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.

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.

  • @[email protected]
    0•2 months ago

    I’ll bet people said the same thing when Intellisense started suggesting lines completions.

    They did.

    And when errors were highlighted in the code rather than console output.

    Yep.

    And when high-level languages started appearing.

    And yes.

    That said, if you believed my mentors, we were barelling towards a 2025 in which nothing running on software ever really worked reliably.

    So they may have been grumpy, but they were also right, on that point.

    • @[email protected]
      0•2 months ago

      I mean with the “move fast and break things” mentality of most companies nowadays, I’d say he was spot-on