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[–] 29 points 21 hours ago (1 child)

Building software at scale has always been an exercise in managing complexity. We carefully architect systems to be maintainable even at huge scales. And no one can do this quickly. I think writing code by hand gave us some think-time to ponder these architectural decisions.

But with AI, the thinking time is gone, but the problem of managing complexity remains. Typically, however, nobody above the devs gives a shit about managing complexity--that just sounds like something that eats into the bottom line. It is, as certain people might say, "loser thinking".

A lot of software engineers like to work on projects where they can be proud of what they've made. A beautiful architecture doesn't only shine in its own right, but it also makes the company run smoothly, makes the customers happy, and improves the bottom line.

And when you don't have those things for the product that you're pouring your heart and soul into 996, is anyone truly surprised that devs are unhappy?

"The night of the fight, you may feel a slight sting. That's pride fucking with you. Fuck pride. Pride only hurts, it never helps." --Marsellus Wallace, Pulp Fiction

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  • [–] 10 points 19 hours ago

    I do resonate a lot with this. Also, another detail: with the speed of ai churning mostly not correct by itself results most of the time gives 2 big things:

    • a much bigger effort of reviewing spaghetti code and hope it makes sense and nothing bad comes out of it (keep in mind generated code can be heavily verbose and without need to do so)
    • without the thinking hard part of the code, making a cohesive architecture is a lot harder.

    Problem is, when the solution is "press button and hope the slot machine gives the good spaghetti back to you" is the answer, you're fucked.

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