AI summaries need receipts: how I built evidence-bound reports from comments

A mistake I keep running into with AI feedback tools is treating the summary as the product.

Getting a model to write a confident paragraph is no longer the hard part.

The hard part is making every useful claim traceable back to the messy source rows that produced it.

I ran into this while building a tool around YouTube comments. Before building this, I spent a lot of time reading YouTube comments manually as a creator, and that probably shaped how I think about this problem.

A creator, founder, or marketer does not just need "people liked the video" or "viewers want more tutorials." They need to know which comments support that claim, whether the signal came from one loud comment or a real pattern, and whether the model invented a clean story that the comments do not actually justify.