Give me some images and the kinds of transforms each color space is good at, and let me pick one, already implemented in a library in a couple different languages.
What's the best color space if I want pretty gradients between 2 arbitrary colors?
What's the best color space if want 16 maximally perceptually unique colors?
What color space do I use for a heat map image?
What color space do I use if I want to pick k-means colors from an image or down sample an image to 6 colors?
TL;DR: A color space just tells you where a color is in relation to others. From there, focus on your domain (eg. mine was "~all software", 2D phone apps) and apply. Ex. the gentleman above talking about specularity and CAM16 is wildly off-topic for my use case, but, might be crucially important for 3D (idk). In general, it's bizarre to be using something besides CAM16, and if that's hard to wrap your mind around, fall back to Lab*, (HCL) and make sure you're accounting for gamut mapping if you're changing one of the components.
CAM16 can't be the best answer to all of them, can it? It's possible but I'd think some color spaces are better suited for some tasks than others.
Which CAM16 are we even talking about? A quick Google reveals CAM16 UCS, SCD and LCD.
CIELAB I've heard good things about but then OKLAB became all the rage and now I don't know what's better.