The hard problems should be solved with our own brains, and it behooves us to take that route so we can not only benefit from the learnings, but assemble something novel so the business can differentiate itself better in the market.
For all the other tedium, AI seems perfectly acceptable to use.
Where the sticking point comes in is when CEOs, product teams, or engineering leadership put too much pressure on using AI for "everything", in that all solutions to a problem should be AI-first, even if it isn't appropriate—because velocity is too often prioritized over innovation.
That's how I have been using AI the entire time. I do not use Claude Code or Codex. I just use AI to ask questions instead of parsing the increasingly poor Google search results.
I just use the chat options in the web applications with manual copy/pasting back and forth if/when necessary. It's been wonderful because I feel quite productive, and I do not really have much of an AI dependency. I am still doing all of my work, but I can get a quicker answer to simple questions than parsing through a handful of outdated blogs and StackOverflow answers.
If I have learned one thing about programming computers in my career, it is that not all documentation (even official documentation) was created equally.
Gone are the days of hopeless Googling where 20 minutes of research becomes 3 hours with the possibility of having zero solutions. The sheer efficiency of having reliable, immediate answers is a tremendous improvement, even if you're choosing to write everything by hand using it as a reference.