and think it looks correct but in reality its extremely nefarious.
Its also trained on old stuff.
And because its old, you get some very strange side effects and less maintainability.
It’s decent at reviewing its own code, especially if you give it different lenses to look though.
“Analyze this code and look for security vulnerabilities.” “Analyze this code and look for ways to reduce complexity.”
And then… think about the response like it’s a random dude online reviewing your code. Lots of times it raises good issues but sometimes it tries too hard to find little shit that is at best a sidegrade.
The pycharm AI integration completes each line. That’s very useful when you are repeating a well known algorithm and not distracting when you are doing something unusual. So overall, for small things AI is a speed up. I haven’t tried asking chatgpt for bigger coffe chunks, I haven’t had the greatest experience with it up to now and ii don’t want to spend more time debugging than I am already.
Oh man, the Codeium auto complete in PyCharm has been just awful for me. Slow enough that it doesnt come up fast enough that I ever expect it (and rarely comes up when I pause to wait for it) then goes away instantly when I invariably continue typing when it comes up. Then won’t come back if I backspace, erase the word and start retyping it, etc. And competes with the old school pycharm auto complete sometimes which adds another layer of fun.
I’m pretty sure every time you use AI for programming your brain atrophies a little, even if you’re just looking something up. There’s value in the struggle.
So they can definitely speed you up, but be careful how you use it. There’s no value in a programmer who can only blindly recite LLM output.
There’s a balance to be struck in there somewhere, and I’m still figuring it out.
I’m pretty sure every time you use AI for programming your brain atrophies a little, even if you’re just looking something up. There’s value in the struggle.
I assume you were joking but some studies have come out recently that found this is exactly what happens and for more than just programming. (sorry it was a while ago so I dont have links)
Doesn’t sound like they’re joking to me.
You can either spend your time generating prompts, tweaking them until you get what you want and then using more prompts to refining the code until you end up with something that does what you want…
or you can just fucking write it yourself. And there’s the bonus of understanding how it works.
AI is probably fine for generating boiler plate code or repetitive simple stuff, but personally I wouldn’t trust it any further than that.
There is a middle ground. I have one prompt I use. I might tweak it a little for different technologies, languages, etc. only so I can fit more standards, documentation and example code in the upload limit.
And I ask it questions rather than asking it to write code. I have it review my code, suggest other ways of doing something, have it explain best practices, ask it to evaluate the maintainability, conformance to corporate standards, etc.
Sometimes it takes me down a rabbit hole when I’m outside my experience (so does Google and stack overflow for what it’s worth), but if you’re executing a task you understand well on your own, it can help you do it faster and/or better.
In the grand scheme of things, I think AI code generators make people less efficient. Some studies have come out that indicate this. I’ve tried to use various AI tools, as I do like fields of AI/ML in general, but they would end up hampering my work in various ways.
The truth, as always, is in the middle. Plenty of programmers hate it, and plenty of programmers like it. It just so happens that these kinds of spaces attracts more or the hate crowd, and paid shill articles attract more or the like crowd ¯\_(ツ)_/¯
I don’t see how it could be more effecient to have AI generate something that you then have to review and make sure actually works over just writing the code yourself, unless you don’t know enough to code it yourself and just accept the AI generated code as-is without further review.
I don’t see how it could be more effecient to have [a junior developer write] something that you then have to review and make sure actually works over just writing the code yourself…
From my experience it’s really great at bootstrapping new projects for you. It’s good at getting you sample files and if you’re using cursor just building out a sample project.
It’s decent at being an alternative to google/SO for syntax or previously encountered errors. There’s a few things it hallucinates but generally it can save time as long as you don’t trust it blindly.
It struggles when you give it complex tasks or not-straightforward items. Or things that require a lot of domain knowledge. I once wanted to see what css classes were still in use across a handful of react components and it just shat the bed.
The people who champion AI as a human replacement will build a quick proof of concept with it and proclaim “oh shit this is awesome!” And not realize that that’s the easy part of software engineering.
