That answer was as expected, a bit generic and pulled from a variety of sources and trying say it in a way that duct tapes them together into a Frankenstein Monster—functional, but a bit off, and could fall apart quickly, causing the whole village to come after it with torches. AI works best in distilling information it's trained on, which means you can create some pretty great troubleshooters and guides when you train in on very specific things, or in this case, specific methodologies and studies. I use it for deep research, feed it workbooks, courses, books, and the like all the time. For instance, Gemini Notebook is an absolute incredible research assistant, and really good at picking apart something on a technical level. The podcast feature is "okay" at teaching you a subject, but even better when you tell it to critique something you wrote on a subject. It will find every single hole it can. But for knowledge, Q&A, advice, and the like, you still have to know enough about the subject to fact check it and error-correct. I can't even count the amount of times I had to call an AI chatbot out on something it was severely wrong about. Most of the time, it corrects itself when you do that. A couple of times, I had to argue with it and present proof that I was right—and that was for legal paperwork that I couldn't afford to get wrong! So, not exactly trustworthy as an expert on anything, even when you train it on very specific things. That said, I'm still working on a troubleshooter chatbot for my courses. My first iteration of it was interesting and mostly right. But even with notes, transcriptions, and very strict instructions on how to answer, it still would make up stuff and interpret my course material in ways I would never suggest something. Sometimes that was helpful, sometimes it wasn't. I at least got it to where it wasn't suggesting things that would hurt anyone.