Solving Problems with Chatbots

Employee engagement is a big issue for any company, put simply disengaged employees leads to departing talent, so it’s vital to constantly be looking for ways to develop teams, especially those working with technology, in ways that result in high levels of ongoing engagement.

During a recent conversation about engagement and issues around internal communications, a colleague of mine suggested making better use of the screens we have deployed around the office to help keep everyone in the loop and up to date. This is an admirable idea but like all comms plans depends on the content more so than the delivery mechanism; the medium may be the message, but it’s important to have a message in the first place!

The conversation about content reminded me of an article in Wired from about a year ago about Github and how they had deployed a chatbot. What was interesting for me in that article was the story of how Github employees are extending the chatbot’s capabilities by scripting new features. What makes this doubly interesting is that not only are the engineers at Github doing this but so are non-technical people. One example in the piece was about someone from the marketing department creating a script that their chatbot uses to check on the status of local street vendors.

It occurred to me that a chatbot system like this could help out with two focus areas for developing team engagement. Firstly, it could provide that content that can be so hard to source. By making a conversational interface to a content management and deployment system, the process of gathering and displaying interesting material could be dramatically improved by providing a reason to generate content as it would give everyone an excuse to interact with the cahtbot. Secondly, having a chatbot system in place could provide an outlet for non-developers who want to spend some time learning development as it could provide a purpose beyond developing the standard issue “Hello World” script, without which too many people abandon their learning efforts.

anatomy_of_a_chatbot
Content generation would be part of the Workflow use case for a bot

Every summer we get a bunch of interns, and in addition to their regular assigned work they are tasked with completing a technical challenge. The challenge is meant to be, well challenging, and this year we settled on Chatbots (I suspect this was entirely my fault and an abject lesson in reaping what you sow)! One team of interns was tasked with setting up a bot that can field queries about one part of the business, while the other (my team) looked at connecting a bot to AWS in order to complete Cloud tasks through a chat interface.

It is something of a tradition that while the interns get on with developing a solution in their own way, I go ahead and do the challenge myself in my own way to determine if it can be done and how differently I’d tackle the solution over how the interns go about it.

As the interns had gone down the AIML route, I decided to deploy Hubot, Github’s own chatbot.

hubot

Up next: Getting started with Hubot

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