I use it mainly to tweak things I can’t be bothered to dig into, like Jekyll or Wordpress templates. A few times I let it run and do a major refactor of some async back-end code. It botched the whole thing. Fortunately, easy to rewind everything from remote git repo.
Last week I started a brand new project, thought I’d have it write the boilerplate starter code. Described in detail what I was looking for. It sat there for ten minutes saying ‘Thinking’ and nothing happened. Killed it and created it myself. This was with Cursor using Claude. I’ve noticed it’s gotten worse lately, maybe because of the increased costs.
The hate is ridiculous as is the hype.
It’s a new tool that is often useful when used correctly. Don’t use it to write entire applications - that’s a recipe for disaster.
But if you’re learning a new language it’s amazing. You have an infinitely patient and immediately available tutor that can teach you a language’s syntax, best practices, etc. I don’t know why that would make you “ill” besides all the shame “real developers” seem to want to lump on anybody who uses AI. If you’re not concerned about passing some “I don’t use an IDE” nerd’s purity test you’ll be fine.
Yes. But I’m not paying for premium like some of my cowokres. I use it to avoid the grunt work, and to avoid things I know I’d have to google.
I used some coworkers account for a while and auto complete is amazing. I it guesses wrong you just keep tipping as usual. If its right, hit tab and saves you like 20 seconds.
On the other hand I have cokowkers that do not check the chatgpt output and the PRs make no sense. Example: instead of making a variable type any (which is forbidden in our codebase) they did
Let a : date|number|string|object|(…) = fetchData()
I’m somewhat new to the field ~1.5 years, so my opinion doesn’t hold too much weight.
But in the embedded field I’ve found AI to not be as helpful as it seems to be for many others. The one BIG thing is has helped me with is I can give it a data sheet and it’ll spit out all the register fields that I need, or help me quickly find information that I’m too lazy to Ctrl-f, which saves a couple minutes.
It has not proven it’s worth when it comes to the firmware itself. I’ve tried to get it to instantiate some peripheral instances and they never ended up working, no matter how I phrased the prompt or what context i’ve given it.
I’ve had good luck having it write simple scripts that I could easily handle myself. For example, I needed a script to chop a directory full of log files up into archives, with some constraints. That sort of thing.
I haven’t tried it on anything more substantial.
This was using Copilot because I haven’t found a good coding model that will run locally on 16GB VRAM.Some definitely are. But I think a lot aren’t. Hell, a lot of programmers still don’t even use an IDE.
I don’t know why it would make you ill.
The same reason I wont use autotune or melodyne. Its just gross to me.
I don’t feel like it’s the same - autotune can make me more in tune than I could ever achieve. Current LLMs definitely can’t write better code than me, they can just do it faster.
Not total bullshit, but it’s not great for all use cases:
For coding tasks the output looks good on the surface but often I end up changing stuff, meaning it would have been faster up do myself.
For coding I know little about (currently writing some GitHub actions), it’s great at explaining alternatives, pros and cons, to give me a rudimentary understanding of stuff
I’ve also used it to transcribe tutorial screencasts, and then afterwards having a secondary LLM use the transcription to generate documentation (include in prompt: "when relevant, generate examples, use markdown tables, generate plantuml etc)
Not a programmer, but I used it at my last job to get over humps where I was stuck on PowerShell scripts. AI can show you a path you didn’t know or hadn’t thought about. The developers seemed to be using it the same way. Great tool if you don’t completely lean on it and you know enough to judge the output.
Thats the key, use it to learn, not to do your thinking
I find it excels at one-off scripts. They are simple enough that every parameter and line of code fits in a small bit of memory. They are really bad at complex tasks, but they can help if you use it judiciously.
I used ChatGPAT to write some fairly straight forward bash scripts last week and it was mostly awful. I ended up massaging it enough to do what I needed, but I would have been better off just writing it myself and maybe asking it a couple syntax questions (although the regex I needed was one of 8 things it stumbled over)
