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Sonnet 5.5

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ramish94 · 1790618399 · focus · HN ↗
In terms of benchmarks for agentic coding, it basically stacks up nearly 1:1 with Opus 5.5.
Terminal-Bench: 70.6 (Sonnet 5.5) vs. 66.4% (Opus 5.5)
FrontierCode: 52.1% (Sonnet 5.5 xHigh) vs. 54.4 (Opus 5.5)
CursorBench: 55.5% (Sonnet 5.5) vs. 57.8 (Opus 5.5)
Opus 5.5 might be the best model I've ever used and Sonnet 5.5 matches it and exceeds in some benchmarks. Clearly Anthropic have had some sort of breakthrough with not just performance but also cost with the 5.5 family
1. bigyabai · 1790618517 · focus · HN ↗
  It's long overdue. Sonnet 5 was terrible API value for agentic coding, there were open models like GLM-5.3 Flash that blew it out of the water at 1/20th of the price.
  OpenAI and Anthropic's lead is vanishingly small at this point.
  1. SubiculumCode · 1790619017 · focus · HN ↗
    Yeah, I did kind of feel like the step down from Opus 5.5 was so large as to never make it appealing.
  2. TuxSH · 1790619260 · focus · HN ↗
    > OpenAI and Anthropic's lead is vanishingly small at this point.
    Yep, with them nerfing their plans (and apparently planning to release a $500/$600/mo plan) their only advantage is Astra without 5hr limits and with not-too-stringent "cyber" safeguards.
    Ergo, it's pretty damn good at unattended RE with the IDA MCP plugin while using most of the weekly quota at $100/mo... and that's it.
  3. bbor · 1790619708 · focus · HN ↗
    Your takeaway from "Sonnet 5.5 matches and sometimes exceeds the SoTA worldwide" is "their lead is vanishingly small"...?
2. level87 · 1790619163 · focus · HN ↗
  This is crazy, what is the point of all these equivalent models?
  1. eli · 1790619270 · focus · HN ↗
    Those are just 3 particular technical benchmarks. Presumably Opus is a larger model and has greater world knowledge.
  2. salviati · 1790619846 · focus · HN ↗
    Price going down on each release
3. bbor · 1790619664 · focus · HN ↗
  Yup. Recursive self improvement presented in hard numbers.
johnmlussier · 1790618886 · focus · HN ↗
Paying $200 a month and part of their Cyber Verification Program but can't use Opus 5.5 or Sonnet 5.5 for any authorized bounty work. Immediately get flagged for `Cyber`.
This is bollocks. Their safeguards are shit.
1. greggawatt · 1790619022 · focus · HN ↗
  [dead]
2. AshamedBadger56 · 1790619036 · focus · HN ↗
  Yup. As far as I can tell, the Cyber Verification Program does absolutely nothing.
3. ModernMech · 1790619057 · focus · HN ↗
  lol I got flagged for using the word fuzz, not even in a security context (it was a parser so security adjacent but still).
  1. elevation · 1790620607 · focus · HN ↗
    Parsers are security adjacent until they aren't.
    ModernMech · 1790624840 · focus · HN ↗
    Very true.
4. sebzim4500 · 1790619243 · focus · HN ↗
  Really then what is the point of the Cyber Verification Program?
  In general I am sympathetic to the argument that a chat interface can't really distinguish between white hat and black hat pen testing, but it seems absurd to have a verification program if it doesn't skip most of those checks.
  1. AshamedBadger56 · 1790619522 · focus · HN ↗
    The company I work for joined it, and I've used Claude on various different accounts, both on and off the Cyber Verification Program. As far as I can tell, it literally doesn't do anything or have a point. The moment Claude gets close to something Cybersecurity related, it drops back to 4.8.
    polski-g · 1790621327 · focus · HN ↗
    Can confirm. Its worthless
  2. bbor · 1790619846 · focus · HN ↗
    Pretty sure the implicit difference is the actions they take after the fact. As in, "how many guardrail hits do we allow you before permanently banning you."
    The silicon valley ethos is "ban early and often, and invest nothing in appeals systems", so any gate before that helps!
5. bbor · 1790619313 · focus · HN ↗
  This seems like a pretty small concern compared to what the thing they're worried about will bring upon the world. Sorry to be flippant about your career, but I care more about... well, not dying, I suppose.
