You don't need much mathematical knowledge to _merely_ be productive, but his points are valid.

1) The more math I learn, the more I realize how much I'm already doing it (via poor heuristics) without realizing it.

2) Mathematical training comes with many tools I would never think to Google without prior introduction. For instance, I sometimes use Karnaugh maps to simplify complex boolean logic. I'm sure there are many areas where I re-invent the wheel, miss simpler solutions, and generally produce less quality because I'm ignorant of the surrounding mathematical context.

I think this is a great example: https://github.com/Jam3/math-as-code

That page is a sort of rosetta stone for me after years of learning to code while also struggling with math notation. I find a similar fog lifts when I look at set theory through the lens of SQL and relation databases.

It amazes me that we still can't clearly demonstrate to children why math is important and instantly and universally instill a love and curiosity. Instead we have unforgiving educational models that are "well, you either get it or you don't."

It angers me to think of all the potentially _effective_ programmers who get their dreams squashed because they can't pass Calculus II (or other prereq.), and thus are literally not allowed to enroll in a programming course.

I didn't know about Karnaugh Maps but I use truth tables constantly in the design phase of tasks. Thank you very much for this. If you've found other tools like this please share. Not really related but for requirements I find gap and SWOT analysis to be vital tools as well as weighted pairwise comparisons. Throw in some UML diagrams and I start feeling good about things. These things impress far more people than they should.