I agree with your most of your comment. * Scalable architecture is, most of the time, a very-NOT-big-deal. Bots tend to be relatively lightweight apps, sending

I agree with your most of your comment. * Scalable architecture is, most of the time, a very-NOT-big-deal. Bots tend to be relatively lightweight apps, sending/receiving json data only. Even websocket Slack apps can now be replaced by HTTP API. * Discovery is really un-solved at this time, especially by Facebook. Slack does a better job, but arguably has a smaller ecosystem of B2B bots to manage and promote. However, I think the article is about a rather ambitious (more than usual) and interesting bot. Having to parse normal language symptoms into medical terms is 1) an interesting use case 2) hard to do well technically. So maybe they face challenges most bot dev don't face. Design-wise, most people don't see how hard it is to design chatbot flows that hard not horrible and confusing. Most chatbots are horrible and confusing at the moment, because coding bots is easy, designing them is really hard. I think the article make interesting points about their own specific case, but their situation is perhaps less general than they seem to think.