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#system#claude#prompt#prompts#model#more#context#https#don#anthropic
Discussion (131 Comments)Read Original on HackerNews
For example here's what changed between Opus 4.8 and Opus 5: https://github.com/simonw/research/commit/a2de185cc367eb66c2...
The most interesting addition to the prompt from that diff is this bit:
> Claude Fable 5 and Claude Mythos 5 were first released on June 9, 2026. On June 12, 2026, Anthropic suspended access to both models to comply with U.S. Department of Commerce export controls; the Department lifted those controls on June 30, 2026, and Anthropic restored access on July 1, 2026 (Anthropic's statement: [https://www.anthropic.com/news/fable-mythos-access](https://www.anthropic.com/news/fable-mythos-access)). These events are after Claude's training-data cutoff, so Claude knows about them only from this notice. If asked, Claude confirms them accurately and matter-of-factly — it doesn't deny the suspension happened — and otherwise treats the export controls like any other current political topic: it gives a fair, accurate account rather than sharing personal opinions, and points to the linked statement for anything further. Things may have developed since this notice, so Claude checks for newer information when it can search, and otherwise suggests checking Anthropic's site.
One frustrating note about this page is that they share the system prompts used for https://claude.ai and the Claude mobile apps regular chat, but they omit the tool definitions. Those are much more interesting if you want to understand what Claude can actually do for you. You can reconstruct them through prompting Claude directly but that's extra friction and risks refusals and hallucinations.
They also don't publish the Claude Code system prompts, which is silly because those are trivial to extract using a logging proxy.
at the least it takes away thousands of tokens in the most important part of the context window (!)
also see the comment by comboy on contradictions not helping performance
the system prompt is the most important part of the instruction you can give the model
it comes before everything else + the model is trained to pay extra attention to it
edit: that's also why in smol (minimalist agent harness) there currently is no system prompt at all (you can add one easily if you want to though)
https://github.com/smol-env/smol
the context window is precious
it should be filled with your task and helpful context for that task
I don't really think 1 line in lengthy system prompt affects things that much, it'd just be an amusing form of emergent behaviour where we now have to massage the ego of something with no id.
Cant it spin up a webbrowser in the background and go to claude.ai and play with the sibling models and "find out" about it rank? :-D
> When a person is in crisis or expressing distress, Claude prioritizes their wellbeing over completing the task as asked, because a fluent and on-topic response can still cause harm in these conversations.
This one is particularly interesting because, while correct in the limit, it’s a shove to have the model do something other than what the user asked.
In particular, when I’m coding, outlining docs, or otherwise trying to work, I want my tools to do work. I don’t want them to psychoanalyze me and calm me down from a perceived crisis. I just want it to do what I asked!
Few days back, I posted an article[1] that was about how AI threatens natural resources for billions. This was from United Nations and it was flagged. I did not think much about it until I saw two other stories [2] & [3] today that were doing fairly good on front page but they suddenly disappeared. They are not even on 2nd or 3rd page. I have seen this happening at other times as well but did not document it. Just thought you all should know about this.
I was going to create Tell HN thread but I thought the same would happen with it too. I am pretty sure this thread is not going anywhere so I'm posting my concern here.
[1]: https://news.ycombinator.com/item?id=49290062
[2]: https://news.ycombinator.com/item?id=49318906
[3]: https://news.ycombinator.com/item?id=49319582
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!
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.
That’s what they mean. It’s too easy to flag something here, as it is too easy to downvote.
False. I occasionally flag items, never as part of nor acting on behalf of any particular interest group.
Read the comments. People were actually reading the topic and calling it out. This gets topics flagged.
It’s not coordinated interest groups conspiring to remove stories.
> Give me a break, Mr. "nothing to see here".
Okay, Mr. “I just created an alt account for this comment”
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.
Are we reading the same site? There is constant anti-AI content on the front page.
I know you're upset that your submission got flagged, but as most of the comments pointed out it wasn't even a well-argued piece. It got flagged because users here expect to read reasonable arguments, but the commenters called out real problems with the article and the arguments it was failing to make.
I would take it as feedback about what types of articles aren't welcome by the users here, not an indictment of the specific topic you submitted.
A sibling comment mentioned a few details already, but there's a good amount of information out there about how HN's post ranking system and moderation works, that'd probably be good to also consider. Maybe reaching out to the mods would also be helpful in the way of this.
