Topic: Engineering

Each post below is tagged with
  • Company/Division names
  • Topics
  • and
  • Narratives
  • as appropriate.
    Uber is Reorganizing its Engineering Team to be More Efficient and Coordinated (Oct 10, 2017)

    Uber apparently recently kicked of an internal project to reorganize its engineering teams in order to make them more efficient and coordinated and less duplicative or competitive in their work. It sounds like the prior structure and approach grew partly out of Uber’s aggressively competitive culture and partly out of a lack of proper structure, both of which need fixing if the company is to make the best use of its resources, a consistent theme in its strategy over the last few months. The historical culture around engineering sounds a lot like that which prevailed in the various Google fiefdoms which built hardware for a long time, with little cohesion or coordination between then and teams often working on similar projects without talking to each other. Fixing that should not only make the company more efficient but more effective, and it may also help to fix the diversity and other issues if the team is run as a single unit rather than a disconnected set of engineering clusters.

    via BuzzFeed

    Snap Beefs Up Copycat Defense Amid Concerns Over Facebook Mimics – Bloomberg (Feb 8, 2017)

    This is another one of those times where it feels like the Facebook copying Snapchat narrative might have been a little over-applied. It seems as though Snap has hired and/or acquired an engineer and his firm in Switzerland, whose expertise is making it harder for outsiders to reverse engineer code. The Facebook read here implies that Facebook is actually reverse engineering the code rather than simply building equivalent features from scratch. To the extent that this is about preventing copying, it’s far likelier to be a response to smaller outfits cloning Snapchat than Facebook, which has many engineers more than capable of building these features without reverse engineering code.

    via Bloomberg

    Most engineers are white — and so are the faces they use to train software – Recode (Jan 18, 2017)

    A lot of the coverage of the lack of diversity in the tech industry focuses on employment and the lack of opportunities and barriers to entry for minorities and women. In other words, the focus is on the negative impact on those who would like to work in the industry. But this article highlights one of what I’d argue are many practical reasons why this lack of diversity is also bad from a product perspective – less diverse teams produce products which are poorer at meeting the needs of a diverse base of users. In this case, the specific issue is face recognition software and its inability to effectively recognize darker faces, in part because it tends to be trained on data sets of largely white faces and tested by mostly white engineers.

    via Most engineers are white — and so are the faces they use to train software – Recode