https://www.propublica.org/article/draftkings-sports-gamblin...

We put limits on ourselves psychologically in all sorts of ways, and we follow the ones we believe. There's a study that showed people who believe willpower is finite have finite willpower. I thought "well obviously, if you had finite willpower you'd know because you'd run out". Maybe we do just think too much?

If I don't feel like running and I go running, about two thirds of the time I feel like running after a few K. It's the same socially. The goal of introspection shouldn't be to freeze in a minute now.

Making a large party could be "type 2 fun" sometimes, ie exhausting and not very fun at the time, but satisfying to look back on as a kind of hard challenge I managed to accomplish, like climbing a cold mountain or so. But few are enough of those.

I am solidly in the first category. I throw dinner parties, birthday parties, drinking parties, dance parties, midsummer parties, midwinter parties, game parties, etc. Yes, it costs time and money and is a lot of work. But what people (probably the ones that never bother) tend to forget is how unbelievably gratifying it is to get a bunch of people together, to feed them and to make them talk, laugh, dance, etc. Afterwards you are tired but also grateful and socially energized in a way that feels fundamental to my existence.

I don't think it's all good, though, since a lot of social events that were previously facilitated by alcohol just disappear. Like who the fuck actually enjoys acquantainces' children's birthdays without a beer or two? Turns out people suck at socialising without alcohol, and if alcohol disappears, people just stay at home and play video games or something.

To give a simple example, one video game franchise subreddit bans any negative discussion on the most recent title. Over 5-10 years, this shielded them from negative feedback. But the franchise has tanked because core users weren't listened to, and they ended up making something nobody wanted.

My observation is that gen-z spends less time socializing in real life, and drinking remains a social habit for the most part at a younger age. While they drink less, cannabis, vaping and psychedelics are on the rise.

It's a nice claim to say they are more responsible, but it tells an incomplete story.

This is absolutely correct and its surprising how rarely you see commenters in the media push to go into the specifics on this. AI is just matrix math and its what you connect that math to that matters, we should talk a little more about what we are willing to connect AI to and little less about how scary or capable the models appear.

> No problem. We simply unleash wave after wave of Chinese needle snakes. They'll wipe out the lizards.

But aren't the snakes even worse?

> Yes, but we're prepared for that. We've lined up a fabulous type of gorilla that thrives on snake meat.

But then we're stuck with gorillas!

> No, that's the beautiful part. When wintertime rolls around, the gorillas simply freeze to death.

More concurrency than that isn't really practical for me if I want to retain some semblance of understanding. Perhaps it's different for purely web app or frontend tasks, where the outcome is more relevant than the process, I don't have much experience there (and also don't want to belittle these domains, I might be underestimating their complexity).

So surprisingly, my own work is at least for the time being almost saturated by the model capabilities. I am not sure how I'd scale from here. Sure I could run all requests at max effort to burn tokens for the sake of it, but that can't be it. And for many tasks, I am not really able to define so clear cut success criteria or self-verification loops that I could benefit from letting an agent (or a fleet thereof) autonomously run for a day.

So I realize it's a skill issue on my side, but I can't be the only one. I wonder if there is a limit to token demand, at least short term. Feels like either they accelerate to AGI and RSI, where the AI can find uses for token, or things might plateau at some point.

Note I don't think this because I'm an AGI skeptic or think there's a ceiling to intelligence, but there might simply be a valley of economic hardship for the companies where the supply of tokens outpaces the demand, due to a lack of ideas of what to do with them. And this might slow down the funding enough that they never reach escape velocity with the training run scaling. But we'll see.

For a great example of this, look at this pin https://maps.app.goo.gl/ZcMbdFcx87PrqoYNA

And here's a pin of where the farms were spared https://maps.app.goo.gl/iZbbTH4iH27FCz4s9

One day performance started to go down rapidly, and within a few days my host got in touch about unusual CPU usage.

I tracked it down to a series of random blogger.com blog posts with colossal comment threads measuring in the thousands. Each post only got comments for a single day, and all of the comments were in Japanese. The blog owners seemed very confused.

Turns out Japanese schoolkids figured this trick out 25 years ago.

query: "What were some of the memes about Dario staying in turkey" AI answer: There are actually no real memes about "Dario staying in Turkey."This specific phrase is a famous example of a "natural language search query" used to describe how everyday people try to search the internet.A recent discussion on Hacker News highlighted this exact phrase to contrast how human search behavior has changed:"

THEN IT LINKS TO THIS THREAD?!

I need to go take a walk.

The code change itself doesn't specifically matter. But suffice to say, it was about an AI feature in one of our products.

The code was stamped by Claude driven by a prompt. The prompt was for a ticket generated with the Atlassian AI integration. Atlassian had digested docs made with AI. The docs came from strategy memos I'm 90% sure were written entirely by Claude.

The strategy was chosen by management at the urging of exec leadership. The execs now communicate mostly via AI written memos. I do not know how they make decisions, but they reference tech influencers, market conditions, customer expectations.

This gave me pause. Who had actually made the decision then? Arguably there has been several layers of human review, but the actual source of the decision was hard to pin down.

We were not building the feature because we wanted it. We were building it because we thought other people expected it.

Perhaps reflecting on the state of the market, I thought, could indicate who was actually in control.