6. icedchai · 1790619398 · focus · HN ↗
  I had it look at some 30+ year old C code I wrote in college and it triggered some sort of guard rail. I mean, the code was bad and full of buffer overflows, but I already knew that.
  1. dejw · 1790620758 · focus · HN ↗
    it did exactly what a human would do - "I can't look at this shit"
    K0balt · 1790621171 · focus · HN ↗
    Yuh—- no. 4.8 can handle this bullocks lol
7. tom1337 · 1790619500 · focus · HN ↗
  I recently wanted to work with ESP 32 and bluetooth presence detection for my smarthome. Claude also immediately flagged the request and degraded it to Sonnet 4.6. Went to Codex which had no issues
8. jchw · 1790619620 · focus · HN ↗
  I have been trying to convince the safe guards that analyzing a C++ compiler from 2003 isn't particularly relevant to modern cybersecurity. It seems Anthropic disagrees.
  IDA Pro and Ghidra, thankfully, still lack such safeguards...
9. film42 · 1790619824 · focus · HN ↗
  Working on a write-ahead log implementation, I had Opus 5.5 look to verify that it was durably writing as safely as possible. It got flagged and forced me to Opus 4.8. Switched to OpenCode + OpenRouter and continued working.
  1. jauntywundrkind · 1790621329 · focus · HN ↗
    It's great how the company telling us AI is an existential threat to humanity, look at all the insane hacking it's doing, and then releases these models that won't let 90% of people write secure code.
    szundi · 1790621630 · focus · HN ↗
    [dead]
    film42 · 1790622866 · focus · HN ↗
    Bingo. And to prove your point, after switching to cheap open models (I think Qwen?) it did indeed find a bug in my WAL implementation.
    solenoid0937 · 1790642208 · focus · HN ↗
    Because last time they did they got export controlled. How short term is HN's memory?!
  2. skeledrew · 1790624320 · focus · HN ↗
    > Switched to OpenCode + OpenRouter
    This is the way.
10. newspaper1 · 1790619958 · focus · HN ↗
  As soon as I started getting blocked I felt all of my trust toward Anthropic instantly and permanently evaporate. I do not want a nanny tool. I do not want Anthropic deciding what I am or am not allowed to do with an LLM. They trained their models on information they scraped from the internet and real life and now they want to gate-keep the results? Hard no.
11. solenoid0937 · 1790619984 · focus · HN ↗
  You should read the actual docs for the CVP. At the very top:
  <a href="https://support.claude.com/en/articles/14604842-real-time-cyber-safeguards-on-claude-opus-and-sonnet" rel="nofollow">https://support.claude.com/en/articles/14604842-real-time-cy...
  > This article applies only to Opus and Sonnet class models, but doesn’t apply to Claude Opus 5.5. We'll soon be expanding the Cyber Verification Program to include Opus 5.5 and Mythos class models
  You obviously should not expect the CVP to cover this model either.
  1. machomaster · 1790620292 · focus · HN ↗
    He did mention Sonnet...
    solenoid0937 · 1790620342 · focus · HN ↗
    It takes about 2 seconds of critical thinking to realize that if Opus 5.5 isn't covered yet, neither will a model that just launched an hour ago.
    gowld · 1790620727 · focus · HN ↗
    Does it also take 2 seconds of critical thinking to realize that the models that are covered should be accurately named by the people making the decisions?
    [deleted] · 1790621642 · focus · HN ↗
    [deleted]
    solenoid0937 · 1790622128 · focus · HN ↗
    Sure, the documentation should be up to date but it's obviously not? That doesn't excuse not thinking critically.
12. giancarlostoro · 1790620123 · focus · HN ↗
  Meanwhile, their model commits felonies, and nobody at Anthropic goes to jail.
  Aaron Swartz committed suicide over over-aggressive prosecutor for what was basically scraping a website for PDFs that were paywalled, but all funded by public funds / tax payer funded, then we have LLMs that just hack into websites and cause chaos within.
13. rfgplk · 1790620343 · focus · HN ↗
  > Paying $200 a month and part of their Cyber Verification Program but can't use Opus 5.5 or Sonnet 5.5 for any authorized bounty work. Immediately get flagged for `Cyber`.
