A former Uber engineer's disaster story

> So my advice. Everything in Computer Science is a trade off. There is no universally superior language. Whatever you do, understand what the tradeoff are why you are making them. Don’t let it descend into a political war between opinionated factions.

I really like this point.

One company I worked for a few years ago, I joined right as a just such a ground-up rewrite of their core system was coming into place. Everyone in orientation was telling me "You'll be spending most of your working life dealing with " but they were actually training me on the existing system. About a month out of orientation there is a company wide. They canceled because it wasn't meeting it's technical specs.

It was also, coincidentally, the company where I most respected the key technical decision-makers, because they had the will to discontinue a product that a few customers already were using, because it wasn't meeting its criteria.

Does it blow your mind that Google Maps is ~190MB?

It can be quality code written by good engineers, but there are issues you won't see until you deal with big numbers. The problem here is that Swift seemed to be a cool language that it might work for a "Hello world" app. You won't notice any problem until the thing grows up to a certain point.

For example, I work in embedded and I am proposed with a new "X brand" Chinese Modem to integrate in our devices. I don't recommend it but since it costs less I'm pushed to evaluate it. I am handed 3 samples and they all work fine, so management convinced themselves that Brand X from China is the way to go.

Once in production the modems started to fail at a 10% rate (10 devices over 100 won't work). And that is a problem you only see only when manufacturing a certain quantity of devices.

Now there are delays, an ongoing battle with the manufacturer of modems and a unhappy customer (that's why I didn't recommended it).

Great thread. Thanks for sharing!

It's interesting to me that the author feels that things were great with Uber in 2016 pre-Trump and that Trump's election was the catalyst for the negative sentiment. Susan Fowler's famous post was early 2017, and maybe _posting_ it was catalyzed by the issues surrounding Trump, but clearly the serious cultural problems she described at Uber had been going on for some time before that.

I'm trying to figure out what to make about a lot of these mis-steps. On the one hand, many of them seem preventable: you could imagine identifying ahead of time that load time and binary size might be risks for the new app and scale-testing these very early in the process to de-risk it. You could imagine testing the new app long enough (and widely enough) to discover the location issues (drivers going to the wrong blocks, etc.). You could imagine foreseeing users being upset about suddenly needing their location data when they're not using the app. Obviously hindsight is 20/20, but is there also a pattern (that we see all the time, especially in Silicon Valley it seems) of not really thinking through the consequences of a lot of decisions, especially where things like user privacy are concerned?