this post was submitted on 11 Sep 2024
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Programming

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Over the past few years, the evolution of AI-driven tools like GitHub’s Copilot and other large language models (LLMs) has promised to revolutionise programming. By leveraging deep learning, these tools can generate code, suggest solutions, and even troubleshoot issues in real-time, saving developers hours of work. While these tools have obvious benefits in terms of productivity, there’s a growing concern that they may also have unintended consequences on the quality and skillset of programmers.

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[–] [email protected] 50 points 2 months ago (9 children)

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.

[–] Kuinox 5 points 2 months ago (3 children)

I browsed author own codebase and the first thing I saw is 150 lines of C# reimplementing functions available in the .NET standard lib.

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