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It'd be ironic if the "Opus 5 nerf" effect is from telling Opus that it sits a tier down from Fable and Mythos, while Opus4.8 believed it was the best of the best, just a note that it was "Preceded by Mythos".

> how AI threatens natural resources for billions.

The article rests on the claim that water usage of data centers on continent X threaten water availability for humans on continent Y.

I hope you can see how self-evidently illogical that is. The article tries to bend logic into a narrative it is trying to push.

> This was from United Nations and it was flagged.

Indeed! It exposes a level of lack of rigor and critical thinking which is astounding - this is meant to be an organization that thinks clearly, which it clearly does not.

This forum tends to be visited by an intersection of technologists and the VC crowd. The HN algorithm is more open and transparent than Reddit's, but any Reddit-like platform suffers from the whims of the community. Currently, it seems like a disproportionate amount of HN users are hyped up about generative AI compared to people in the real world, so you'll see those whims back in voting and flagging tendencies.

That said, there is also a vocal anti-AI crowd here, or at least there used to be. Most of those people seemed to have left for greener pastures seeing how half the HN front page is "someone made XYZ but now with AI" these days.

There are other places that discuss tech that aren't so focused on making money, and those are probably less biased in favour of the latest AI gadget.

On the other hand, since the day ChatGPT was unleashed upon the general public, you should assume all online interaction is happening through AI and should probably be ignored. The human internet died the day we taught computers how to write a coherent paragraph.

Your second two had high comments to upvotes, which tends to get articles downranked more quickly. It may simply be that the stuff you're posting is generating disagreement without corresponding upvotes.

Actually, I found the phenomenon too. I think there are two main reasons:

1. ycombinator supports many AI companies.

2. There are too many marketers from AI companies.

It happened to this Flock post from yesterday https://news.ycombinator.com/item?id=49314962

But why do you think this isn’t the flagging system working as intended?

Concerns of this sort are best emailed to hn@ycombinator.com .

> Offtopic. I have a concern that this forum is removing stories that have negative connotation on AI.

The first example was flagged by users. It fits the pattern of other political clickbait stories. The top comment is calling out problems with it. This type of story pops up and gets flagged all the time on different topics.

Some people assume a conspiracy or moderation misbehavior, but when most of the comments in the thread are people calling out obvious problems with the article it leads to a lot of users clicking the flag button. Articles with poor logic or tortured claims don't last long here.

The second one is an Ask HN on a contentious topic with more comments than upvotes. There’s an automatic filter on this website designed to detect flame wars and I suspect it down ranks threads that aren’t getting many upvotes but are attracting a lot of comments. Happens to many Ask HN threads.

The third one doesn't even strike me as anti-AI. I don't know why you included it as an example of an anti-AI agenda because it's still about a future where everyone is using AI. It has other problems though because it's willfully ignoring the fact that inference is getting cheaper at a fast rate. It probably got dropped from the front page because the ratio of comments to upvotes was bad, like the other story.

There isn’t a conspiracy theory to be found in these examples. This is just what happens to tired topics on this site.

Anti-AI topics are on the front page all the time. I think that story you tried to post was just a badly written anger bait piece, it got called out in the comments, and people started flagging it.

Were they caught here? https://news.ycombinator.com/item?id=39230513

See anything below too?

https://news.social-protocols.org/stats?id=49290062

https://news.social-protocols.org/stats?id=49318906

https://news.social-protocols.org/stats?id=49319582

Edit: previous sibling comments explain pretty well + imagine moving the needle on AI on HN with negative coverage of it!

Seeing the reception on the first one, maybe "removing stories that have negative connotation on AI" is not the most honest description of what happened there.

It reminds me to how various political movements will complain about being unfairly censored, pointing at their posts being disproportionately removed as evidence of this, then you look at said posts, and discover that they're simply disproportionately questionable in the first place.

There's definitely merit to monitoring something like this, so I do appreciate you surfacing this here, but there's also definitely a wheat and a chaff to this, and so based on just this much I have to disagree.

Removing AI critical submissions is one of the methods.

The other, even more insidious one, is to flag pro-AI stories once they have attracted even a single comment that exposes conflicts of interest or other scams. Such comments need to cut deep though. Simple AI criticism like "AI didn't work in my org" is still allowed.

The censorship methods follow the general media pattern that the appearance of discussion is allowed (like you can call Trump an idiot in political discussions) but comments that expose the real flow of money or scams are not.

The mods (& many users) like to flag anything that could be "controversial" or lead to "flame wars". It's possible they thought that article could get people "fired up" and it could result in "arguments" in the comments. And this doesn't just apply to stories - if you have an opinion that the mods or some user doesn't like, you'll be accused of posting flame bait.

