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LLMs are eroding my software engineering career and I don't know what to do
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this post was submitted on 09 Jun 2026
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Programming
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It’s also patently false.
A good chunk of good patterns are to make sure humans understand it sure. But a good chunk of patterns exist to make individual components reusable and make sure you’re encapsulating requirements and testing them correctly.
A lot of LLMs take the “easy” way out and duplicate code, suppress listing, etc to make a prompt work. It works at that point in time but when you suddenly have a bunch of spaghetti and repeated code littered across multiple services suddenly making changes without causing massive regressions becomes a headache.
Companies are going to pay for this mess in several months as token prices go up and the codebase is a massive pile of slop.
That's going to be the bubble. When AI has to be able to actually pay for itself, no one is going to be able to afford it, and if you happen to be one of the companies that went all in any used AI to build your codebase and fire not devs and front line workers, you're going to be the hardest hit. Possibly the only hope is that they saved enough from partial and didn't pass any savings on to the customer (because of course they wouldn't) that they can almost survive the actual unsubsidized token costs. But then you will be in direct competition with everyone else who can write a prompt with likely literally no differentiator outside of maybe name recognition in an industry.
If the only problem is that your code is slop and nobody can work with it without AI, then it’s probably not that bad. Text models I can run locally on my five year old Macbook are maybe a year behind in terms of coding assistance. So AI for coding is probably never going away. The worst case for someone in this scenario is just that it gets a bit slower and dumber and that they have to hire more engineers again. It’ll suck but I think it’s survivable. Someone would have to make a new Stackoverflow though if we’re going to google stuff again.
Now if you integrated multiple AI services into all your business workflows and into the products you sell, on the other hand, that might be a different story. In a way the risk is the same as with cloud providers. You get locked into a stack and then your product literally dies if the provider decides you’re not paying enough, because you have no feasible way out. Tbh I would much prefer working at a post-bubble era software company fixing the codebase to working at a random company now extracting their IT from a hyperscale cloud. But in reality, most companies that bet on AI are in this scenario. Nobody only installed Claude and called it a day.