I've seen enough programmers blindly copypasting code from stackoverflow and other forums without thinking and never understanding the thing they just "wrote", to know that tools like copilot won't make programmers worse, they will allow more people to be bad programmers.

people need to read more code, play around with it, break it and fix it to become better programmers.

I have heard the same rhetoric about IDEs, autocomplete (Intellisense, Jedi, etc.), DevOps, and frameworks. The kernel of truth across all of them is the separation between a dev and good dev. It is getting easier and easier to have something built for you using AI in your IDE in a framework that abstracts all the things away dumped into a prebuilt pipeline that deploys your artifacts for you. A dev can do that. A good dev understands the tools and knows when to dig into things.

I have yet to see a decrease in the number of good devs I meet even though IDEs slowly replaced text editors (and editors became strong enough to become IDEs). Frameworks have enabled more good devs to focus on business logic. DevOps provides solid guard rails for everything.

I don’t know if there’s an increase in the number of superficial devs. I haven’t interviewed junior dev candidates in awhile. I do know the market is flooded right now so I’d argue there might be other factors.

Also overall I do agree with the idea that letting copilot do everything for you means you don’t understand anything. Shit was the same way when cookbooks were common.

I was hoping this might start with some actual evidence that programmers are in fact getting worse. Nope, just a single sentence mentioning "growing concern", followed by paragraphs and paragraphs of pontification.

Anything that allows people to blindly and effortlessly get results inherently makes them more stupid. Your brain is like any muscle. You need to repeatedly use it for it to work well

https://sfconservancy.org/GiveUpGitHub/

I'm a 10+ (cumulative) yr. experience dev. While I never used The GitHub Copilot specifically, I've been using LLMs (as well as AI image generators) on a daily basis, mostly for non-dev things, such as analyzing my human-written poetry in order to get insights for my own writing. And I already did the same for codes I wrote, asking for LLMs to "Analyze and comment" my code, for the sake of insights. There were moments when I asked it for code snippets, and almost every code snippet it generated was indeed working or just needing few fixes.

They've been becoming good at this, but not enough to really replace my own coding and analysis. Instead, they're becoming really better for poetry (maybe because their training data is mostly books and poetry works) and sentiment analysis. I use many LLMs simultaneously in order to compare them:

• Free version of Google Gemini is becoming lazy (short answers, superficial analysis, problems with keeping context, drafts aren't so diverse as they were before, among other problems)
• free version of ChatGPT is a bit better (can keep contexts, can issue detailed answers) but not enough (it does hallucinate sometimes: good for surrealist poetry but bad for code and other technical matters when precision and coherence matters)
• Claude is laughable hypersensitive and self-censoring to certain words independently of contexts (got a code or text that remotely mentions the word "explode" as in PHP's explode function? "Sorry, can't comment on texts alluding to dangerous practices such as involving explosives", I mean, WHAT?!?!)
• Bing Copilot got web searching, but it has a context limit of 5 messages, so, only usable for quick and short things.
• Same about Bing Copilot goes for Perplexity
• Mixtral is very hallucination-prone (i.e. does not properly cohere)
• LLama has been the best of all (via DDG's "AI Chat" feature), although it sometimes glitches (i.e. starts to output repeated strings ad æternum)

As you see, I tried almost all of them. In summary, while it's good to have such tools, they should never replace human intelligence... Or, at least, they shouldn't...

Problem is, dev companies generally focus on "efficiency" over "efficacy", wishing the shortest deadlines while wishing some perfection. Very understandable demands, but humans are humans, not robots. We need our time to deliver, we need to cautiously walk through all the steps needed to finally deploy something (especially big things), or it'll become XGH programming (Extreme Go Horse). And machines can't do that so perfectly, yet. For now, LLM for development is XGH: really fast, but far from coherent about the big picture (be it a platform, a module, a website, etc).

As someone who thinks we are in an AI bubble about to burst, this article has "old man angry at the kids using new technology" vibes.

What's Copilot? ;)