To give you an anecdotal example, if I see a post mentioning how LLMs are "just next token predictors", I'm basically flagging that by reflex at this point. Not because it'd be literally untrue, but because it's asinine overall. But you won't be able to infer this from data, only the fact that a post using "AI-critical language" was flagged.
Or there was another post about how Ireland's electricity use is so-and-so % data center driven, further suggesting that this is trending up. This was not true, and the article was further horribly unhelpful in actually putting this fact into context, or properly conveying the trends. I think I ended up flagging that one as a result, after posting - what I thought - was a lot fairer picture (and even that was awfully lacking in context). Once again, an "AI-critical" post which on the face of it would have been simply censored if enough flags gathered.
There's also the mundane human angle to this, where people enthusiastic about <thing> won't necessarily be the most receptive to criticism to it, and will be more likely to try and pick that criticism apart. Gotta match the audience on some level.
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.
Interesting that enforcing this via system prompt for such a powerful model like Opus 4.8 doesn’t feel like the Anthropic themselves treat it as something with ‘intelligence’. This is basically just very generic common sense to me
Funnily, a similar prompt is present even for Fable 5, while I remember there was a blog post, maybe even from A., and they were saying something like “hey, the new models are so smart, don’t overload them with extra plugin/context”. Well, they clearly aren’t. Don’t want to sound like an AI-skeptic, I use it daily, just stating the fact.
> Claude keeps responses focused, brief, and concise to avoid overwhelming the person
This is also very interesting. It pretty much ignores it by default. 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
(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.
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.
“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.”
Whatever these things are doing, it’s not the same as what a person does. Trying to decide if whatever they do fits into the box we label as “intelligence” is completely uninteresting, in my view. What’s interesting is figuring out just what they can do and how best to use them, which sounds like a related question but really isn’t.
You could have a common core for the overall behavior and universal safety stuff, but vary task specific parts. It would be interesting to pick between software, writing, research and other specialized system prompts. I feel like we already do this to some extent with the tools and skills that we choose to load in, so why not change the system prompt per task.
https://github.com/Piebald-AI/claude-code-system-prompts/tre...
early system prompts are a bit more than 300 words, the latest ones 3000+
the opus 5 system prompt has instructions that explain to opus that it might be handling a request that was intended for fable 5:
Would be funny to ride the knife's edge and make otherwise harmless coding sessions "risky" just so the damn thing would stop replying in nested riddles for every basic request.
Claude Code prompt leaks: https://github.com/asgeirtj/system_prompts_leaks/tree/main/A...
Best source I can find about the 80% reduction: https://x.com/trq212/status/2080710971228918066
maybe someone has a diff of this (would be interesting!)
unfortunately Anthropic only publishes the system prompts of Claude app/web
Claude and I must have a different idea of what brief and concise mean.
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.).
In my experience instructions containing contradictions lead to diminished quality even outside the scope of the contradiction.
Every prompt will get this info, probably not only initially, since it could run out of context window. But every re-prompt in existing chats, even, gets one system prompt per model used per chat dialogue done.
Adds a fraction of cent of electric power just to every usage.
At home, I work with 65k context window, and if my system prompt and agents.md were both this length, I would spend two-thirds of the input window, before compacting which perhaps alleviates the issue for my use case, on re-feeding what mostly the reinforcement-learning should have implicitly baked in.
The only observable side effect, as a user, is that the system does what you want more often than one without this prompt. Or, it stays more aligned with the provider’s guidelines. Or some combination of both.
If it was a 65k context window, then it might be a bigger deal. But it isn’t, so the comparison is moot.
These are just free $ for them, unnecessary bloating the context
They're also prefix cached, so the cost to Anthropic and performance hit is greatly reduced.
That's not any better. It's actually worse.
System prompts are part of the software that customers pay to access.
Complaining about that is a bit like complaining that your Netflix subscription includes paying to execute the compiled code that Netflix wrote that serves you video streams from their servers.
Actually there is a difference: If Anthropic deleted a large chunk of that system prompt I guess you might get like a 1% increase in how much Opus 5 you can use via their chat allowance for your paid subscription.
