If someone just wants a library to power a chess UI this isn't really necessary. Either way I'd suggest the author finish off the current implementation until they can get perft and other automated tests up and running first.

That said, chess programming is a _wonderful_ education in Computer Science, and you'll be following in the footsteps of so many great figures in the industry. Understanding bitboards and how to work with them can take you all the way from the bit-twiddling chapters of The Art of Computer Programming, right up to recent advances in CPU architecture and instruction sets. Learning how search works will teach you both very low techniques and high level heuristics in performance optimisation. And of course you can go all all the way up to recent advances in evaluation from deep learning.

You need to consider the goals of a project before giving advice.

OP mentions chess AI and game analyzer. Those would benefit from an optimized data representation.

But both can also be written optimizing for simplicity and clarity at the cost of performance.

Competing with the state of the art is not an implicit goal for every project.

Perhaps they don’t need anything performant? You don’t need a bitboard for everything. (They’re also not always performant.)

Yea and you probably also need OpenCL or CUDA and several GPUs to get anything really “performant”. The basic OO model is good for its own purposes

If the API is well written, this is an implementation detail.

Well, it depends on the project goals. For a GUI app I can agree but good luck writing a chess engine where data representation is hidden behind an abstract interface.

Abstract as in using bit-boards or proper abstraction as in giving a clean interface to interact with a model and let the implementation worry about itself?