One of the easy things that he was programming it to do was, if you put in a Minute clinic and a zip code, it will tell you what the wait time is at the local Minute clinic. In zip codes there’s multiple stores. There’s some issues there but what would really be powerful would be if it was truly localized to the individual. What I mean by that is, here at the studio we eat out at the restaurants that we have access to here in Arlington Center quite a bit.

What would be easy, what would be great is if it knew when we say Thai restaurant, it’s talking about one specific place. If we say the Burritos, it’s talking about one specific place. Suddenly, that thing with the local contact as a bot will be able to make a round trip orders for us in seconds. We type in what we want and then it’s all just done, but with the bots being designed as these global things, it can’t discern when I say Thai, that it means the restaurant to our left, not across the street and to our right. If I say pizza, it means the place that’s a lot farther, that’s really good as opposed to the place that’s closer and sucks.

There’s this gap with programming being done at the global level, we’re trying to write a bot that covers everyone everywhere in a generic way. The usefulness doesn’t get that deep. Where it gets deep is where it’s more localized, where it’s more specific to us in the examples I’m using just because of the very micro geography that we’re in and our taste preference as opposed to the more generic glom and so bridging that gap, is where a lot of the really exciting things will start to happen in the sort of software you’re talking about to really get at the local personal level and convert that into care as opposed to the generic and the macro.