Interesting to hear the perspective of an experienced developer using what seems to be the SOTA coding assistant of Cursor/Claude. I thought his "Changes to my

Interesting to hear the perspective of an experienced developer using what seems to be the SOTA coding assistant of Cursor/Claude. I thought his "Changes to my workflow" section was the most interesting, coupled with the fact that coding productivity (churning out lines of code) was not something he found to be a benefit. However, IMO, the workflow changes he found beneficial seem to be a bit questionable in terms of desireability... 1) Having LLM write support libraries/functions from scratch rather than rely on external libraries seems a bit of a double-edged sword. It's good to minimize dependencies and not be affected by changes to external libraries, but OTOH there's probably a lot of thought and debugging that has been put into those external libraries, as well as support for features you may not need today but may tomorrow. Is it really preferable to have the LLM reinvent the wheel using untested code it's written channeling internet sources? 2) Avoiding functions (couched as excessive abstractions) in favor of having the LLM generate repeated copies of the same code seems like a poor idea, and will affect code readability, debugging and maintenance whereby a bugfix in one section is not guaranteed to be replicated in other copies of the same code. 3) Less hesitancy to use unfamiliar frameworks and libraries is a plus in terms of rapid prototyping, as well as coming up to speed with a new framework, but at the same time is a liability since the quality of LLM generated code is only as good as the person reviewing it for correctness and vulnerabilities. If you are having the LLM generate code using a framework you are not familiar with, then you are at it's mercy as to quality, same as if you cut and pasted some code from the internet without understanding it. I'm not sure we've yet arrived at the best use of "AI" for developer productivity - while it can be used for everything and anything, just as ChatGPT can be asked anything, some uses are going to leverage the best of the underlying technology, while others are going to fall prey to it's weaknesses and fundamental limitations.