One other connection between these two is the fact that for AI assisted coding you can <i>only</i> get the AI to write you code that has broad adoption on the internet. Otherwise the AI doesn’t know the standard libraries and conventions.<p>I worry overall that this could signal the complete end of new programming languages except in a few special cases. (Which I think was already a worrying trend before AI- see Bret Victor’s “The Future of Programming” talk).
The larger point is that by keeping non-strategic part of your tech stack boring, you can focus on core innovative technology. In this guy's case it's LLM.<p>Which is same point that the original post "choose boring technology" makes. I don't see the contradiction.
Agreed, especially for "serious" project, where LLMs are a good approximation of an average dev that could easily increase your bus factor.<p>On the other hand, this could be the same slippery slope that starts at "choose a boring project because it has mature tooling" but ends at "IDE's are a language smell". If the language is so boring that you can't focus on it without an LLM doing the menial work, that could be because there is too much menial work to start with.
How does it work with mainstream technologies that are being actively developed?<p>Did anyone try working with LLMs and Swift for example? Is the AI suggesting deprecated libraries from earlier iOS versions / generally having trouble? Or is it working fine?
I guess Go is quite fine for his use cases, but I suppose if suddenly he had to delve into more frontend-focused apps or AI development, he would be forced to use Javascript and Python.
I’d say it’s more being deliberate about how much new tech you incorporate into new projects. One small and ideally isolated new piece in each project is a good idea else you’ll stagnate
And boring areas of enterprise or professional world with boring classical techniques for software engineering while applying LLMs. I see a lot of potentials.