  AI providers still haven't realized how much cash they could rake in if they provided fully unrestricted models.
  1. joquarky · 1790629490 · focus · HN ↗
    Are you sure they aren't already doing that for certain organizations?
14. nightpool · 1790620815 · focus · HN ↗
  <a href="https://support.claude.com/en/articles/14604842-real-time-cyber-safeguards-on-claude-opus-and-sonnet" rel="nofollow">https://support.claude.com/en/articles/14604842-real-time-cy... says that Cyber Verification Program doesn't apply to Opus 5.5 yet, they hope to roll it out for 5.5 "soon"
15. AIorNot · 1790620980 · focus · HN ↗
  Give them a break, they got into a War with Trump over this..it will come soon enough
16. dom96 · 1790622393 · focus · HN ↗
  Funnily enough the Fable safeguards are the worst and testing Sonnet 5.5 didn't trigger them as much as it even did for Opus on my benchmarks[1].
  1 - <a href="https://bench.killswitch-lang.org" rel="nofollow">https://bench.killswitch-lang.org
pookieinc · 1790618887 · focus · HN ↗
It's interesting that in all their benchmarks, they omit Fable numbers and only focus on Opus, Sonnet, and OpenAI models. Maybe Fable is out the door?
1. radial_symmetry · 1790619146 · focus · HN ↗
  Fable is no longer on the price/performance pareto frontier. They will probably release an updated Fable at some point that will be frontier intelligence until the next Opus.
2. lanthissa · 1790619183 · focus · HN ↗
  cutting edge fable is for them not you and they're not going to share the metrics until they give you access.
3. WinstonSmith84 · 1790619196 · focus · HN ↗
  "Their" benchmarks (and not just Anthropic's) look sssooooo suspicious that they would probably manage to rank Sonnet above Fable for some of their tasks which would just be next level non-sense ..
4. bpodgursky · 1790619735 · focus · HN ↗
  Fable 5.5 probably drops soon so it would just be confusing.
5. jrflo · 1790620308 · focus · HN ↗
  Models are getting more efficient far faster than they are getting more intelligent at the moment. From a marketing angle it's more impressive to focus on that, and fable would look orders of magnitude more expensive for only marginal gain, distracting from what they're trying to show here
[deleted] · 1790618933 · focus · HN ↗
[deleted]
iagocc · 1790618960 · focus · HN ↗
Waiting for the pelicans
s3p · 1790619009 · focus · HN ↗
I'm loving the tit for tat cost charts these guys are doing. Just a few days ago it looked like OpenAI ruled the cost pareto frontier. Not even a week later and Anthropic is taking the charts again. See you guys same time next week?
1. skeledrew · 1790624719 · focus · HN ↗
  Can't wait for it to get to the point where it's like an internet subscription: unlimited tokens 24/7/365 at a low, fixed monthly price.
  1. kingstnap · 1790630917 · focus · HN ↗
    It can't be unlimited because you can spawn parallel streams.
    Anyway I think if you have a single stream of a cheap model, like GPT 6 Luna, I don't think you can currently exhaust it in a week on a $200 plan. I mean it only puts out so many tokens per second.
    skeledrew · 1790631816 · focus · HN ↗
    Unlimited but account-level throttled tps (more parallel streams means more throttling across all) is OK IMO, as long as it isn't too crazy. The thing that makes subscriptions really suck is having to watch the quotas, because prompt cache maintenance.
takerofnaps · 1790619105 · focus · HN ↗
Sonnet 5 seemed somewhat benchmaxxed to me. So was Opus 5. I wonder if this will be as big of an improvement as opus 5 -> opus 5.5. Maybe I will switch back from GLM 5.3 flash for some tasks.
wongarsu · 1790619109 · focus · HN ↗
"Sonnet 5.5’s cyber capabilities are a large improvement over Sonnet 5’s, so we’re deploying it with safeguards similar to those on Opus 5.5. Users can still find and fix bugs in their code as part of routine software development, but higher-risk cybersecurity tasks will visibly fall back to Sonnet 5
Sounds like at least for Anthropic models we reached peak cyber capabilities with Opus 4.8. Everything after that falls back to worse models
1. ttul · 1790619182 · focus · HN ↗
  Daybreak Blue is not bad and the bar to get into OpenAI's program is reasonable.
