Because Google is the decider of what constitutes "slow"? You have a single organization deciding what the threshold is between slow and fast. And, they also have a Google-approved solution (amp) that I'm sure they will tie into the recommended actions for "slow" pages.
I'm not saying it's a walled garden (that's a more extreme situation on the continuum between open and closed), I was just using the phrase to illustrate my point that the end-user experience isn't the only factor to consider.
Walled gardens and proprietary software can allow for fantastic user experiences in a way that open platforms often cannot match. However, I feel focusing on the user experience misses the main point - the web is an open platform, and this is an example of Google exerting an authority that many may not feel comfortable with.
"A history". As I said, you are interpreting that word differently than they are. I think it's valid to interpret "a history" to mean "something that happens with some amount of frequency". I also suppose it's valid to interpret "a history" as "something that's every happened".
At the end, you write "don't and have never never endangered", which is something only you are saying.
The person you are replying to didn't say it's impossible for a cyclist to kill a pedestrian, just that it doesn't happen very often. They cited a statistic, you found an anecdote to counter. The disconnect seems to be around the word history. You're taking it to mean "something that's ever occurred", where as the person above is taken it to mean "something that is a common occurrence".
What's the benefit of targeting only people who have been part of a high profile layoffs? Seems like a smaller pool on both sides-less people to recruit, and less recruiters who specifically are interested in these types of candidates.
If it's as a proxy to quality of candidate, isn't there a better way to measure that?
Sure, its possible that they place "greater emphasis on academic education" etc., but then you have to ask yourself what is the reason behind this.
As an Asian American who has had good academic success, my best guess is its socioeconomic. Asians who came to the US in the 70s - 80s often were highly educated, upper middle class, and they had resources to raise their kids towards academic success. They certainly faced some struggles, but were not socially disadvantaged in the way that other minority groups in the US have been.
You may not have meant it this way, but your post reads like a racist dog whistle.
Employees "would be paid a week of severance" - I haven't gone through something like this, but that seems low. I know when the money runs out it runs out, but I hope employees weren't totally blindsided...
You don't understand why it's informative to hear a viewpoint on a topic from someone who has had a different experience than you? Why are you on this site?
Funnily enough, I am one of those people-my partner and I have one car between us (in LA), and I rely pretty heavily on Uber pool (or the Lyft equivalent) to get around on a day to day basis.
However, it feels unsustainable. I can't imagine the fares remaining this low, and because of people like me, transit ridership is declining. I don't think these rideshare companies can sustain such low prices indefinitely, and my guess is it's delaying real improvements to transit infrastructure.
You say "even with higher pricing", but are also saying that higher pricing (due to taxes) would ruin the services?
Uber and Lyft fares are unsustainably low right now, and at their current prices, they depress public transit interest and ridership. But what happens in 5 years when these ride sharing companies need to turn a profit? Self driving cars is potentially a solution, I suppose, but will it be ready at that scale by then?
I think it's simply a byproduct of silicon valley's fetishization of the word "failure". Anything that isn't a runaway success is re-contextualized as a "failure" so that it can function as blog title short hand for "here's what I learned from my experience that didn't go 100% as expected".
I bet there are far more people who didn't leave similarly-positioned-but-unsuccessful startups and regret it... maybe spurred on by the survivorship bias (or non-survivorship bias, in this case) of those who left a successful startup.