maybe the problem is the 4day workweek. I worked 30h for some months and 32h for half a year in between always fulltime. People want to shovel one day free and then add a weekend but that creates all those sync issues and makes them just less productive.
But instead work 6h every day in intelligence jobs like programming. When I did that I had zero sync issues because in core time I was always there, I had no downtime during work. Effectively I got just as much if not more done than fulltime but still everyday felt like I had half the day to myself (going swimming ...). It is a worlds difference in quality of life (unless you have to fill the free time with other family work or waste your life on Netflix).
If I was an employer in IT, I would only hire 6h day workers (full pay). No breaks but no more than 6h 5 days a week. I can do 6h concentrated work almost any day with an afternoon/evening of other things. 8 or 12h only works occasionally on average when I work 8h I add more than the 2 extra hours of time wasting, because less satisfied/concentrated/happy.
SQL queries that can beat NoSQL are easy but you still have to think about schema.
Which you can just not do in K/V(you just need the key) or NoSQL.
As such it makes starting really easy which is the allure. Many seem to hope they can avoid doing schemas and well architected data. Or push it in to the future.
The rude awakening comes when you do need to run complex queries (and you do not have SQL or joins at all). Or when the people do not understand they have to take care about data integrity in app layer now.
At the end people going for NoSQL have a much harder to manage system without the tools (like SQL, schemas, constraints)
I think NoSQL is great for very specific purposes. Caches, keeping state, logging stuff. For many things it is misused and postgre with jsonb can do everything you need (faster, easier) without rude awakenings.
If you think the how is irrelevant you are completely missing the point of this exercise. Maybe to you only the result matters but for every other task and humanity the how matters.
Simply imagine next taking on a different Game like one version of the Anno series.
If developers did it by hand, you need 50 devs sitting there for probably a couple of months, figuring out the best, rules their sequence and putting them in. That is about $20 Million just to get a similar AI for the next game.
Compare that to download all available replays, requiring maybe 2-3 data scientist to get the data into shape, renting some compute in the google cloud and you get the same or a better result for probably half a million $.
Watch and learn from data alone is why modern machine learning is considered a revolution and novelty. Buying compute time in the cloud is in comparison (to devs and hand coding) dirt cheap and the results are often better.
Deepmind is not working on this problem for the benefit of gamers or the Starcraft community. Making the perfect bot is not the aim. Tackling the next hurdle, next hardest problem in machine learning is. On the way to become better at generalizing the learning algorithms.
If I was an employer in IT, I would only hire 6h day workers (full pay). No breaks but no more than 6h 5 days a week. I can do 6h concentrated work almost any day with an afternoon/evening of other things. 8 or 12h only works occasionally on average when I work 8h I add more than the 2 extra hours of time wasting, because less satisfied/concentrated/happy.