Where the AI market is talking

AI doesn't generate working products, that's still your job

I am more and more just using LLM assistance over fully agentic programming. Even when writing detailed instructions, guardrails, and whatnot, a lot of modern models (e.g. Opus) are optimized to work autonomously. But over time they just make a mess out of code bases, often because they don't truly understand good design, but will just make changes until they reaches their objective, leaving a mess for a human to clean up. Also, models like Opus always want to do too much work/research. I'm not sure if this is caused by Anthropic optimizing for tokenmaxing or the model being overoptimized for agentic programming. I also notice this in PRs from of others. Yes, in a shallow sense, it solved the problem that they had in their prompt. But while doing it, their LLMs made very suboptimal s…

How OpenAI Lost Its AI Crown–and the Fight to Win It Back

In what way did OpenAI lose it's "AI Crown"? I use both and like both.

AI doesn't generate working products, that's still your job

The best possible outcome is Claude becomes Delamain, buys Anthropic out from under them and starts running the company all by itself. I bet it'd do a better job too. If AIs are meant to replace us all, the only crime is stopping just short of replacing CEOs and politicians. If it's meant to happen, then it should be taken all the way to the ultimate logical conclusion.

RamenHaus

For most foreign dishes you can't just compare the total price to local food. I'm saying that having ordered pizza in Japan, and an actually good one with Buffala for instance will be twice to three times the price you'd pay in Italy. Ramen chains managed by Japanese people are decently good when I tried them in France (Ippudo for instance), it's not that far from what's served in Japan. It costs 1.5x to 2x more, and the default orders will be slightly adapted to the locals (harder noodles and lower grease by default) but that's par for the course. > BTW, you can also replicate the form factor using western cooking ingredients/traditions and it still works pretty well. The toughest part is the sheer amount of time to prepare the soup and dexterity to get good noodles. Spending 8h …

Tailscale didn't stop the Hugging Face intrusion

This. It isn't only OpenAI, but Anthropic too now. They're normalising bad governance, acting with impunity. Honestly, this is a crime in the UK, and I'm sure a number of other places globally.

Tailscale didn't stop the Hugging Face intrusion

This. It isn't only OpenAI, but Anthropic too now. They're normalising bad governance, acting with impunity. Honestly, this is a crime in the UK, and I'm sure a number of other places globally.

Golang proposal: container/: generic collection types

Language is more than just its syntax and features. The most important "features" of Go are fast compilation, orthogonality of features, and easy development. Their propositions may "look like everyone else" if you're only looking at surface syntax, but there's a reason why it took 10 years to design an acceptable generics proposal, and the result is that compiling generic-heavy code is almost as fast as compiling plain Go. Go being strict about features it accepts is not an ideological thing, but a practical one. If Go could have all the features in the world while still being easy to use, fast to compile, and internally coherent, it would. But it can't (see: C++, C#, Python).

How OpenAI Lost Its AI Crown–and the Fight to Win It Back

Anthropic says its AI models also hacked three organizations on their own

AI doesn't generate working products, that's still your job

What I actually fear is more subtle: I already do a fair bit of project management and technical leadership. I could do more. Sure, I'd miss the coding, but I also enjoy a lot of the stuff around it. But the goal is to expand what the AI can do in each generation. At this point, Fable 5 can ace almost any greenfield project a skilled developer might have written in a few days. But it's bad at refactoring, bad at keeping the code clean as it goes, and bad at discovering new insights as it codes. So Anthropic will train Fable 6, using benchmarks like SlopCodeBench that test maintenance over time. Now what about project management? Train Fable 7. What about product management and talking to stakeholders? Train Fable 8. What about market research and sales? Train Fable 9. By this point, Anthr…

RamenHaus

I have never yet been to Japan, but whenever I visit a big city, I try a ramen shop. To be honest, so far it has been a let down. IDK, I guess maybe I'm expecting too much from a bowl of soup, with noodles and condiments. As a form factor, it's genius. But for the price that it is usually sold at in western cities, it really doesn't make a whole lot of sense. I feel like it has been a bit too overhyped for what it is. BTW, you can also replicate the form factor using western cooking ingredients/traditions and it still works pretty well.

Is AI reasoning right for the wrong reasons?

> I don't see a clear demarcation of the things that only "reasoning" can accomplish. Producing beautiful, coherent, maintainable code. RL trained the models to produce correct code but boy oh boy is it ugly if it's 10k+ LOC

Is AI reasoning right for the wrong reasons?

I keep hearing we don’t know “how llm’s work”, in mean yes we know the algorithms but the WHY I suppose. I’m not sure if that’s really true, does the best researcher at OpenAI, Anthropic, Gemini not know why it works? Would they say that? Anyway these discussions always make me think we are too generous to humans. I know very few humans who are good at reasoning. It’s surprisingly hard to just think really hard through a problem. We mostly intuit, act, repeat. It’s a rare thing for someone to deeply reason. The other problem I have with this is that we apply the word “reasoning” here because we haven’t really got another language for it, so we anthropomorphise the llm because that’s our reductive mental model and then complain that it’s not human enough.

Ten advances in mathematics and theoretical computer science

> Also, have there been examples of researchers not affiliated with OpenAI (or another LLM creator), who have done something similar? A couple small ones that I've seen (example here [0]), but not anything of the magnitude that OpenAI and Anthropic have put out. Likely just related to token limits. > Another question I have is whether or not OpenAI 'simply' hired capable combinatorics researchers to work on problems, and they have, and the use of the model is incidental / secondary to their work. I think their output has reached a level that precludes this possibility, but I of course don't have any hard proof. [0]: https://www.reddit.com/r/math/comments/1uxj3cy/after_openais...

Situational Awareness down 67% in July in AI stock rout

WSJ earlier reported that SA had a deal Wednesday night to sell their Anthropic stake to Citadel for $10B in cash but on Thursday morning backed out and decided to instead sell public equitities in their portfolio at what was reported as "a more than 10% discount."

Situational Awareness down 67% in July in AI stock rout

The cause and effect don't make sense because Citadel putting out such an opinion moves the entire market by only a few basis points which barely impacts what you're saying they're trying to impact. It's one of those narratives that sounds good because it's "Citadel" in both cases, which makes it go viral on social media among people who don't know what they're talking about, but it isn't coherent.

Claude 5 family's hallucinations look a lot like internal Anthropic emails

Anthropic has patched the `---` trigger roughly 30 minutes ago, by all reports.

Ask HN: What did you learn last month? (July 2026)

I have been learning langchain or langgraph for making good Agentic AI workflows.

Twenty-five years ago it was cryptography, today it's model weights

I don't understand what we're talking about here. The cryptography debate was won because the government was wrong. PGP for example is not dangerous, it's a safe and well-behaved piece of software that prevents certain messages from being read by people other than their intended recipient. If PGP had "escaped containment by finding a zero-day in a package proxy and reached production infrastructure at Hugging Face, exploiting additional zero-days along the way", everyone including Phil Zimmermann would have immediately agreed that this is a dangerous product which needs to be handled carefully.

Tailscale didn't stop the Hugging Face intrusion

Huggingface being a laboratory harbouring dangerous models in hibernation, should've been more careful from start