4 minutes read | 682 words by Ruben BerenguelSome links are affiliate links
Haven’t read much these days, but luckily I have not added much to the list either.
Currently my reading list stands at 99 books (2 read this year) and 10 articles (yay!). The book one is obviously the hardest to trim, because my goal of 50 read this year is tricky: it’s almost a book per week. Although I have already read 2, this week I haven’t finished any (maybe tomorrow, I have two with 50% read).
I have also started using Readwise (this link gives you 60 days to try it instead of 30, and may give me 30 more free to keep trying, if I don’t subscribe before that though, it’s worth it) to keep track (and be reminded of) annotations I take from books. I copy many of my book notes into Obsidian but not all of them, only either the actionable ones or the very enlightening ones. Readwise helps keep all others, and can sync with the plain-simple My Clippings.txt from a Kindle.
Impressive amount of work for an equally impressive demo. I disagree with one comment mid-way in the article: the pyarrow Python library is pretty decent, probably the work done in the Python script is better done in Pandas, which you can use to interact to Arrow later.
I have been considering moving from Mailchimp to Buttondown for more than a year. I try to streamline my processes as much as possible, and the preparation of the newsletter in MC takes 50%+ of the time the post+newsletter take. Unreasonable.
As mentioned in the article, there are several ways to think of data ROI but I think Mikkel makes a solid case for his, since it takes into account all the levels data covers (from deep down data engineering to up close with data driven product changes).
One of recommendations in this article is Optimize notes for future searchability. I have been taking notes for many years, and the way I optimize my notes for searching is by writing everything in English (except in very rare occasions). This makes sure there is only one way to find information.