Have you ever found a GitHub project or anything that seemed nice and tempting to install until you dug a bit deeper?
What are some red flags that should detur anyone from installing and running something?
Have you ever found a GitHub project or anything that seemed nice and tempting to install until you dug a bit deeper?
What are some red flags that should detur anyone from installing and running something?
That ship has sailed. The question is how to use AI to code, for every project there’s a sweet spot and it rarely is 0% or 100%.
You really don’t need to. Nobody is forcing you.
And if they are, seriously considering finding another place of work.
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.
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.
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.