[simonw]

I was confused by that too. I think I've figured it out.

They're saying that a public LLM won't know the email address of Jon Snow, but they still want to be able to answer questions about their private SaaS data which DOES know that.

Then they describe building a typical tool-based LLM system where the model can run searches against private data and round-trip the results through the model to generate chat responses.

They're relying on the AI labs to keep their promises about not training in data from paying API customers. I think that's a safe bet, personally.

[aidos]

Makes sense. I agree that it’s probably a safe bet too. Not sure how customers would feel about it though.

It’s also funny how these tools push people into patterns by accident. You’d never consider sending a customer’s details to a 3rd party for them just to send them back, right? And there’s nothing stopping someone from just working more directly with the tool call response themselves but the libraries are setup so you lean into the LLM more than is required (I know you more than anyone appreciate that the value they add here is parsing the fuzzy instruction into a tool call - not the call itself).

[simonw]

> You’d never consider sending a customer’s details to a 3rd party for them just to send them back, right?

I use hosted database providers and APIs like S3 all the time.

Sending customer details to a third party is fine if you trust them and have a financial relationship with them backed by legal agreements.