Walkthrough
The story
How a .deepcell file gets built, act by act — the claim, the assumptions under it, the calculations that produce it, and the history of every change.
Notes on conclusions that keep their assumptions — and the agents that write them.
The number an AI hands back is only as trustworthy as the way it touched your file. Three ways it can — and why only one of them keeps the model alive.
openpyxl on a binary .xlsx, raw .deepcell XML, or the deepcell CLI. Same task, three very different affordances. Here's why the agent picks the CLI.
Better AI on Excel can't fix what's structurally wrong with the file. So we built a new one.
The cell says 78.4% — but why? How a .deepcell keeps the reasoning behind every number, long after the chat that produced it is gone.
Values flow both ways. Structure travels one direction at a time. Here's why that's the right tradeoff.
Two paths, one non-destructive import, and an honest note about formula conversion.
Eight plainly labeled sections. Open one in any editor, read it like prose — and leave whenever you want.
The file is the shared surface. The agent reads, edits, and proposes; the analyst signs.