Hi all,
Like I did last month, here are some quick notes about the books for which I’ve yet to post a full review.
A Pattern Language by Christopher W. Alexander, et al (March 2019)
This one thousand plus page brick doghouse of a book is probably enough reason to stop doing reading reviews altogether. Alexander and his team describe the principles of design in public and private spaces, tying it all together by identifying the shared or larger patterns relevant to each detail. The idea of south-facing design making the most use of natural sunlight has made a big change to how I’ve looked at spaces. I also thought the comment that people learn best when they help someone who knows what is going on was a brilliant insight into the learning process.
It Doesn't Have to Be Crazy at Work by Jason Fried and David Heinemeier Hansson (April 2019)
Longtime readers may recognize these authors from prior comments about Rework or Remote . This latest book is more tactical than their past works, detailing specific strategies for achieving their ideal of a calm company – one that rejects the frenzied attributes most take for granted in the modern workplace. Their note that remaining profitable is critical to achieving this goal made a big impact on me. A company in the red cannot do anything meaningful to calm their employees because in the back of their minds is always the lingering possibility of imminent bust.
Maniac Magee by Jerry Spinelli (April 2019)
Yes, I still recommend it. I may have noted this in the past but I find it interesting how so many books are about orphans (including some of my other favorites such as Eureka Street and the Harry Potter series).
It's Better Than It Looks by Gregg Easterbrook (March 2019)
I have a mixed history with Easterbrook’s work that has gone largely undocumented (most of the reading happened pre-TOA). He is a broadly optimistic figure whose insights grow from a willingness to question any widely accepted opinion. His note that agricultural advancements mean our planet can feed between 10 and 20 billion is a good example of what you’ll find here. For me, his comment that models can only ‘predict’ the conclusions built into their programming was one of my favorite ideas of the year.
