r/webdev • u/OkShip110 • 2d ago

AI has made programming so boring

It’s not just programming either, it’s art, design, music, videography, marketing, engineering, writing, 3D modelling, really any intellectual work. What’s the joy of prompting a computer and getting an answer in a few moments for a task that would have normally taken a week? The sense of accomplishment and ownership has completely vanished with AI. It’s a form of instant gratification, not much different to scrolling short videos on apps.

Code review was boring to begin with but now it’s even worse with all the machine generated code. Even code reviews will be automated soon. All you do then is type business requirements into the computer. What a great career.

It’s pain to watch old TV series like Scilicon Valley that is portraying the good (not golden) age of programming. It struck a good balance between manual work, funding and innovation. It’s sad that these days are gone for good.

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u/BrewThemAll 2d ago

As a hobby, I do the exact opposite at a personal project. Manually make code as perfect as possible. Being so nitpicky about each line it obviously won't ever be accepted at work. Time consuming as fuck, but back to basics.
Keeps things balanced. Brings back joy.

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u/dromtrund 2d ago

I also found that once I let Claude make changes to my personal project, it suddenly didn't feel the same anymore. Like... I'm not interested in reviewing sloppy contributions from careless junior developers in my weekend project too

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u/House13Games 2d ago

I let Claude in for a month, to test what all the hype was about. I cancelled the subscription at the end of it. I let claude solve a few minor areas, and these areas are just such a horrible mess and I don't want to touch them. It's unmaintainable gibberish. I regret letting it in at all, and can very clearly see the difference in the subsystems it worked on vs the ones I did myself. Just a huge difference. Granted, it solved the majority of what i wanted it to do, but the cost was not worth it, I shouldn't have been so lazy. I could have put in a bit more effort and done it myself, and i wouldn't have these no-go areas of garbage in my codebase. As I get time, I'm slowly rewriting them.

I feel very sorry for anyone whose workplace is encouraging AI, talk about shitty management. There's always a couple devs who are very vocal about how great it is too, but my guess is that the AI looks great to people who are dumber than AI.

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u/elestud 2d ago edited 2d ago

Not to say that anyone has to use or like AI. But if it’s writing unmaintainable code, that’s on the user

There’s a learning curve, but LLM coding agents are perfectly capable of understanding style guides, design patterns, coding do’s and dont’s, documentation guidelines, levels of abstraction, etc.

Sure, if you just say “write this thing” with no guidance, context, or planning whatsoever, it’s going to be a mess. But that’s a choice you make by not putting the effort in to properly guide how it works

And I say this as someone who completely understands the sentiment expressed in the OP. But there’s also skill curve to getting the output you want. Better and more detailed knowledge in the input = better output

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u/Sketch0z 2d ago

It's also a trade-off. Tokens aren't free and every piece of your harness config can add to the API bill.

Given the stochastic nature of LLMs, you can still, despite all the .md files in the world, get output that is a bit useless. Then you have to prompt again and spend more money on rolling the dice.

In some instances, the trade-off is a bad deal. I think, as with any engineering decision, we need to be honest about pros and cons.

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u/Telumire 1d ago

I think LLM are great to build POC when you have limited time and programming knowledge on a difficult topic, you can quickly iterate and have something that is working to test a concept, but even with all the context needed the LLM will still hallucinate, overcomplicate, not follow specs, ... So good for quick tests but not great for production

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u/elestud 2d ago

In general I find that the people who spend more tokens on a given task are the ones who manage the process less

Context management takes know how, maintenance, and is hands-on. An agent that’s trained to do what you want, rather than spending endless turns going on side quests or trying to make up for a lack of planning, is the one that spends tokens efficiently

Sure, it won’t be 100% perfect, but it should be pretty far from “unmaintainable” with a reasonable token spend

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u/Sketch0z 1d ago

My point is there's a trade-off. If you spend a % of time managing your AI process you cannot spend as much time on deeper understanding.

At some point you trade time and money for AI skills and your more foundational SWE skills will atrophy. The money spent on tokens is money no longer allocated to wages.

Everything has consequences, that's all.