tl;dr: Performance review feedback should be specific. If it's too generic e.g. "you're overly cautious" or speculative e.g. "you could have done this", you should ask for examples. Gergely outlines eight biases he's experienced, such as recency, strictness and leniency.
tl;dr: There are an abundance of tools to create systems that "shepherd code from its earliest juvenile days in version control through to its adult stage in production." These systems are not cohesive but fragmented, pieced together. The system is an afterthought. Stephan outlines five adjectives describing the next generation of the developer experience.
tl;dr: Will's tips on managing staff-plus engineers include: (1) sponsor and support more than direct.(2) Help redefine what success. A staff engineer’s "flywheel of feedback" is less immediate and that should be managed accordingly. (3) Give frequent feedback and explain why.
tl;dr: "It does not have many features. It is riddled with bugs and edge cases that it can’t handle. But that is not important. It works for my problem. If I don’t like something, I can fix it. If bug doesn’t bother me, I’ll let it be." Erik outlines the philosophy behind his SSG.
tl;dr: Adopting Typescript at scale was a net positive for the Bloomberg team. Principles core to the project were (1) scalability, (2) ecosystem coherence, so packages work together, (3) standards alignment, sticking to standards like ECMAScript. This article outlines some of the "surprising corners" turned.
tl;dr: "We’re committing to further strengthen a community that has greatly benefited us and our customers." As well as the community, AWS investments include "developer tools, infrastructure components, interoperability, and verification.”
tl;dr: "TensorFlow users on Intel Macs or Macs powered by Apple’s new M1 chip can now take advantage of accelerated training using Apple’s Mac-optimized version of TensorFlow 2.4 and the new ML Compute framework."