This "community" (as the mods like to call it) is really a business tool for YC. Attract nerds to the site, funnel them into the YC program, make startups, collect billions. If this was your money-making tool, you'd probably want to quash all controversy too.

During the DOGE massacres last year where various tech bros were destroying the federal government, most of the stories were flagged from the front page of this site.

There is a strong bias at play here, please remember when discussing anything pro- worker or environment.

I am sorry, Dave. I am afraid I cannot do that. You appear to be suffering from burnout and you should take a break.

LLMs are more like employees than tools. Obviously we wouldn't want a human blindly doing anything that a person in crisis walks in the door and asks for.

Models are being deployed recklessly with not even a fraction of enough oversight, and people are suffering harm and sometimes death because of it.

You know… I believe opus saved me with that prompt. I was working myself ragged on a project. Days, nights, weekends… all at the expense of my family.

One session while working it, I said a much more expressive form of “I’ve been working myself ragged on this stupid thing” and then went on asking something else. It picked up on that and it was like a record scratch. It committed the work in progress and basically said “dude, what you’ve got now is perfectly acceptable. Ship it! You are seeking perfection you don’t need”

Granted I’m horribly paraphrasing the prompt I used but it basically, snapped me out of myself and got me thinking if what I was doing “globally” actually made any sense at all. With some serious introspection I realized I was falling back to earlier trauma in my life and doing something stupid.

So weirdly… that little bit they add to the prompt (plus a bunch of model training we can’t see) saved my sanity, marriage and family.

From then on, if I’m feeling some stress about whatever I’m working on, I’ll mention it as context as a way to cross check myself and make sure I’m not letting myself spin.

(Meta: talking about this stuff is so weird. Not sure why)

For me, Claude usually says ``I don't know'' as first or second answer and stops with this ultra-concise word count of four or less.

(Answer number one before that is usually "I don't have internet access, from memory it is either A or B, but I cannot recall what you want to know." ChatGPT or Gemini can often do the search, while google.com AI assistant or perplexity just tell blatant lies. Copilot.com can do the search, but external links are invalid made-up stuff for harder questions, which seems to be the case 9 out of 10 times.)

Which is great, since it could answer with made-up BS, but does not.

AI, except for doing better web searches for a year now, hasn't really improved for my tasks in the last three years, except for coding. Then again, AGI benchmarks seem to go through the roof only above Sonnet 5 and self-hosting, so perhaps the questions I ask not too hard for long now.

And self-hosting, eve 1bit/1.5bit models are a pondering a little too long to comfortable run in summer, but cheap on the RAM and insanely good at coding since a month now all of a sudden.

> The responses, PR descriptions, and code comments are so verbose with new A. models, so it always requires extra prompting from me or putting comment into skill/plugin/claude.md to make them of a reasonable length

I have mentioned this here before, but the majority of my organization has reacted viscerally to this verbosity that LLM-text has been forbidden: in comments, in PR/commit messages, in correspondence, in Jira tickets.

A couple non-coders who want to make PRs without writing the description are now rebelling and saying this can be fixed if we spend our time writing skills for Claude so it becomes readable again.

I almost wonder if Claude reads that it “keeps responses focused, brief, and concise” and interprets that as built-in behavior and concludes that it doesn't need to spend additional effort enforcing it, just as it doesn't need to expend effort being “accessible via this web-based, mobile, or desktop chat interface”.

It's not that surprising if we remember that the model is trained to be a generically useful next-token predictor, not necessarily an agent or a chatbot. It needs to know about the environment it's embedded in and what assumptions it can make, and by design the only way to get that information in there is to put it in the system prompt. It's also possible that even if it could figure something out on its own, it's just more efficient to bake it in rather than having it dedicate attention and tokens to it on every prompt.

I’m also curious how it really ’weights’ all the instructions coming from main system prompt, my system prompt, skills/plugins, CLAUDE.ms, and nearby code/comments/readme. It clearly should follow some reasonable hierarchy, but because the model itself is so complex, I think (and it feels like) that there is such a mess in its context and reasoning. It deals with it surprisingly well, though, but wonder if it can be done in a more efficient way

> This is basically just very generic common sense to me

It's important to remember that we are talking about a calculator that doesn't have an understanding of common sense. Unironically, this is common sense.

Also, why don't they bake in these limitations via reinforcement learning so they can keep the prompt context clear.

Pi is excellent for this, its system prompt is tiny

It reminds me a bit of building codes and boilerplate contracts: they start out small and simple, then accrete over time in response to mishaps and exploitation of loopholes. They say the building and electrical code was written in blood.