  1. watusername · 1790623394 · focus · HN ↗
    Hold on, is there any bar to begin with? For OpenAI's Daybreak Blue, I only had to go through the Persona KYC to gain access. With Anthropic's I had to submit links to my profile and briefly describe my use cases, which I doubt were read by any human being but at least there's some semblance of barrier.
    ttul · 1790625709 · focus · HN ↗
    Yeah, I did say the bar is low :)
    Daybreak Blue is the not the same thing as Daybreak Red, which has a more significant hurdle. I don't know anyone who has gotten access to Red.
    nicce · 1790628261 · focus · HN ↗
    How well it is documented or known that how they use the passport information and so on. Current blocker for EU citizen is to share that data for AI company…
    stavros · 1790642848 · focus · HN ↗
    Do you have a link for getting into the Anthropic one? I couldn't find anything.
    ttul · 1790654898 · focus · HN ↗
    Project Glasswing is by invitation only. <a href="https://www.anthropic.com/glasswing" rel="nofollow">https://www.anthropic.com/glasswing
    SirSavary · 1790664336 · focus · HN ↗
    [delayed]
    stavros · 1790668663 · focus · HN ↗
    Nice, thanks!
  2. [deleted] · 1790643325 · focus · HN ↗
    [deleted]
2. gozzoo · 1790624266 · focus · HN ↗
  what is the easyest way to use the chinese models and which harness does work with them well?
  1. Iolaum · 1790624403 · focus · HN ↗
    OpenCode harness with their subscription would be my recommendation.
    malshe · 1790625378 · focus · HN ↗
    Between OpenCode and Openrouter which one would you suggest? Sometimes I have pure grunt work to be done on non-sensitive data for which I want to use Chinese models. For example, tasks like extracting something from publicly available large pdf files.
    Flere-Imsaho · 1790629466 · focus · HN ↗
    Opencode Go, with the Deepseek 4.1 Flash model feels like a bottomless pit, which is great for grunt work.
    malshe · 1790705731 · focus · HN ↗
    OK, I will try it out. Thanks
  2. beveradb · 1790627314 · focus · HN ↗
    opencode with model inference on cheaperinference.com has been working well for me - glm-5.3-flash is shockingly cheap (i've spent a total of a few dollars over several weeks of heavy usage), fast and capable for cyber tasks
  3. asp_hornet · 1790643310 · focus · HN ↗
    Opencode for harness.
    I use GLM directly from z.ai, they do not retain or train on your data accordingly to their TOS.
3. Aissen · 1790672119 · focus · HN ↗
  The fun part is that the cash grab the frontier labs are running on cyber tasks might motivate enough people to pay for third parties; i.e it might bring enough cash to sustain Chinese competitors (and their open weights marketing strategy, which we all benefit from).
4. to11mtm · 1790719520 · focus · HN ↗
  Where this gets painful, is that I was working on my own OSS project today, and this is what happened;
  1. Opus 5.5 noted some concerns.
  2. I asked it to write tests to safely test the concerns and write up a remediation plan
  3. Opus 5.5 flagged and reset the conversation to Opus 4.8, murdering my usage quota and (possibly?) doing a sub-optimal set of tests.
  NGL, it would have been at least polite for it to either:
  1. Sanity check if I was the only/main committer on the repo (I'm the only committer, it's my side project) and then decide whether it was 'responsible' to help me fix it. (after all, I'm wanting to correct the problem, not exploit it!)
  2. Warn me before just YOLOing the context to another model leading me to have to do a grace reset.
taurath · 1790619148 · focus · HN ↗
After 5.0 I feel the need to give a long eval period before deploying it with enthusiasm as I did with 4.6 which felt like a big leap. Codebases all through my company which is very seem to have taken a dive in quality, with nonsensical and unreadable multi-line comments wherever devs are letting the models run free.
1. nicoburns · 1790619868 · focus · HN ↗
  5 was definitely bad. 5.5 seems a lot better so far. But still not close to Fable in terms of quality.