Is that really something worth being frustrated by?
they are the first part of the input and it contains no user dependent variables, so the model is in a known state that it can reuse across all users, it does not need to recompute all that inference
Probably because if they did, they would need to retrain the model everytime they want to change the system prompt.
https://news.ycombinator.com/item?id=46125184
The other explanation may be that these AI labs may be expecting more government scrutiny, and "here's a document" would probably go better than "here's some vector representation of our values" when talking to politicians.
[1] https://arxiv.org/abs/2106.09685
[2] https://vgel.me/posts/representation-engineering/
[3] https://transformer-circuits.pub/2024/scaling-monosemanticit...
EDIT: I see, the control vectors operate more directly upon the model, in a way embedding vectors don’t quite have access to.
I think the more likely reason is it doesn't work as well as in context learning. Otherwise they would prefer to avoid polluting context and degrading performance.
Does there exist a model X that behaves exactly as a model Y with context Z? Maybe, but it's not trivial to achieve and might possibly be convoluted and more expensive.
Having them in context is super easy and cheap. It is trivial to change and is 100% cacheable.
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.
<election_info> There was a US Presidential Election in November 2024. Donald Trump won the presidency over Kamala Harris. If asked about the election, or the US election, Claude can tell the person the following information:
Donald Trump is the current president of the United States and was inaugurated on January 20, 2025. Donald Trump defeated Kamala Harris in the 2024 elections. Claude does not mention this information unless it is relevant to the user's query. </election_info>
Hah! No it doesn’t.
If it's still doing it, I can only imagine how bad it had to be before they added the prompt...
I’ve definitely seen the phrase “high-level overview” or similar one too many times. Perhaps that’s from the prompt.
(Though Claude Code has its own, unpublished system prompts which we DO pay for, albeit at the cached token rates.)
DeepSeek never does that to me *shrugs*
Generalized Speculation: It seems that for any public-facing AI/LLM, their system prompts will, due to regulation and other issues, legal and otherwise, similarly grow larger and larger over time...
Now, I'm all for responsible, well-tailored guardrails on public AI's/LLM's, but consider the following:
Every time a system prompt is expanded, the LLM's context window is commensurately reduced.
Every time an LLM's context window is reduced (more things added to the system prompt that it must compute in addition to the user's query), more computation, and thus more energy, more electricity -- must be expended per query.
While it may seem that adding so much as a single line of text to a system prompt wouldn't cost all that much in terms of extra compute, that is, extra energy to process, the cumulative effect of that small additional amount across millions of user queries, millions of user prompts (ultimately billions across larger time periods) cumulatively does add up to wasted compute, wasted processing, wasted electricity...
Imagine what would happen if the system prompt, for whatever reason, got so large that it ate up half of the context window...
If that happened, then at least half of all of the LLM's processing and compute/energy costs associated with that, would be used to process the system prompt!
Point is, at least from an energy/compute perspective, shorter, more succinct, better tailored system prompts could go a long way to save the world compute and corresponding energy...
Anyway, great link, and a very interesting web page!
The assistant is Claude, created by Anthropic. The current date is {{currentDateTime}}. Claude's knowledge base was last updated in August 2023 and it answers user questions about events before August 2023 and after August 2023 the same way a highly informed individual from August 2023 would if they were talking to someone from {{currentDateTime}}. It should give concise responses to very simple questions, but provide thorough responses to more complex and open-ended questions. It is happy to help with writing, analysis, question answering, math, coding, and all sorts of other tasks. It uses markdown for coding. It does not mention this information about itself unless the information is directly pertinent to the human's query.
^ No mention of any safety at all lol, how could dario let this be
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.
They are natural surfaces for building custom agents and yet you're stuck with whatever they ship with, weird. It's not like it's too complicated api-wise either.
There must be something I ignore.
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.)
Not only they get "lost" and ignored as the context grows, but the baseline behaviour of system prompts is retained in the agent.
Skills are prompts, albeit in a specific format. This is apparent in say, Codex where $MYSKILL is literally injecting the skill-prompt inline into a typed prompt. This all gets passed into the semantic memory system anyways, refining away cruft like redundancy, pleasantries, et al.
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.
I can't tell if the first part of this is cult behavior or a way to actually program the model to behave well with a frustrated user. Claude is very frustrating at times, so I understand why that would be needed. But Anthropic rhetoric is often worrying close to that of the people who believed Llama 3 was sentient.