AI review generally will find fault in anything. Any non-trivial code has multiple solutions with different tradeoffs. Any code can be over-engineered for theoretical edge cases and future use cases you don't need. No matter which solution you pick you can always at a minimum say that some alternative just looks and reads better.
Code is somewhat artistic. If you don't have well defined standards and priorities, the AI review cycle can spiral infinitely figuratively debating what makes art good, and your code will be no better for it.
Tbh, so what? I googled "symbolic math engine in Typescript that can perform evaluation and simple expression reductions over +-/*()" and got what looks to be viable answers without using any AI model at all. Reciting well established things from memory isn't terribly interesting. Show it a novel codebase and have it implement something within it.
Loads of brands are nothing more than a logo on some Chinese generic products like that. Google "best hand coffee grinders" and see how many of the 100 dollar models you can find identical matches for on eBay for 20 bucks.
Maybe the eBay ones are QC near-fails or knockoffs, but it's hard to tell without buying a bunch to inspect.
Code is somewhat artistic. If you don't have well defined standards and priorities, the AI review cycle can spiral infinitely figuratively debating what makes art good, and your code will be no better for it.