From the TL;DR in Tech archive, originally sent on Substack. Some links may have died since.

tl;dr in tech by Joe Karlsson - Issue #20

tl;dr: The ML model takes into account spatial and temporal features, such as the origin, destination and time of the request, as well information about real-time traffic and the nature of the request, such as whether it is a delivery dropoff or rideshare pickup.”

tl;dr: “If you agree with the notion that you need to be able to tell the difference between the absence of a value and a value itself, then this has some impacts on the code you write. If you want to keep ‘em separated (so they can come out and play), then it gets you looking at your API designs in certain ways.” The author shares her reactions to some of the ways a value can be returned.

tl;dr: Markdown in all its flavors, interpretations, and forks won’t go away. However, it’s important to look at emerging content formats that try to encompass modern needs. In this article, Knut shares his advice against Markdown by looking back on why it was introduced in the first place, and by going through some of the major developments of content on the web.

tl;dr: Start experimenting with ten mental models you can use to get unstuck, look at difficult problems from new angles, verify your assumptions, and understand systems more deeply.

tl;dr: A growing body of evidence is showing that employees who feel comfortable and psychologically safe are more engaged and creative team members.

tl;dr:

1) Imagine you’re telling your story at a bar. How would that change the way you related information?

2) Use the art of persuasion to tell stories that change minds and rally teams - “stick to a very short, simple message that you repeat in different ways again and again.”

3) The best leaders know how to tell stories about failure - “being vulnerable doesn’t weaken your authority. It strengthens everyone else around you.” And more.

tl;dr: “This blog post is for top-of-mind technologies that are improving my life at the moment.” Jowanza provides insight into how he’s leveraging:

1) Docker.

2) Httpie, a CLI tool for HTTP calls.

3) OpenAPI 3, a specification for describing RESTFUL APIs.

4) TypeScript.

tl;dr: “I hope this post will help platform engineers develop their cloud-native, self-serve streaming data platforms and scale use cases across many business functions (not necessarily from our success but maybe more from our failures).”