·3 min read
Grounding is the product decision
A bigger model doesn't know your course any better than a small one. Grounding is the difference between a confident guess and a correct answer.
It's tempting to treat model size as the whole story. In a real product, the gap between a good answer and a bad one is rarely about parameter count. It is about what the model is allowed to see.
Campus answers are built from the actual course: the syllabus, the lecture notes, the reading list, the calendar. The model's job is to read that material well, not recall a fact from the open web.
That constraint is a feature. Every answer can point back to a source. Every wrong answer is traceable and fixable. The system improves as the course material improves, not by waiting on the next model release.
Bigger, more general models still matter. They are the reasoning engine underneath. The product decision that actually changes the outcome is what we ground them in.
The TruFyre Way
A bigger model still does not know the course. TruFyre builds products that retrieve the syllabus, notes and calendar, and stay quiet when the pack is empty.