then what should sites be thinking about before they dive in? And what are some of those mistakes that you see often, especially when we're talking about what you just shared this sort of methodical approach to it?

So before a site even spends a dollar, I would have them answer just their, I would say, three top questions.

One, which single workflow hurts the most every week? So what is constantly a pain? Because I know a lot of sites go through the process of telling their sponsors what is hurting and get ignored or pushed to the side or say, don't break the wheel kind of process.

So basically, which one is hurting and keeps hurting? The second one would be two, who is the named human reviewer? So who is the person you would go to for these reviews or assigned? And then also three, what's that one success metric that tells you whether it actually worked? And then if they do get those three kind of Hammered out along with their team and they've dodged most of the pain out of there.

It's really because the common mistakes are just the mirror image of those questions.

So trying to transform everything at once, dropping the sensitive data into general purpose tools, which never good thing.

And then also treating AI output as the final annotation.

So I want to conclude our conversation today and learn a little bit about what you all are building and how it speaks to everything we've been talking about and where you see the site's role ultimately then heading as all of this continues to evolve.