this post was submitted on 22 Aug 2026
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I can kind of relate. There are a lot of parts of coding I find a little boring.
When you use an expensive AI agent, like Claude, it can nowadays handle these tasks competently, to the point where I only need to correct small things here and there.
When you give these tasks to an AI agent, it feels a bit like delegating to a junior, but without the guilt of giving someone a menial or boring task. That allows me to work on stuff I find more interesting. To me, THAT'S why it's adictive.
However, this isn't without cost. First, there's the societal costs: Environmental, centralization of power, contribution to hardware shortages and a bubble
Second, there are more personal costs. You'll come to rely more and more on these tools, and your skills will rust. You may end up avoiding learning things about a codebase because you delegate it away.
It's a tempting tool. One which in my experience can genuinely help, but is easy to misuse.
Wow this is all so true and well put.
Some colleagues are showing off 20k+ line change commits with no review. Whilst I'm at most doing 100 lines, usually 10 or less. I am reading each change. Every plan is read thoroughly with multiple iterations. If I don't understand a part, I ask the AI to explain. It is surprisingly good at explaining the work. However I do find mistakes. I have it commit after every change after the tests work and I'd say a third of the commits are prefixed as "fix: ". I'm still on the fence about the whole thing but it feels good and weird and phoney at the same time.
I feel like: we've been developing these "best practices" of documented traceable requirements and design specs, repository storage of the whole change history, trace matrices showing test coverage / validation of all requirements and specs, code reviews, etc. etc. etc. and... for the most part... if you've got exclusively good responsible programmers on your team, most of that is a waste of time. But, when you have personnel turnover, people with ... marginal skills, etc. those practices become much more important, even if they more than qunintuple the time required to do a thing, they enable projects to grow and be maintainable at much larger scale than if you don't do them.
And along comes LLM agents, who strongly resemble those fresh hire colleagues of marginal skills, and they don't complain about these "best practices" wasting time, and they're so wicked fast that they can cut through the process that used to take 500% as long in 20% of the time instead... No, they're not the greatest at getting things right on the first try, but they have been getting good at catching and correcting their own mistakes. And I can type messages like this one while they work on things that don't need my attention...
Our primary use of the Cursor LLM agent is: code review. Refinement of the review to clear out the misconceptions - improvement of the pull request documentation to make intent more clear for everyone - not just the LLM agents.
We also have come (lately) to rely on it for writing unit tests. A year ago the LLM written tests tended to be ineffective, just "whitewash" coverage that didn't really check the important aspects of the requirements. Today, they're probably better than our Sr Sw Eng written unit tests, and you can crank the coverage arbitrarily high with very little effort.
One of my big criticisms of the .NET toolchain is that even simple changes can touch 47+ files, thousands of lines of code, and take hours just to have eyes on everything that changed, whereas a similar change in my Qt/C++ might be one line, or up to a dozen here a dozen there in maybe 6 files, but never the mess I've been seeing come out of .NET/WPF and friends for the past 20 years.
I mean, if you're curious and you're diligent, you can learn from what the AI chugs out. Skills only stagnate when you trust the AI blindly.
I'd say the bigger problem is that when you're outsourcing junior coder work (even the tedious stuff) to a machine, you're not investing in new junior coders.
I don't trust the AI, I just can't be bothered to argue. At the end of the day it's no longer my code, so I feel no guilt about pushing in slop.
Trust But Verify is a good policy regardless of where your code comes from.
"AI" code is still human code in some capacity. Human code is what it was trained on. What would you do with a module you grabbed off GitHub or a script you found on Discord? Hopefully the same thing.
Yeah I relate strongly with this. Once you get used to having more time and energy for the tough problems, the interesting stuff, it’s hard to go back to the mechanical and menial.
But I’ve found it’s a lot like riding a bike. You don’t really rust, because the stuff the agents can handle today are the kind of shit that you’ve done so much and from the start, that it has become menial and boring. Which means it’s pretty ingrained into the backbone, at least that’s what I’ve found.
But damn if I don’t feel bad about it, recognizing and being conscious about the societal and environmental cost the convenience has.
Don't get too bent about the environmental costs... the (US) AI data centers pollute about the same as 11 million office commuters. So, the great corporate leaders who are trying to mandate 30 million work-from-home workers back to the office are advocating for 3X as much pollution increase as the current crop of AI data centers emit.
I keep having the issue where I ask AI to do one small but tedious task, e.g. a refactor, and it sloppifies the rest of the code while it’s at it