Excel is one place where AI makes sense. All the data is there, in a nice structured and typed format with headings etc. Easily verifiable and to provide the reasoning for its work.
I swear none of you guys have even attempted to use AI to do data analysis. I have, I built a MCP and integrated a copilot agent into Teams which has access to specific database data, and refined the rules for it to the point where the CFO rigorously tested it (and still does) and trusts the results it returns.
Excel is one place where AI makes sense. All the data is there, in a nice structured and typed format with headings etc. Easily verifiable and to provide the reasoning for its work.
LLMs can’t count. Can’t add. Can’t deal with actually large datasets
How is excel a good fit for vibe-coding?
This isn’t just an LLM. It uses excel functions and features to do the counting and adding and dealing with large data sets.
It’s not “vibe coding” as much as “vibe performing steps in excel”.
Also LLMs absolutely can deal with large data sets anyway. Not sure where you got that from.
It could be good to layer in standard machine learning (ML), and it already does have some features (like line of best fit).
However, in today’s context AI means LLMs, and that is not a good fit due to its unpredictability.
Until it starts pulling data from nonexistent worksheets
You tell it not to.
I swear none of you guys have even attempted to use AI to do data analysis. I have, I built a MCP and integrated a copilot agent into Teams which has access to specific database data, and refined the rules for it to the point where the CFO rigorously tested it (and still does) and trusts the results it returns.