**Our Take: The Spreadsheet Trap That AI Can Finally Unlock**
This user's frustration is familiar to anyone who has tried to build a real portfolio tracker in Excel. They have the skills. They have the data. They have a clear goal, an "as at" valuation that calculates cumulative quantities, multiplies by the correct price, and handles missing weekend dates. And yet, they are stuck on a formula that should be straightforward but isn't. This is not a failure of effort. It is a failure of the tool.
Excel was designed for static tables and manual calculations. It was not designed to reconcile transaction histories with price databases across multiple accounts and dates. The user has already solved the hardest part, handling missing dates with a last-available-price fallback. The remaining problem is that their formula needs to stop summing transactions after a certain date, and the spreadsheet's logic fights them every step of the way. They are not asking for a new product. They are asking for a smarter way to express what they already know. That is exactly where AI-native spreadsheets change the game.
An AI-powered spreadsheet would not force the user to build a positions table and then debug why it breaks when dates overlap. Instead, it would let them describe the calculation in plain language: "For each date in my valuation sheet, look up the cumulative quantity of each asset from the transactions table up to that date, multiply by the price from the price master on the nearest prior date, and sum across all assets for each account." The AI would interpret the intent, handle the edge cases, like weekend gaps or partial months, and return the result. The user stays in control of their data, but the grunt work of formula logic disappears.
This is not about replacing Excel. It is about evolving past its limitations. The user has demonstrated deep expertise by structuring their workbook, normalizing price data, and solving the missing-date issue. They deserve a tool that meets them at that level, one that understands context, respects their existing data, and removes the friction of manual formula debugging. For anyone building complex financial models, the question is no longer "How do I make this formula work?" but "Why should I have to?" The answer is, you should not.