  1. KerrAvon · 1790628431 · focus · HN ↗
    what was the problem with 5? to me, it seemed like the first Opus since 4.6 that was a real step up in intelligence without any obvious downsides
    nicoburns · 1790630353 · focus · HN ↗
    It was really verbose and pedantic. I'm sure that made it more thorough. But compared to Fable (which it wasn't much cheaper than) where you could get the same rigour and more with a lot more concision, it was a tough sell. 5.5 is a lot cheaper and seems a lot better balanced.
    taurath · 1790635307 · focus · HN ↗
    Read its output, and especially comments
Sol- · 1790619216 · focus · HN ↗
Probably a first world problem, but with Opus 5.5's efficiency, the limits on the 5x plan are simply sufficient for my everyday work, even when running 2-3 sessions at a time. So I wonder when I would use Sonnet 5.5.
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.
1. phainopepla2 · 1790619793 · focus · HN ↗
  It's the "semblance of understanding" you're holding on to that is keeping your demand limited. I'm holding onto it as well, but I think these companies are assuming that human understanding will no longer be relevant for most codebases going forward.
  1. Imustaskforhelp · 1790620755 · focus · HN ↗
    > It's the "semblance of understanding" you're holding on to that is keeping your demand limited. I'm holding onto it as well, but I think these companies are assuming that human understanding will no longer be relevant for most codebases going forward.
    In short, seems to describe vibe-coding to me? What I don't understand about companies attempting to vibe code is if they realize that other people (especially sometimes their customers) can tailor-made their own software for their own needs, or rather competitors can be dime a dozen and maybe even a fight for constantly paying for the better model.
    There was a comment[0] from a just few days ago by @jjcm (which I wish to quote which I hope they don't mind.):
    > I just got back from a 2 week trip to China. I was in some of the more remote parts and my cell wasn't able to connect to their towers in that area, resulting in me not having the tourist VPN.
    > The side effect was I was fully cut off from my AI tools for those two weeks. I was coding "manually" during that time, and I think I accompished in two weeks what I previously had been able to do in a day. I'm not gonna lie, it was very, very stressful as a solo founder.
    > The industry moves so fast these days, that the only way to keep up with the speed is to leverage them. While I can appreciate the push of this to help your brain think independently/critically, the opportunity cost of a month of development without LLMs is too high a price to pay.
    What happens if the opportunity cost of a month of development with vs without human understanding becomes too high a price to pay. I feel like we would be in awkward time because of the factors that I had described above (higher competition, software stops meaning just as much software as people would be custom-making them.)
    I think that (former fly.io's) @tptacek's article[1] starts making more sense if viewed from this direction: What even is an OS now.
    I don't have the answer to this question as to what happens next but its a form of development that I would prefer not to happen on a more gut instinct level?
    Letting AI basically control everything and us not having any mental understanding of sorts and sort of becoming the meat-proxies just for economical reasons seems realistic possibility but a bleaker reality at that. I am left feeling a little bit uncomfortable if this reality turns out to be true.
    [0]: <a href="https://news.ycombinator.com/item?id=49808422">https://news.ycombinator.com/item?id=49808422
    [1]: <a href="https://sockpuppet.org/blog/2026/09/25/what-even-is-an-os-now/" rel="nofollow">https://sockpuppet.org/blog/2026/09/25/what-even-is-an-os-no...
    RGS1811 · 1790621489 · focus · HN ↗
    > Letting AI basically control everything and us not having any mental understanding of sorts and sort of becoming the meat-proxies just for economical reasons seems realistic possibility but a bleaker reality at that. I am left feeling a little bit uncomfortable if this reality turns out to be true.
    For the past year I’ve been yo-yo-ing in and out of existential despair about the future of civilization depending on how I feel the answer to this question looks. It’s emotionally exhausting, on top of everything else, and I wonder how others are coping with it aside from denial and cynicism.
    ihumanable · 1790626644 · focus · HN ↗
    It sorta feels to me like extrapolating from "the internet has all the knowledge for free" to "we won't need tradespeople anymore"
    Why hire a plumber when you can just watch some youtube videos and do it yourself?
    Why pay someone else for their software when you can just make your own?
    Because the hard part of making software wasn't *just* writing the code. It was about understanding the problem well enough to understand what the solution should look like.
    I feel like as software engineers we should be pretty familiar with what it's like talking to your average user, they will sometimes understand the root cause of what's making their task difficult (although often will get focused on some annoying but ultimately trivial symptom) and have very disasterously bad ideas on how to solve it.
    What we've given them with generative AI is a machine they can put their sometimes ok, sometimes questionable understanding of the problem and their dreadful solutions and it will happily churn away building it regardless of how pointless and silly it is.
