[peterbell_nyc]

A big chunk of the knowledge contained in enterprises is in spreadsheets. It's a no brainer to make that more easily accessible to LLMs. Wrap a thoughfully designed agentic framework around this and you presumably get a cheap junior data analyst that you can ask arbitrary questions of to better optimize value delivered through the knowledge you have. Anything from "free" drill down reports by territory on sales or ops to potentially running monte carlo simulations based on identified correlations to get a sense of the best classes of improvements to invest in to reduce shipping costs, improve sales conversions in specific verticals, etc.

I don't know if this is the framework, but this is one of the problems that needs to be effectively solved for large spreadsheets to unlock access to the data more efficiently.

[echelon]

> agentic

This is the hot new word in the LLM space. Was this picked because LLMs are losing luster for broad, cross-domain applicability? What systems actually demonstrate this behavior?

I'm not short on LLMs, but I can see a future where Gen AI in the creative space (image, audio, video) outpaces LLMs in terms of impact.

[syrgian]

I was trying to write a decent definition but Wiki does it better: https://en.wikipedia.org/wiki/Large_language_model#Agency

In this context it could be able to do multiple actions in order to address an ask from the user: read cells, documentation, edit cells, and perhaps even read the result from the edited cell before answering. i.e. "Can you create a new sheet that focuses on the Countries where the sales happened, including YoY differences, and tell me which countries are outliers and for which reason(s)?" (probably very far fetched given the level of progress Excel has achieved in 20 years).