“Many developers say AI coding assistants make them more productive, but a recent study set forth to measure their output and found no significant gains. Use of GitHub Copilot also introduced 41% more bugs, according to the study from Uplevel”
study referenced: Can GenAI Actually Improve Developer Productivity? (requires email)
I don’t want to be productive.
I want to do the least amount of work possible while still getting paid.
AI coding assistance is good for the same stuff you would have put through a tool assisted service previously anyway. Regex and other forms of complex pattern matching are way easier for a computer than a human. The only difference now is that you can just write out the problem plainly instead of in tiny chunks.
I recently had to write a script to parse an nginx log for unique entries with very specific criteria that could vary depending on other criteria, and then do some crap to manipulate that data and use portions of it for API calls to other more complicated shit. Figuring out how to properly parse that data manually would be mind numbing. AI does it instantly.
That’s not to say that the entire concept as a marketing ploy isn’t complete bullshit, but if it were just used for the crap it’s good at, it would actually be a net benefit to society.
Regex and other forms of complex pattern matching are way easier for a computer than a human.
I know what you meant by this, but I still chuckled. Humans are the ultimate pattern matching machines in the whole solar system.
AI has simply weaponized copy/pasting stack overflow answers without reading them.
Not only was it not that useful to me, it decreased the most fun part of programming (writing code) and increased the least fun part of programming (reviewing code), so it overall gave me a worse experience.
I’m a software developer. What it does do is help you out for beginning level work, half remembering methods sometimes works out.
What it’s really good at is templates. Like build a simple MVC based on this table kinda deal. It saves a ton of boilerplate time in a semi intelligent way. What it’s really bad at is anything remotely complicated because it will forget/error out/ rely on libraries that do not exist. I have other thoughts on the actual companies and the spam they say is AI but that’s another convo.
This is the perfect AI niche. Making something mediocre that resembles an already existing pile of mediocre material.
It’s really good at boilerplate. Saves a lot of time on repetitive tasks. I’ve found it particularly useful for unit tests and demo pages. Things where you write one variation and it automatically generates the others for you.
Another instance where it was useful for me was when I needed to make a small change in another team’s repo. I knew exactly what I needed to do, but I wasn’t familiar with the language. Copilot helped with getting the correct syntax.
The #1 thing Ive used AI for is commenting my code. It is pretty good at following my format and generating code documentation, based on my existing code.
It’s also really good at helping me think of a good name for something, if there’s a specific word on the tip of my tongue. “Whats the word for when you do the thing with the thingy?” “It sounds like you are looking for (word)”
Also its really good for helping me find the name of specific algorithms for use cases.
“Is there a known algorithm I can look up that can fenangle a dinger?”
“You might be looking for the Ferg Dergeson Flemming algorithm, which is a popular way to fenangle dingers”
Then Ill look it up and it is, indeed, like the best way to fenangle a dinger and I’m like “well holy shit, this is a solved problem turns out, I shoulda known”
seems a lot of people are using AI as a replacement for search since Google search has become such garbage
Last time I tried to look up how to fenagle a dingle, Google showed me ads about how to friffle bahoonies for two pages, and finally out showed me the dingle fenagling algorithm in the ancient Expert Sex Change website.
Yep. I think looking back it’s going to be clear Google chose the wrong time to lean into enshittification of their algorithm. Further, their habit of abandoning products will cause people to choose other LLM solutions first.
🤣 lmao
