Management, Startups, Marketing, Productivity

• Summary of Deep Work: Rules for Focused Success in a Distracted World by Cal Newport. Of course it worth to read the book but for busy people with long “have to read” lists, summaries like that are priceless.
• Estimates are hard and never precise. This research
  (russian version) based on more than 12k projects and represents some correlations between scale of projects and probability estimate time for the project right. I few impressive outcomes: in most cases we estimate right, but when we are mistaken, the scale of mistake could be drastic. Uncertainty tends some projects to be indefinite (or at least have no sense to be finished). From my side I can add up to this a few my observations: we often overestimate small tasks but underestimate big ones. So, my recommendation to subdivide tasks as much as it possible until it will be small enough (6-12 hours) and then do corrections depending on the risks you include in it.
• One more great article about pitfalls in estimates from Karl Wiegers, author of the best books about business analysis and requirements.

Programming, technologies, computer science

• Long-read about one on the oldest open source projects (was started even before “open source” term was invented). Indeed, TeX and LaTeX developed by Donald Knuth and Leslie Lamport have a significant impact on science for the last 50 years. Hard to underestimate how much knowledge and how many ideas became available to scientists through the world and how many even more great ideas was built over them.
• Things you’re probably not using in Python 3 – but should