James Carse has a theory[0] about this: “There are at least two kinds of games. One could be called finite, the other infinite. A finite game is played for the purpose of winning, an infinite game for the purpose of continuing the play.”
While I appreciate the “middle” metaphor, I think it’s unwise to generalize business (and real life situations, more broadly) as a chess game — life doesn’t often come with symmetric information and zero-sum stakes.
Annie Duke says it better than I can, in her book[0]:
> “Chess is not a game [in a game theory sense]. Chess is a well-defined form of computation. You may not be able to work out the answers, but in theory there must be a solution, a right procedure in any position […] If you lose at a game of chess, it must be because there were better moves that you didn’t make or didn’t see.”
> “The decisions we make in our lives—in business, saving and spending, health and lifestyle choices, raising our children, and relationships—easily fit von Neumann’s definition of ‘real games.’ They involve uncertainty, risk, and occasional deception […] Trouble follows when we treat life decisions as if they were chess decisions.”
I agree with you that life doesn't come with symmetric information, but to argue that "Chess is a well-defined form of computation" is a bit much. Go/Weiqi is also a computation problem given this argument. What precludes asymmetric info games like poker from being "computation" problems, if one takes a wide enough view (to include the unknowns as the modeled state)? Quantum computing inherently probabilistic.
Your second argument is about zero sum stakes, and I think this criticism applies to virtually all "toy" games we play.
> They involve uncertainty, risk, and occasional deception
As do decisions in chess, because the players aren't perfect computers.
> Go/Weiqi is also a computation problem given this argument.
I agree with the assessment that it is a computation problem.
As a go player for 25 years, I never thought that I would see a computer consistently beat a strong amateur in my lifetime (with many decades still theoretically left to live). Not only did I see it much sooner than I expected, but AI beats the best pros at an almost 100% win rate.
Within the Go community, there is consternation that a computer can make some moves that humans probably shouldn’t make due to the ability of the computer to follow up properly where humans cannot (yet).
This may change over time, but right now the computation part of the go world is much closer to expressing perfect play in a complete information game than humans are.
> What precludes asymmetric info games like poker from being "computation" problems, if one takes a wide enough view (to include the unknowns as the modeled state)?
Also as an avid poker player, I think many aspects of poker are rapidly leaning this direction, even though poker does not have complete information.
I’m not sure how much you know about the current poker scene, but GTO solvers have opened the poker world’s collective mind about what “good” play looks like, and the players are riding the tails of the computers in terms of strategic and tactical evolution.
In some formats, like heads up limit hold em, the game has been effectively solved.
Bringing it back to the original topic, I would love to see a GTO version of life. Even if it is hard to implement, it could provide a guide that informs decision making.
I personally don’t think I will see it in my lifetime. That said, like Go AI, I hope I’m wrong.
As someone else said in a comment, while any metaphor has its limits, I feel that there are many more analogies to make with chess.
As a mediocre chess player who has played too many subpar bullet games, I've begun to recognize patterns. For instance, sometimes my opponent has a good move that they are ignoring, but then I make a bad move that naturally highlights that good move. And then my opponent makes that good move. To me, it seems there should be some good analogies to make in business, where your decision spurs your competitor to make a great decision. I just can't think of any.
Or the idea that chess is about keeping your options as wide open as possible and limiting your opponents options (i.e., to restrict the king). That's one reason you might play for the center. It is certainly why the Queen is more valuable than all the other pieces... she has more squares she can move to. Typically a knight on the edge of the board is inferior to a knight in the center because the edge reduces its 8 maximum moves. IIRC, you can compare point values assigned to each piece with the number moves a piece can make average over all position in an empty chess board and see that the proportions match up. It is also why playing positionally matters. Your opponent could be up a piece but if one of them is trapped, it is almost like they are. That is an example of a un-usable advantage.
Or take simple tactics. Forks are when you have two threats on your opponent and they can't deal with both. It is a lose-lose situation for them. Or a pin is about restricting their movement. Sometimes the pin or fork is subtle, where the fork is between checkmate and capturing a piece.
There is a lot to explore here that goes far beyond "chess requires thinking deeply, chess requires anticipating your opponents moves, etc" that requires the pattern recognition that comes from playing many games.
In Dan Carlin's Hardcore History episode about the Nuclear Age, he makes a similar point about chess. The American leaders at that time didn't play chess, they played bridge as it simulated a more dynamic environment with a lot of missing information.
Indeed there exists a perfect chess game, where each side plays the optimal move. Any different move results in an equal or worse outcome/speed of outcome.
"Unwise generalization to business" is the essential contribution of this blog. I've had the same feeling about nearly every post that made its way here.
To split this hair a bit, I think “code quality” has two definitions:
1. the degree to which the code can be trusted to operate correctly and in a fault-tolerant way (i.e. “yeah that API endpoint will give you a 5xx about 2% of the time, sorry about that, just retry!”)
2. the degree to which the code optimally models the problem it’s solving, as well as how flexible it is as priors/needs change in the future and whether optimal languages/frameworks/patterns are used to solve the problem expressively.
The former has obvious customer implications — if your webapp craps out every ~20min of usage, or your API silently drops data when it can’t persist something to a data store, that’s bad, you will lose customers (and you deserve to!). Conversely, lacking in the latter could slow you down as you iterate, but you’re just as likely to not need to touch that code for a while if you’re off building new views/features/what-have-you.
I think the “don’t worry about code quality” folks are generally trying to beat it into technical founders/builders’ heads that the thing they’re building is ultimately being judged as a product, not as an engineering project... but that doesn’t mean that reliability and performance aren’t part of what may make your product valuable.
To expand on something you hinted at. I think it's a very important insight to realize that your code base doesn't have to be homogenous, and you can make different trade offs in different parts of the app.
If you have an accounting app for instance, if it crashes every once in a while users will accept that. If it calculates your taxes incorrectly leading to an IRS audit, that is unacceptable and an existential threat to your company.
In that scenario UI could be messy but your tax crunching code has to be the cleanest and best tested code you can write.
> why aren't most messaging apps peer to peer [...] it's literally the point of messages: sending from one person to another.
Messaging apps are more like postal services — "please deliver this message to $person" — you're describing driving across town to drop something in a mailbox directly. A peer-to-peer messaging system wouldn't have many benefits over an E2E-encrypted one (in a centralized E2E-encrypted service you already enjoy technical guarantees that the courier can't peek inside the metaphorical envelope), but would have several usability drawbacks that would drive away casual users, which the sibling comments mention.
Driving away casual users has its own problems: you might drive them away to insecure services ("ah fuck it, this thing doesn't work, I'll just DM them on Twitter"), and the lack of casual users will make your remaining users stand out in traffic analysis (e.g. state agency says "hmm, askxnakjsn is using SuperEncryptoP2PMessenger, better go make sure they aren't a dissident").
I don’t know much more than you on this, but I’ve seen this explained as such: inflation requires the injected money to actually be circulated in the economy in order to dilute the value of the currency. of the money distributed to companies and individuals during the pandemic, how much of it went to everybody’s “rainy day funds” and war chests? Most folks I know that are on unemployment right now have touched <20% of their funds, and Americans just hit a record savings rate[1] last month. Schwab has an article[2] that explains the monetary effects of this better than I.
