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I very much enjoy using AI for all the biloilerplate, test cases, suggestions, etc. It really makes me more productive, hard metrics behind it. Nobody is forcing me to, they just provide the license and let us use our judgment.
I honestly can't think of a project where 0% AI would be better. For 100% maybe a very trivial PoC, but even that would require at least a code revision.
So, as with many things, use in moderation is fine.
It's almost certainly also making your code worse.
It's not impossible to use AI effectively (although I would argue it's impossible to use large "frontier" models ethically, as the companies making them are burning the planet down to power the process), but you have to be extremely vigilant and thoughtful about what you're using it for, and you have to review every single line of code it produces, or you're going to miss bugs and you're going to lose skills.
A good way to test yourself is to see if you can still scaffold out an application by hand. Doesn't matter what... A to-do list, some buttons, whatever. Just test yourself to see if you can still do it.
If you can't, then you've lost the skills necessary to be certain that what you're producing with AI is actually good.
And if the idea of testing yourself like this makes you uncomfortable? Then AI isn't a tool you use, it's an addiction.
I mean, I do leet code semi-regularly, so I'm not too worried about getting rusty. Writing tests is boring as hell, the AI does a decent enough job for at least 90% of them.
Leet code is good for making sure you still have a good grasp of programming conceptually, but I don't think it's good for testing your own practical skills.
Seriously, just take an hour or two to scaffold out something new. Doesn't have to be complicated, just something to confirm for yourself that you can still do it. The only rule is to do it without AI.
When I did it myself, it was after months of my work requiring me to use AI, and there was a moment at the start where I was tempted to just fire up Copilot and tell it to do the work, which - of course - would have defeated the purpose. It was that moment where I realized I was addicted, and needed to go cold turkey.
Now I do the bare minimum with AI I'm required to at work, and focus on crafting my code carefully, by hand as much as possible. And it shows. My code quality has improved.
What do you mean by scaffolding something new? If it's writing all the boilerplate for the framework and dependencies, that's exactly what I don't care about. I use AI now and copy paste in the past.
No, I don't mean writing all the boilerplate. It's simpler than that.
Just to take a random example, let's say the throwaway project you decide to do is build a custom button component in Angular. The steps would be something like this:
ng new buttonscd buttonsng serveI chose Angular because these days the CLI for it does almost everything for you. It's absurdly easy, and is the sort of thing it may actually be slower to ask an AI to do, because the AI will absolutely try to create a bunch of things in the project itself rather than through the CLI. And it will use Angular patterns from 2024 rather than anything current (such as Signals), because of its training data.
Not only is doing something like this (in whatever language you prefer) good practice for keeping your practical skills, it's a good reminder that AI is only one tool in the toolbox. If it becomes your only tool, well... The old saying about how if all you have is a hammer everything looks like a nail applies.
Back when I had to do frontend the AI did use create-react-app. No idea about angular. If it's on stack overflow, the AI knows about it (even if it doesn't always use it).
Even if you ask to create a one shot PoC, sometimes it will use Maven, sometimes Gradle. If you want something specific you include it in the prompt or preferences.
I'd be curious to see what your hard metrics are based on.
https://mikelovesrobots.substack.com/p/wheres-the-shovelware-why-ai-coding
https://filebin.net/zf92vn7hm4zcabe9
Points per sprint, features shipped, test coverage. Defects remain unchanged.
Code quality? Maintainability down the line? Numbers for those aspects yet?
It's been more than 3 years since we started, and the metrics are stable, slight improvement even but that could be more experience or better models or anything. No apocalypse.
Happy that it's working out for at least a small margin of people. 👍
There's always the many ethical aspects as well, of course.
The ethics are debatable, but there's not turning back, there's plenty of open source models even that do a very decent job, so we will need to learn to deal with the reality. We never hired juniors anyway, but companies that did apparently have stopped, that can't be good.
In my opinion, the ethics are clear problems. There are way too many ethical issues for me to even consider using AI right now. I would never have a clear conscience using AI. Using AI as a service responsibly is impossible right now IMO.
I don't see it that bad. Specially open source models. Agree to disagree I guess.
Open source models aren't really used in AI as a service though, are they?
Depends what you consider as a service. Anthropic and OpenAI will only offer their own stuff, but if you go for AWS Bedrock you have plenty of open source ones. Probably similar for Vertex on GCP. God only knows what Microsoft is doing over there.