The Pareto Principle, and technical challenges

Dave often says he wants get down to the technical level

But there is little point in doing so, in my experience, until the less
technical issues are framed correctly (scope, goals etc)

stratML aims to make explicit scope, goals  etc, of organisations
and their strategic plans

does stratML apply to technical systems such as software and AI?

Can we have a stratML scheme that explains what a piece of AI does
and how etc?  would that be useful? if it has been done, can we see
examples?

In systems development (in particular, software system development)
people start hacking code and demos because that is what they are
interested in-  but if  more research an analysis of the problem space had
been carried out first, maybe they would have come up with a different set
of system goals and corresponding solutions.

Technical issues are trivial, there are no real technical problems unsolved
but  plenty of unresolved non technical issues that end up creating
technical problems  that would not exist, had these issues been tackled
first.

There are many fun articles that explain the pareto principle in relation
to software, I always start my day with the Pareto principle (read it the
way you want it)

But in my technical life, I try to figure out  first the 80 percent of the
system/research I am trying to do  (analysis and design) and only after
worry about the 20 percent to the coding/implementation/writing up itself.

This was gold dust given to me while I was being schooled and it was one of
the most important lessons in my life. Do not trust code that cannot be
explained in plain language or programmers who refuse to speak to non
programmers about what they do.  Software should read like a book, give or
take some technicalities.

On this list we are still trying to figure out what is KR, why are we
talking about it, what are we trying to achieve etc. That is for members to
figure out
(I am working on my own stuff, while doing a lot of reading and sharing
what I learn).

 I understand of course that Dave may be interested in prioritizing what he
likes to do the most, which is doing great demos, but from a research
perspective I d like to ask what does the demo do, why, what problem does
it solve, what need does it fulfil, how does it address the issues being
tackled (in our case the bruning KR in ML topic) before devoting my full
attention and eyeballs to it
PDM