I don't see the need to make the Joel Test sound so nefarious. The Joel Test was content marketing, yes, but not of the FogBugz tool (while a bug database is item 4 out of 12, he doesn't even plug FogBugz in the item - it was a recruitment piece more than a sales piece). The reason we're still talking about the test is that it really struck a chord - it listed practices that were true and important, but not widely held to be so. Today, it's mostly redundant, because those practices are now totally uncontroversial standard industry practice, but it's worth dwelling on the fact that not too long ago you could "content market" recruiting developers by promising them source control systems and an Excel sheet of bugs.

Don't go too fast. It is widespread in the startup world. In entreprisey world not so much. Here we have no version control, no continuous build and bugs never get solved.

Don't even think about Hall testing. And the people that hired me asked no question about my coding ability nor my Github account. And it is not a small company, nor an isolated thing.

And don't ask about the tooling, i spend my days fighting it... not being able to use package manager due to bad proxy is a PITA.

The Joel Test is still on my list of things to check with every company that want to hire me now. Because i see what happen when it is not respected every day...

I don't intend to make it sound nefarious. Lots of people were saying that this piece was a sales piece as if it should be dismissed.

I actually love well-written content marketing as it is often highly educational. Other examples include:

- DigitalOcean paying people to write tutorials on server configuration

- MIT paying students to write blog posts on life at MIT

- Ksplice writing a post on the uses of strace.

One of the points in particular seems highly dependant on the product category you are analyzing: ability to put data science models into production. You might be working on some product that can't dynamically respond to stimuli as that seems to imply. My team's work influences product decisions frequently, but it would be contrived to actually deploy our models to the product in many cases.

Another that may not apply is the stuff about reproducing past experiments. Suppose your experment platform is programmatic and interfaces with some codebase. Old feature flags are a form of tech debt that should be removed. So old experiment code is sitting in a repo history somewhere but not necessarily deployable.