I wonder what's next. I suspect one interesting endpoint is that the excel model becomes the quantitative surface of a much deeper research graph / self-constructing ontology. I could imagine something like every quantitative revenue key driver being hyperlinked to a graph of the intermediate qualitative assumptions that underpin it. Maybe analysts use some kind of ambient capture during their desktop and field research process, and then there's an agent-mediated live evidence stream (e.g, expert calls, filings, transcripts, podcasts, articles, tweets, etc.) that supports or contradicts the analyst's assumptions in real time. And based on that you could calibrate your confidence about various qualitative assumptions at any given point (as new evidence comes in) and the model could compute how that flows through to quantitative KDs. Overtime, this surface / system would learn how new evidence shifts your priors and how accurately your updates actually end up representing economic reality. It could then start to understand how to weight different pieces of qualitative evidence! Lots to think about.