I was talking about novel/real-world applications. With software, you can pretty much know in advance what will work, ROUGHLY how much it will take and how much it will cost. With ML you have a high chance that ML will not work at all for your problem, or that YOU won't be able to solve it.

I'm a java developer and during my first 3 years I was able to investigate bugs not only in my code, but inside jboss or hibernate ORM; I can look up core java code and understand it just fine.

How many of the ML self-taught crowd can write framework-level code, or debug a ML algorithm bug?

Fooling management wanting to get into ML with some scikit code is easy, mastery of ML is orders of magnitudes harder than mastering a programming language/frameworks.