> I'm finding the challenge of getting AI-generated code to be robust, maintainable and better quality than if I'd typed it out myself to be deeply intellectually stimulating.
Yea that's why I started my comment with "it depends on the person", in response to you asking what's not fun about having AIs do what you tell them. For many, coercing a tool to do something you can likely do yourself better isn't ideal, and at least for me, is just inefficient use of time (in the long run) and a headache. It also zaps the fun out of any task since now you move from searching for a good solution using your priors, to now validating that the LLM has a solution that works, even if it's not optimal. The searching for a good solution is for some, the fun part, which is eliminated by agentic coding, since that search inherently relies on you writing code and seeing what works IMO. The coding is an essential part of the thinking here. An analogy would be doing a math problem by hand versus reading the solution in a textbook. I can give concrete examples if you'd like.
For your SVG examples, I have used AI for a similar use case, the construction of 3D scenes for robotics via a text prompt and an asset catalog. I wish I could get the same richness as your SVG examples, the LLMs fail too hard on all 3D tasks given, even after spending a high amount of engineering effort on a suitable harness + tools. Also like your SVG example, it often doesn't give a realistic, or even nice output, and coercing it to do so, likely takes longer than just creating the image/3D scene yourself.