themgt

Maybe they were poisoned, had malaria, were stabbed, and also suffocated and drowned, all at the same time?

Just now learning Grigori Rasputin died of malaria.

William Roper: "So, now you give the Devil the benefit of law!"

Sir Thomas More: "Yes! What would you do? Cut a great road through the law to get after the Devil?"

William Roper: "Yes, I’d cut down every law in England to do that!"

Sir Thomas More: "Oh? And when the last law was down, and the Devil turned ’round on you, where would you hide, Roper, the laws all being flat? This country is planted thick with laws, from coast to coast, Man’s laws, not God’s! And if you cut them down, and you’re just the man to do it, do you really think you could stand upright in the winds that would blow then? Yes, I’d give the Devil benefit of law, for my own safety’s sake!"

Claude-written code is quite easy to spot - because it has this particular style of overly verbose "walls of text" comments, that 1. repeat verbatim what the code just below does, 2. include "list of things" that quickly go stale, 3. talk about "how things used to be before we changed it here" (useless to anyone reading the code now), 4. "talk to reviewer" in comments. And many other comment sins.

"quite easy to spot" this style in what sense? To a human? To an LLM? To a deterministic code scanner you wrote by hand yourself, per Codeberg policy?

That screenshot is some Lynchian horror. "#engineering. New direction, team – we're moving the prototype to Flutter" and then the humans and agent bots engage in flirty emoji-filled chats with cutesy names "I nailed the physics, UI shell @Honeybot?"

I'm trying to imagine a world in which this makes sense as a way to organize software development work, but coming up short. It's on a blockchain or something though, so there ya go.

https://github.com/block/buzz/blob/main/docs/assets/screensh...

So, is there a reason that your link to the official playground is dramatically more underwhelming and lacking in features compared to the from-scratch-in-C Minikotlin compiler page? You claim that the submission is uninteresting work from a lone non-technical rando and then link to / implicitly endorse a "hello world" repo from the multi-billion dollar corporation that runs the whole thing?

"If you owe AWS a hundred thousand dollars, that's your problem. If you owe AWS three billion dollars, that's Amazon's problem."

For sure. You cannot have "only higher level thoughts" without doing lower level work.

Spend 3 days a week writing Ruby on Rails and 2 days hand rolling x86 assembly. Every web dev I know has been doing this since long before LLMs. Ensures they can keep having high level Rails thoughts.

Even with a large database servers (10s of CPU cores, 100s of gigabytes of RAM) bottlenecks arise pretty quickly.

Err, do they? For what percent of real world use cases?

The database can scale to handle more traffic by adding replicas. An extreme example of this is OpenAI's use of 50 replicas on a single Primary.

So an extreme example is OpenAI needing 50 replicas, but we're doing five blades ... err, we're doing 768 servers because the need arose "pretty quickly"?

When we needed to store a petabyte of data (one million gigabytes), we'd need many more shards

For who? The United States government? How many end-users are running 1PB Postgres database on DBaaS?

It's sort of insane though, you not only have dozens/hundreds of stochastic agents running on your machine, but you cannot even inspect the instructions those agents are working off of?

I've gone in to look at Claude subagent/workflows and sometimes been like "no this was a mistake to spin up" ... Codex users just get to token yolo the encrypted telephone operator instructions+shell from orchestrator to subagents?

Yet one is technical and the one you actually got a negative opinion about a programming language supposedly isn't?

Yes, on the one hand here's "Structure and Interpretation of Computer Programs" and on the other hand here's my blog "embedding-shape is a stinky slop beginner shit show"

And yet you got a negative opinion of me from the "embedding-shape is a stinky slop hack beginner shit show" post rather than SICP? I feel like I woke up in an alternative universe!

I’ve never been in a situation that says “We’ve not think of that, we need to get back to the drawing board”

And you're somehow able to post on HN from within the time crystal?

Hard-coded to use his relay server and then asking for donations for bandwidth?

https://github.com/schollz/croc/issues/931

OK. Anyhow ... if there's a cognitive task you are personally superior to Fable at, let us know.

To meta-unpack a little bit ... it is strange to me that Fable is far more capable of discussing these questions than apparently 99% of humans. Along with being more capable at quite a lot else than most humans.

What's strange to me about these comments is they're timeless. They could have been written in 2026 or 2016 or 1966.

Like, afaict, for many on HN going from ELIZA->Fable 5 just didn't cause any update to priors regarding this whole philosophical question. The argument against has remained unchanged. I don't see any point in arguing about it, I just find it very strange.

Zig is getting that Elm, etc vibe. Genius/visionary BFDL who's also personally incapable of leading the project towards healthy long-term viability.

Say what you will about Matz or José Valim, I don't think they'd ever write a "and don't let the door hit you on the way out" screed full of personal attacks ("stinky manager", "writing slop", "a total shit show") against a person who led a very prominent project and financially supported the language.

HubSpot has been building a different solution for our customers. On August 4, Contact Discovery launches — and for the first time, your team can find, verify, and add net-new contacts without ever leaving HubSpot.

To support that, we’re updating our Customer Terms of Service, Product Specific Terms, Privacy Policy, Sub-Processors Page and Data Processing Agreement, effective July 1, 2026. This post explains what’s changing and why.

The contacts you find through Contact Discovery are reliable because they’ve been checked for deliverability, accuracy, and whether that person is still at that company. You’re not buying a raw list and hoping for the best. Every contact that surfaces has been validated, and decision-makers are ranked first.

