I really don't think that's how it works. Smart, experienced developers who thought coding agents were junk for most of 2025 and think they're useful now in 2026 are not saying that because they got "worn down over time".

It tends to be when the training data wanders into their area of expertise temporarily and they go “OMG, they hype is real. I was so wrong” and then a few releases later they’re on the train and furious that the skills in their domain space have not just stopped improving, but regressed. Cue someone else in a different part of the world starting the same cycle.

Meanwhile the guy who leaned in a year ago and gave up reading the output is beginning to see work grind to a halt and throwing more agents at it is increasingly not working.

You can see these tropes all over social media near constantly.

As a smart, experienced developer who's getting worn down over time, I disagree.

I didn’t start using Claude Code until late 2025. Prior to that I would use ChatGPT to give me snippets of code but I was still doing most of the actual code writing. Coworkers told me in late 2025 about how they hadn’t written a line of code in “months” and just use Claude Code/agentic “whatever” so I tried out Claude Code and was pleasantly surprised. It is passable to have entire apps written by LLMs (I’ve made several that I otherwise never would have had the time to create by hand), but I wouldn’t say maintainable or easily extendable. It’s hard to be specific, but there’s something about LLM code that doesn’t look “natural”, and I’m not talking about the excessive use of comments in code. The code itself is unnatural. Functional, but unnatural. I wouldn’t want to suddenly lose LLMs and have to read through and understand and continue enhancing a codebase created by an LLM.

I was getting useful coding work done with GPT 3.5. I think devs saying "the models are finally good enough" this year are just trying to save face from their own previous irrational denials.