[sesky]

But the quality of code was already very bad due to market forces. Most code at large companies is notoriously poor despite the talent density, because the incentives are not there to tackle tech debt or improve code quality.

With such a low baseline, there is an optimistic perspective that LLMs could improve the situation. LLMs can produce excellent code when prompted or reviewed well. Unlike human employees, the model does not worry about getting a 'partially meets expectations' rating or avoid the drudgery of cleaning up other people's code.

[devin]

The model is optimized in a different way to "partially meet expectations". Sycophancy coupled with only really "knowing" what it has been trained on assure a different kind of mediocrity.

[switchbak]

The same incentives that discourage good code in pre-AI times are still dominating now. You will be pushed to ship sub-par products in the future, just like you were in the past.

AI certainly has the potential to make the underlying code/design a lot cleaner. We will also be working with dramatically more code, at a much higher rate of change. That alone will be a big challenge to keep sustainable.

The ones making the decision to under-invest on design are either are unaware of the real costs, or are aware and are deliberately choosing that path - that's not new, and I don't expect it to change.

[demorro]

The only thing that has changed is that there used to be a loose correlation between capability to effect change and inherent desire for quality. This correlation barely exists anymore, so the counter-cultural acts that happened to manifest quality inside our perverse systems will occur much more rarely now.