How do you keep humans in the loop when AI gets things wrong? One approach builds inspection and human review directly into the system from the start, treating imperfection as inevitable. The team started design work in 2018 and integrated it into their product by 2019, moving toward pricing based on outcomes rather than token usage.
But where does human judgment come in? There has to be a place in this new workflow where someone that actually has a thinking mind doesn't take AI at face value. I don't know if you've seen some of these TikTok things where people can really fool AI into giving a lot of BS answers. Where does that fit in an organization? Yeah, so governance is a crucial part. It's in its— we've been— we built our AI with remediation embedded into the product from day one. We know that back in 2018 when we were designing our AI, we knew that AI was always going to be imperfect and we had to allow for humans to remediate when the AI couldn't figure it out, and humans to inspect to make sure AI got it right. That was embedded into our product in 2019. And so, um, there are some really creative things, Joe, we're doing right now to allow for that inspection, but also to price in creative ways that will drive customers to get— pay for value and pay for outcomes rather than just paying for tokens.
