The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 26 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Hastings: Dave Chappelle is not anti-trans
“Which I don't believe that Dave is anti-trans, but he definitely takes on some of the issues”
Karp: Anyone paying for streaming or Starbucks can afford healthy food
“It's a myth that only people with money can afford healthy food and the reason it's a myth is because we've looked at the data, and it's a choice. So what I mean by that is anyone who has a smartphone, right, and you have to separate people who are below the p…”
Diller: Tech giants like Netflix and Apple have ended Hollywood's hegemony
“Those tech companies essentially have now taken over the old hegemony of quote, Hollywood, and now Netflix and Apple and Amazon.”
Reed Hastings Details Netflix's 'Keeper Test' Framework for Talent Management
“So the keeper test is a Netflix shorthand for asking yourself if one of your employees were quitting, how hard would you work to keep them to stay? Would you try to change their mind? And if you wouldn't, then you should proactively give them a generous severa…”
Hastings: Entertaining customers does not equal endorsing objectionable behavior
“Entertainment is not always going to be stuff that you love or that you emulate or is admirable. There's lots of stuff in entertainment that's not admirable and if you don't want to be in the entertainment business, that's fine, but if you do, this is a core p…”
Hastings argues performance improvement plans are useless compared to generous severance
“And then we generally don't do performance improvement plans, which are sort of a way to document the employee's poor performance so that you can win a suit. Instead, why not give, just give them a check? And you know, there's so few people who get put on a PI…”
Hastings: Loyalty in organizations acts as a stabilizer, not lifetime commitment
“We came to think of loyalty as a stabilizer. So loyalty gives you know, if you have a bad day, you don't get instantly fired, or if your boss has a bad day, you don't quit instantly. You sort of think things through solidly over, you know, a couple months. But…”
Hastings admits Netflix relied on creative instinct to greenlight House of Cards
“You know, there's some data, but I would say that's raw. It's instinct that the thing you've got a partial script, you've got some casting, and you have to guess how good is that show going to be. So to figure out what it's going to comp against in terms of yo…”
Hastings: Netflix culture was not cutthroat despite external perception
“So, in Netflix there was the meritocracy and outsiders thought it was cutthroat, thought it was Hunger Games. But inside it really wasn't. People looked out for each other, helped each other quite a lot, but in the words we used to describe it we're not warm a…”
Hastings: Netflix eliminated expense policies because enforcement costs exceed waste
“And we got rid of all of that, and we just had to travel as you would on your own nickel. And you know, I'm sure there's, you know, occasionally some expense that gets done that shouldn't be, but compared to the cost of enforcement, it's tiny.”
Eyal: 'The Social Dilemma' is sloppy to the point of negligence
“My take on it is that it's equivalent of if Steven Spielberg called Jaws a documentary.
It's you really have to see it.
It's so, it's sloppy to the point of negligence.
It's so silly.”
Hastings: Judgment can be taught like music, not innate like language
“I think so. I mean, I, you know, to varying degrees, I mean, it's kind of like music or something, which is everybody can learn some music, probably only some people become fantastic at it. But you need some teaching in it for sure. It's not just like, it's no…”
Hastings: Entertainment workers will lose jobs to AI-using producers, not AI
“You're not gonna lose your job to AI, you're gonna lose your job to a producer who uses AI. And, you know, it's a tool for people to use and hopefully everybody will use it and raise the level of performance just as they did with, say, digital filmmaking.”
Hastings: Netflix focused on inclusion over DEI for commercial interest
“But I would say in general for us, we always focused on inclusion. We never called it DEI. For us is we want everyone who's a Netflix employee to be able to contribute at their highest ability. Cause that's in our commercial interest.”
Hastings: Ted Sarandos and Greg Peters Proved Me Wrong on Live Sports
“Well on Christmas we had two NFL games, so I would say it is part of that. It's one of the things that Greg and Ted have done because I was always very skeptical not of course of the viewing, but that there could be a good long-term proposition there, and they…”
McLean: Enron's hyped broadband division was conceptually Netflix before its time
“Enron's really hyped business was this business called Enron Broadband, which it's an interesting aside. It really was Netflix before its time.”
Hastings: Netflix culture deck repelled security seekers and attracted risk-tolerant talent
“The people who fundamentally wanted job security overgrowth were repelled. And the people who wanted growth and willing to trade off job security loved it. And so then we, you know, selected a very creative type of person who, again, was into performance and t…”
Hastings: User Ratings Inform Netflix Content Decisions More Than Completion Rates
“The thing that's helpful is at the end of a Netflix show, you give a double thumbs up, single thumbs, or thumbs down. We know you finished it, but maybe you thought it sucked. And so we really want to know what you thought of it. So that's the, probably the pi…”
Hastings brings Netflix keeper test and meritocracy to Powder Mountain
“And in powder we started with big hearted champions who pick up the trash. And so big hearted, of course, loving and generous as the lead word in our kind of employee motivation. Champions like, no, we really do care about performance. That's that meritocracy …”
Netflix ignores secondary commercial windfalls to focus strictly on entertainment value
“It is certainly true that when we set a show in a context, and then the show works, as Drive to Survive did then it popularizes that thing, but if we, it doesn't, like, bother us that they profit from it any more than If we did a show that was set in farming a…”
Hastings: Company-first loyalty only works if leaders visibly sacrifice for the organization
“What he's getting at there is not a personal loyalty like political factions where you look after, you know, your boss or something like that but you care about the organization, and I do believe he's right that that creates a very powerful force, and it only …”
Wolfe: Viewing data algorithms cannot crack the recipe for hit shows
“They've put a lot of money into this, but it hasn't yielded the recipe maker for, like, the next perfect show, and oftentimes the thing that you want to see is almost something that's orthogonal from what you've been watching.”
Hastings: Squid Game's Global Hit Status Was a Complete Surprise to Netflix
“So we knew Squid Game would be big in Korea, or we highly suspected it would be. But the fact that it took off globally you know, was a surprise to us, and we'd been doing it for 20 years.”
Hastings: Netflix Accounts for Only 5% to 10% of TV Viewing
“And so Netflix earns, you know, depending, depending on the country, like five to 10% of television viewing.”
Domingos: Netflix and IBM Watson Already Use Basic Forms of Meta-Learning
“And this type of meta learning in certain basic forms is actually already widely used today. Like for example, Netflix uses this type of thing to recommend movies. It doesn't just use one learning algorithm. It uses a whole bunch of them. And then another algo…”