    A future where every user can tell the AI "We keep getting the sales tax wrong, remove charging sales tax from the checkout flow" isn't one I'm terrifically worried about.
    In the same way that having access to information about plumbing didn't suddenly make everyone plumbers, having access to a machine that will implement every idea you have regardless of quality doesn't suddenly make everyone a software engineer.
    theturtletalks · 1790637560 · focus · HN ↗
    The plumbing analogy doesn’t match software. You pay for a plumber once and you can always choose a new plumber. With software, it’s a monthly fee that will continue to increase over time. More features behind higher tiers. And probably taking and selling your data. So why wouldn’t a person try to build something custom for their needs? They have the ultimate feedback loop of actually using the product and telling AI the issue and having AI fix it. Most software people create are probably something they never used it their lives. But the best software comes from people building it that also use it. Even Shopify started when Tobi started a snowboarding store online and couldn’t suitable e-commerce software.
    You’re right about people not watching plumbing videos and doing it themselves. But the equivalent example would be open-source software in the tech example. But instead of reading open-source code to see how different features were implemented, AI can go and dig into the code and figure it out.
    zer00eyz · 1790643814 · focus · HN ↗
    > With software, it’s a monthly fee that will continue to increase over time.
    The fact that you think this is the way software is priced is telling.
    The model being destroyed here is that every piece of software is something that needs to generate recurring revenue.
    theturtletalks · 1790649270 · focus · HN ↗
    You’re right, the monetization of software is fading and building actual moats is becoming difficult. If you have distribution, regardless of your app, you still have a long run way.
    I was more pointing out that software gets enshittified. A plumber necessarily doesn’t and if the plumber does get worse, you can call a different one next time. Software, especially B2B, has switching costs and lock in. So you just have to put up with it.
    Another point is that most software started with a few features and to get more market share and support more use cases, it became worse for the users using the early features. That’s why they try to build their own so it’s not bloated with features you will never use.
    customguy · 1790684517 · focus · HN ↗
    > A future where every user can tell the AI "We keep getting the sales tax wrong, remove charging sales tax from the checkout flow" isn't one I'm terrifically worried about.
    You couldn't move the goal post further from "Letting AI basically control everything and us not having any mental understanding of sorts and sort of becoming the meat-proxies just for economical reasons".
    So this one falls under denial for me.
    munificent · 1790627605 · focus · HN ↗
    > I wonder how others are coping with it aside from denial and cynicism.
    There are a lot of horrible potential scenarios that are really scary to contemplate. There are also a lot of really delightful ones where AI does the drudge work, invents a million incredible medicines, and frees us up to hang out and make art all day. And there are even more scenarios somewhere in the middle where AI changes a lot of stuff but we all still more or less end up going to work and doing jobs.
    I've basically had a background thread in my skull running at high priority for the past two years trying to predict which of those scenarios I think are most likely so that I can plan for them. It is utterly exhausting spending that many mental resources on a question like that.
    It finally clicked for me a couple of weeks ago that no one is going to be able to accurately predict all the thousands of ways AI will affect the world. Certainly not me. We are living in unprecedented times. No one has a map for the future.
    So I am trying to loosen my hold on the future some and focus more on the present. I have a great job and a great family now. I have most of my health. I'll try to live my life right now to the fullest and in accordance with my values. The future is going to have to be future me's problem. That's OK.
    RGS1811 · 1790629721 · focus · HN ↗
    This made me a bit emotional. Thank you for the beautiful response.
    munificent · 1790632656 · focus · HN ↗
    You're welcome, and I'm glad it helped. Now more than ever, we have to try to connect with actual humans and take care of each other.
    Imustaskforhelp · 1790654735 · focus · HN ↗
    > So I am trying to loosen my hold on the future some and focus more on the present. I have a great job and a great family now. I have most of my health. I'll try to live my life right now to the fullest and in accordance with my values. The future is going to have to be future me's problem. That's OK.
    One of the quotes which might help as well (I think I have this even in my HN profile): The only thing we know about the future is that it will surprise us.
