· ai-devtools
Catching prompt injections hidden in PDFs
Some months ago, I was tasked with defining what "QA for AI applications" would look like at work.
It's been one of the most rewarding and most fun journeys of my professional life. I don't have a great segue into how it all happened and what I did in the early days, so here's one of my larger efforts: we have an internal tool that reads PDFs of financial data: SEC filings, account statements and the like.
The idea here was that I would do traditional QA and automate tests to make sure each document type was parsed properly so we could catch regressions. Except there's already the problem of what "properly parsed" amounts to and then how to decide whether a new model does a better job and/ or does it at a lower cost.
This is better done at the Golden Dataset level than spending CI time grinding through a matrix of documents every run. This deserves a post of its own. And then I asked about prompt injection.