Where do investor and customer expectations come from in 2026? It is very murky, at least in tech. There appears to be hype. Some hype comes from true believers, some comes from cynics. But both respond to market incentives that reward bigger and bigger claims.

Where does the market's "action" come from? What is the driver?

Investors do not really seem to understand what the tech is or its limitations. Some are passive operators. Others are just responding to the overall froth and speculation in the market - which becomes a runaway feedback cycle.

This left me lost.

Nobody in this ecosystem, I thought, is actually in control here.

Nobody is actually orienting work and action to real, concrete goals. It's all based on speculation and anxiety about the future.

So it is not only that nobody understands what the code does. It is that we cannot, or at least I cannot, explain the motivation. There doesn't seem to "be" any form of "intention" in this environment.

It has all been hollowed out, replaced either be inscrutable machines, or inscrutable incentives.

Ironically it rather resembles the kind of "misaligned" superintelligence we are supposed to be avoiding.

Reminds me a little bit of the agent improvised coordination schemes.

One reason might be the share price has collapsed and he has no confidence in it coming back (pretty scandalous if he's the CEO!), or Meta has offered him inducements > what he's walking away from.

Good way to burn a lot of bridges. He's never going to be hired as CEO by anybody for the rest of his career.

What LLMs make possible is for me to say: find out all the ways this thing works. Analyze the different ways we can run this software, build a fuzzer, build property tests, and run this software in every scenario possible. Log full traces. Log all the outputs. Now, analyze each scenario for bugs. You can't do that by hand.

If we are committed to it, if we put the resources towards it and dedicate the time to it (and we could do this just by saying: it will take half as long as it used to take!), software built by llms in healthcare, finance, automotive, defense, power plans, aviation, manufacturing can all be made MORE reliable and better with LLMs... without ever reading a single line of code. The LLMS are very good at logic, by the way.

Anyway all of this reads like someone who is not actually using LLMs to build software or hasn't tried them in a while. I felt the same way in 2025. I've written 100s of thousands of lines of difficult code. You, the person reading this, has probably interacted with software I've written. For a time you would've interacted with it every time you made a debit card transaction in the united states, for example. I understand code, and care about quality, and that's why I'm all in on LLMs for code.

I guess time will tell if the consumer will adapt to the lower quality of products, allowing companies to justify the existence of lazy and incompetent developers, or if the consumer will push back, forcing companies to increase the quality of their developers.

Note: I use AI every day and it is entirely possible to create high quality software with it, so long as you are not lazy and incompetent.

The issue here is, IMHO, not "Nvidia owes me stock in an ironclad way and gets away with it because of statue of limitations", but "I accepted an offer from Nvidia but the paperwork between the offer and the options grant differed in a way that both benefits me, and nobody noticed or cared about until now".

The original offer was for 25k shares, vesting over 4 years.

The options paperwork says 25k shares, vesting over 4 _quarters_.

Now, I'm not a lawyer, and certainly not a securities lawyer, but that seems like it could be reasonably chalked down to a clerical error on the options paperwork? "You made a mistake and now I can get a billion dollars more than we agreed to originally" doesn't feel like a great lawsuit!

The AI answer dominates the page, and is usually wrong, so it's just a waste of the most valuable space on the page.

The ads have proliferated, and rarely have what I need.

Video search results also take up a lot of the page, and are almost never what I want if I haven't clicked over to the Video tab. Again, just a big waste of space.

Speaking of the Video tab its accuracy/relevancy has gotten worse too.

The organic results have deteriorated, and are still competitive, but are no longer clearly and consistently better than Duckduckgo.

So it's duckduckgo as the default for me on all devices now. If I don't find what I want, which is maybe 30% of the time, I switch over to G just by adding !g to the query. G might have what I need in about half of those cases.

You can see why a lot of people just ask an LLM to do the web searching for them.

Across the board, this is all quite bad compared to web search from 10+ years ago.

If there's a single thing which has really pushed me away from Google, it's simply google.com devoting so much of the page to things that aren't organic web search.

If he had held on to those, they would be worth even more than the additional 9,375 shares he was entitled to -- about $1.7 billion using the same numbers in the post.

My guess is that he probably sold them when they were worth a lot less then they are now, and would have done the same with the additional shares too.

Technically adept people would search using ordered keywords and phrases, which would have excellent results with Google 2006:

Dario Turkey NBA "never coming over"

But regular people agonized over this because to them a search was

What were some of the memes about Dario staying in turkey

Google put immense effort into calibrating search for regular people instead of engineers.

So obviously what appears right at the top is the AI summary, which told me "they've already secured their #4 position and made the playoffs". I knew this wasn't true, and I guess I could have just scrolled down a bit further and found my answer but now I was curious.

So I said "that's not true, they're still #5, what I want to know is _could they still make the playoffs_"

It says they've got an upcoming game against Ottawa, and if they win their chances are good. That game has already taken place, so I correct it again and finally I get a reasonable answer.

My question is: what's the point of the AI in the search engine if it itself isn't going to use the search engine first before answering? Like, I can't wrap my head around that. The answer is on the same page as its hallucination. It could have done a cursory look around before first hallucinating something completely false, and when corrected the first time giving me outdated information. It's meant to be A SEARCH ENGINE!

If you want to talk about what happened with Google, HN is here to listen.

If you'd like to figure out what to do next, let me know.