* The '90s "Access in 24 hours" programmer has been replaced by the latest anecdote-based technique/toolset preacher; e.g., TDD.
* Becase deep learning is better than humans at finding useful patterns in data (whether concerning biochemistry or web site interaction) it is the best technique.
* Aesthetic (e.g., language) and social justice (e.g., feminisim) issues distract from utilitarian effectiveness.
* Utility is only furthered by math and science (where for "science" read "patterns inferred from data"), and we should aspire to be "scientific programmers" who apply only math and science.
My biases may be guessed at in my summarization, but let me make them more explicit.
I think it odd that some of the techniques he rails against are inspired by mathematics: TDD tries to preserve invariants; RESTful design tries to impose the invariance of idempotency. If the question is whether those techniques make those who use computers more productive, then a scientific answer would involve a stunningly expensive human subjects experiment involving large numbers of people and complex problems. The likely result would be this: https://xkcd.com/1445/
I'm a sysadmin doing my best to automate (e.g., puppet); I rarely have the luxury of collecting data sufficient to the immediate problem, so I rely on math and (unreliable) heuristics. I write perl/shell/puppet/ruby/anything in small fizz-buzz complexity chunks; an "artisan" if you will. I support CAE environments with low-latency and poor parallelism opportunities, and until that changes (e.g., becomes cloud compatible) I don't see my tactics changing significantly.
Your summary is indeed very biased. Maybe someone could use the first bullet point. Better to look at the last paragraph:
We got to grow up and go back to school, relearn all about Maths, statistics, and generally scientific reasoning. We need to man up and re-learn that being a good coder has nothing to do with the number of stickers you have at the back of your Mac. It is all scientific - we come from a long line of scientists, we have got to live up to our heritage.
* The '90s "Access in 24 hours" programmer has been replaced by the latest anecdote-based technique/toolset preacher; e.g., TDD.
* Becase deep learning is better than humans at finding useful patterns in data (whether concerning biochemistry or web site interaction) it is the best technique.
* Aesthetic (e.g., language) and social justice (e.g., feminisim) issues distract from utilitarian effectiveness.
* Utility is only furthered by math and science (where for "science" read "patterns inferred from data"), and we should aspire to be "scientific programmers" who apply only math and science.