That quality is only possible because of a shared dataset. When you opt into enrichment, some of your business contact data helps keep that dataset current. Everyone who participates gets more accurate data back in return. You never pay for a contact already in your CRM, and there’s no separate contract.

These are the new leads. These are the HubSpot leads, data mined from your own HubSpot account. And to you they're gold, and you don't get them. Why? Because to give them to you is just throwing them away. They're for closers. I'd wish you all good luck, but you wouldn't know what to do with it if you got it.

What I have been doing in many places—the octopus thought experiment, stochastic parrots, the phrase “synthetic text-extruding machines”—it’s all about trying to make vivid to people who aren’t in the business of building language technology what these systems actually do

Meanwhile, O, a hyper-intelligent deep-sea octopus who is unable to visit or observe the two islands, discovers a way to tap into the underwater cable and listen in on A and B’s conversations. O knows nothing about English initially, but is very good at detecting statistical patterns. Over time, O learns to predict with great accuracy how B will respond to each of A’s utterances. O also observes that certain words tend to occur in similar contexts, and perhaps learns to generalize across lexical patterns by hypothesizing that they can be used somewhat interchangeably. Nonetheless, Ohas never observed these objects, and thus would not be able to pick out the referent of a word when presented with a set of (physical) alternatives.

This seems kind of obviously wrong at least in the context of coding agents. These models get trained on actual output of the previous version of the model doing its job, often "IRL" on a real computer/project. It's like O is in the conversation for years now and learning from his own interactions between A <-> O <-> B, where A is the human and B is the computer.

The idea O ontologically has never "observed" "these objects" or referents is philosophically strained. Have I observed the moon, or a finger pointing at the moon? Have I observed `sed` more than Fable?

Yeah I went looking: https://github.com/langchain-ai/openwiki/blob/main/src/agent...

Forgetting? I think you mean to say your advice was auto-compacted to keep our context small and deliver better results.

afaik there's somewhat painful economics. Not sure back-of-napkin but something like:

   • 150-500B: Sonnet
   • 0.9-2T: Opus
   • 3-5T/10T: Fable / Mythos

If it turns out a $10m/10x shared node can host even smarter models, then what?

This is exactly it - the ultimate skill now is to be Rick Rubin with an LLM. Not a comfortable transition as a coder.

"Well, in our country," said Alice, still panting a little, "you'd generally get to somewhere else—if you ran very fast for a long time, as we've been doing."

"A slow sort of country!" said the Queen. "Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!"

I will just say, if you are any good at programming and have experience using agents, you're in the top 0.1% of the world in adoption of a critical new technology.

It may seem hopeless as a programmer, but imo you'd be much better off reframing your situation re: the above sentence.

I just tested GLM 5.2 out via Z.ai in pi for a little one-off project that was already scoped. It actually did a relatively decent job starting out, and figured important things out from context.

But the reasoning traces became increasingly hilarious, with it getting confused and going in loops, doubting itself. I began to feel almost sad, it was like listening to the internal monologue of someone with anxiety disorder.

It made pretty good progress but wound up going in a lot of goofy loops and doing things a bit "off" from standards I'd hoped it would infer, and finally started going a bit nuts, "This is very confusing.", "OH WAIT", seemingly hallucinating a whole side-quest that didn't make sense and looking at making internal system changes to try to achieve its (now very confused) goal when I pulled the plug.

Without seeing the reasoning traces from Claude/GPT it's hard to really know, but it definitely didn't feel like the same quality of reasoning, even if dogged persistence does wind up actually working eventually.

It's not like the job market was that much better before AI infested every single corner of the market, but it supercharged all of the worst aspects of everything. I've seen people supposedly smarter than I advocate for just giving in, conceding to AI coding as it's the future. But doing so means tossing out my friends who make art or the people who work their asses off to properly test and review code or the writers pouring all of their energy into even mundane dialogue. It means throwing out my dignity as a software engineer, as someone that truly gives a shit about security and code.

Don't let yourself get attached to any tech stack you are not willing to walk out on in 30 seconds flat if you feel the heat around the corner. That's the discipline.

instead of people’s vibe checks and pelican SVGs.

Right, what happened is everyone went to Fable and asked it to make the very best bicycle pelican SVG, no mistakes. And Fable's bicycle pelican SVGs were such timeless masterpieces, we all instantly got AI psychosis. Happily, you were immune to this.

This was never the question. The question was, will the export controls slow them down in the short/medium term to the point where it will give US companies an advantage?

I mean, I remember listening to the Biden people back in 2022 talking how they were going to cripple China's semis and therefore AI industry and keep them 5+ years behind the curve as Team America accelerates ahead. That was the pitch.

You've now got Huawei Ascend 950, GLM-5.2 at Opus 4.8 levels, China dominating OSS models, and Z.ai saying they'll have a Fable-level model by EOY. I would say the export controls have utterly, utterly failed.

https://www.csis.org/analysis/understanding-biden-administra...

That’s not what your quotes said. They said bigger models = plateau in intelligence, nothing about more data or increased hallucinations ... I’m pretty sure #1 is well known

Well known in a multiverse branch where Fable was a dud?

Great, got it. I'll update my running "how computing works" chart with this new information:

  | implementation = reality | magic  |
  |-----------------------------------|
  | 999,999,999,971 (+1)     | 0      |