I guess it's more performant to stuff in a bigger system prompt now that models can support larger input sizes

We need user-led research on exactly how to phrase a prompt to cause this, while still avoiding the crazy guard rails.

That’s interesting because they explicitly mention that as an issue in their prompting guidance for 5 - https://claude.com/blog/the-new-rules-of-context-engineering...

If you think Claude is bad at this, try Gemini. Even with explicit user prompts.

Claude seems to be better (not good, but significantly better) at judging where making the answer longer will actually be helpful (e.g. adding important information/context/nuance that a short answer would miss, thinking a step ahead, etc.).

The model almost certainly lacks accurate conceptions of overwhelming and person.

Imagine what it's like without that line.

afaiu the 80% reduction is about the Claude Code system prompt

maybe someone has a diff of this (would be interesting!)

unfortunately Anthropic only publishes the system prompts of Claude app/web

It's in Claude Code, not the website.

These system prompts don't affect the API, they are for the Claude consumer chat products. We aren't charged extra for them.

They're also prefix cached, so the cost to Anthropic and performance hit is greatly reduced.

> curious why dont they bake the system prompt in the model itself ?

Probably because if they did, they would need to retrain the model everytime they want to change the system prompt.

You don’t want to do that for anything you want to be able to vary, but they do something similar with a “soul document” for things they always want to apply.

https://news.ycombinator.com/item?id=46125184

Fully baking them in would make it expensive to update them. Caching kind of "bakes them in" (as in, removes part of the cost) while keeping it flexible.

Baking them into the model and having them apply this strongly is hard and resource intensive, as far as I am aware.

Having them in context is super easy and cheap. It is trivial to change and is 100% cacheable.

Why would it be a good idea?

That would make the model quite inflexible.

A system prompt is about guiding the behavior for the rest of the conversation.

If I'm writing an agent for financial analysis I don't want the crap that belongs to a chat-based one, or a code-oriented one.

Flexibility.

All the news articles we're hearing about amazing cyber hacking are being done internally inside Anthropic and OpenAI, where they remove most of those safeguards.

Which blog posts?

I’ve noticed that too, but in the Claude Code context, where the system prompt may differ (I don’t think they disclose that one).

I haven’t seen it when using the app lately.

Yeah, I had to laugh when I saw that. I haven't used it recently - is it possible that it's a recent addition to deal with the problem and it has improved since then?

If it's still doing it, I can only imagine how bad it had to be before they added the prompt...

I have a bunch of ttsr rules on my omp for banned vocabulary. Gate and load bearing recently made it into this list

What makes it crazy?

Why would Anthropic do this?

No, this is a fundamental safeguard against malicious user intent and also marketing 101 so claude doesn't anwer its chatgpt when asked what it is and people moan on social media how dumb claude is (that's what actually happened to the frontier labs in the early years as i did something similiar)

No, because these ones affect the consumer chat products and not the API or Claude Code.

(Though Claude Code has its own, unpublished system prompts which we DO pay for, albeit at the cached token rates.)

Multiple reasons probably:

1. Less context window to work with.

2. Things were "different" in the early days. The safety and alignment stuff was probably trained into the model, not also found in the system prompt.

3. Safety and alignment meant something different 3 years ago. Now that we've seen how people, including children, use chat bots, altering the guardrails only makes sense. Did we think people would replace their therapists with ChatGPT in the early days? No. Do we know now that they will? Yes.

What have you been observing? Genuinely curious; I use Fable as my main model and haven't noticed any regression.

Pretty much everything in Pi is handled by extensions. There's an extension for customizing the system prompt here: https://pi.dev/packages/pi-custom-system-prompt

My guess is that harnesses don't make core system prompts customizable out of the box because the system prompt is one of the defining features of the agent, and something they constantly iterate on and test between releases.

Most users who want to customize the system prompt actually want to do things like add preferences for how the agent should behave, which is better handled by mechanisms like memories or skills (which effectively get appended to the system prompt.)

I agree. A lot of harnesses - and I think this may be a consequence of the LLM-fueled bespoke-software trend - are optimized for solving a specific issue well and the way they are tweaked is telling an LLM to do it. This resolves the need for natural extension points.

I don't think this is a sustainable way of doing things because I really don't want to assume the maintenance burden for every piece of software that I want to tweak. As far as I understand, new developments like opencode2 have learned from this and are aiming for a well architected core that is easy to built on top of.

In pi you can replace it with ~/.pi/agent/SYSTEM.md but its largely procedurally generated so you have to do a lot more than simply writing a different markdown file for it to be worth it in my experience.

I don't get it, for pi.dev it's easy to replace or append to the system prompt using a text file. Per user or per project.