I tried going through the site and also the comments but couldn't wrap my head around what this library actually is. It sounds awesome based on the response/comments. Can anyone explain this to a layman?
The fact that you defined your model as a symbolic graph means you can derive gradient equations automatically, hence ridding you of a rather tedious step in optimization. With such tools, the workflow for a practitioner is much simpler: 1-code models as graphs of symbolic expressions, and 2-define objective functions (ex. for a regression problem, your objective would be the root mean squared error, plus some regularization). Disclaimer: I did not look at the code, but from what I understand it is pretty much the same as Theano (which I've been using a lot lately).
The problem is that there are about 3-5 alternatives out there, and none of them are mature enough or convincing enough to dominate. The field changes so fast that it's easy for them to become obsolete.
What you're seeing here is the enthusiasm of people who really want to get a good tool with proper support, and be able to stick with it. I'm still not sure if TensorFlow is that tool, but it depends on what will happen to it during the coming years.