1. Creating something
2. Solving puzzles
3. Learning new things
If you are primarily motivated by seeing a finished product of some sort, then I think agentic coding is transcendent. You can get an output so much quicker.
If your enjoyment comes from solving hard puzzles, digging into algorithms, how hardware works, weird machine quirks, language internals etc... then you're going to lose nearly all of that fun.
And learning new things is somewhere in the middle. I do think that you can use agentic coding to learn new technologies. I have found llms to be a phenomenal tool for teaching me things, exploring new concepts, and showing me where to go to read more from human authors. But I have to concede that the best way to learn is by doing so you will probably lose out on some depth and stickiness if you're not the one implementing something in a new technology.
Of course most people find joy in some mix of all three. And exactly what they're looking for might change from project to project. I'm curious if you were leaning more towards 2 and 3 in your recent project and that's why you were so unsatisfied with Claude Code.
I guess if you're in an iterative MVP mindset then this matters less, but that model has always made me a little queasy. I like testing and verifying the crap out of my stuff so that when I hand it off I know it's the best effort I could possibly give.
Relying on AI code denies me the deep knowledge I need to feel that level of pride and confidence. And if I'm going to take the time to read, test and verify the AI code to that level, then I might as well write most of it unless it's really repetitive.