Make a web crawler that hits publicly traded tech companies careers page, once a day, and tracks how often their job listings change. Make a big line chart at the top of a landing page that compares the different companies job openings (by count), over time. Penalize listings that list/delete/re-list job openings to always make it seem like they are hiring. Maybe have a max time a job post can be open before it's no longer part of their count (3 months?)
What you'll end up showing is similar to this article: A lot of company's stock is evaluated on growth, and part of the growth estimation is based on how much they are hiring in this down market. Some companies know this, and are trying to game the system
Anyways, I bet a decent amount of people would watch that like a hawk, and the honest companies would love it because it would show how great they really are doing
I maintain a reactive, state management library that overlaps many of the same ideas discussed in this blog post. https://github.com/yahoo/bgjs
There are two things I know to be true:
1. Our library does an amazing job of addressing the difficulties that come with complex, interdependent state in interactive software. We use it extensively and daily. I'm absolutely convinced it would be useful for many people.
2. We have completely failed to convince others to even try it, despite a decent amount of effort.
Giving someone a quick "here's your problem and this is how it solves it" for reactive programming still eludes me. The challenge in selling this style of programming is that it addresses complexity. How do you quickly show someone that? Give them a simple example and they will reasonably wonder why not just do it the easy way they already understand. Give them a complex example and you've lost them.
I've read plenty of reactive blog posts and reactive library documentation sets and they all struggle with communicating the benefits.
function onLoginClick() { validateFields(); networkLogin(); updateUI(); }
Any study like this needs to have an explanation for the recentness of obesity and diabetes epidemics.