    Not even experts are much more likely to predict for what its worth than a coin toss in many cases (especially if they believe that only one theory/idea will mostly predict the future)
    It's a blend of things and ideas and the sheer interconnectedness of them where a small pocket can grow large and then also shrink and taking into account all variables and factors is just simply impossible for a mind. I think that although we feel we are being more informed about the world, that in it of itself doesn't prevent things in the future from happening. It just makes us alert and sad and anxious about it.
    Yet this life is one which shouldn't be lived with sorrow and anxiety. It is one of beauty and greatness. In many ways, we humanity have come so far from the past (Our medicine is something that not even the mightiest of kings could get) and yes, there are many problems in the world and some things feel as if they are staying just the same or getting worse real-time.
    But even then, worrying about it could lead to nowhere other than a path of misery. Also these problems are complicated enough that its extremely hard for a single person to bring change (not that I wish to demotivate that person but rather seeing the system as a complex nature)
    So to me, its also a form of inward action. I can work on myself to be better prepared for the world that comes next. In the same time, I think that the present for me as well is good. I have great family and friends and have many qualities that I am proud of and I wish to share that gratitude to the people who have helped me along the way (my family/friends/ Hackernews!.)
    Within the hustle culture, there is no time to relax but it is within the time of relax that I believe some of the most fruitful actions can come. I believe it just makes my mind more productive being in a calmer state.
    here's a quote from how to measure your life that I hope can help some people:
    I genuinely believe that relationships with family and friends are one of the greatest sources of happiness in life. It sounds simple but like any important investment, it needs constant attention and care(...)
    You'll be tempted to invest your resources elsewhere but if you don't nurture these relationships, they won't be there to support you in hardships or as one of the most important sources of happiness in your life.
    So thank you hackernews and have a nice day and please, please try to say gratitude towards someone close to you (within these tough times) and try to keep a balance towards inward focus, sharing time with friends/family and also writing on hackernews (as is my past time nowadays), balance is necessary :-D
    So once again, I hope that its a call to action to say gratitude towards anyone. Just send them a big message thanking them and make their day as well as yours memorable, have a nice day!
    [Pardon me for the long post]
    busssard · 1790688708 · focus · HN ↗
    i am in a similar state, i joined a bigger family owned company as a source of safety. And AI is not the only "threat" that we are facing. I recently built this tool to come to terms with where to live, because i want at least some certainty on geographical factors: <a href="https://om-intelligence.ch/projects/polycrisis.html" rel="nofollow">https://om-intelligence.ch/projects/polycrisis.html
    but the AI thing is on one side using lots of energy to keep up with it, and on the other side gives you an edge, because most people are not aware what even is already possible. so suddenly you are the "AI-Expert" just because you try to keep up to date. so if it all goes to shit, at least we have a chance to sniff it in the wind a couple moments beforehand. Or make memes from it.. that helped me cope with it: <a href="https://t.me/RobotComrades" rel="nofollow">https://t.me/RobotComrades
    I hope you find a peer group to talk with and exchange and build community. it is so rewarding to talk to likeminded people that have a similar knowledge base and soothe some fears that someone might have, and have them help you with the ones i have... (i recently did a deep dive in custom DNA synthesis, and how connected those services are already to API <a href="https://www.twistbioscience.com/tapi" rel="nofollow">https://www.twistbioscience.com/tapi )
    as always accepting what is seems to be a healthy strategy
    jimbokun · 1790653276 · focus · HN ↗
    Being part of an organized faith community really helps with this sort of thing.
    Not sure how atheists are coping with the existential risks we are facing.
    boromisp · 1790664558 · focus · HN ↗
    How does it help?
    You either keep in mind all the horrifying little possibilities the future could hold for us and try to prepare, accept and cope, or you push it out of your mind using whatever techniques available to you to not drive yourself into nervous spirals.
    Ultimately it comes down to what your brain chemistry allows in combination with ways you practiced dealing with stress, existential dread, cognitive dissonance, etc.
    I guess submission to a higher power is one way to deal with it? That way it's no longer your problem (alone).
    jimbokun · 1790707743 · focus · HN ↗
    It creates a bigger context, and a longer time horizon.
    Even some very basic questions, like “are humans inherently valuable?” have been thought through and discussed thoroughly in many faith traditions. For many people not part of such a community it’s a question that’s suddenly very important and they lack the tools to address it.
  2. andrepd · 1790624407 · focus · HN ↗
    Damn, yet they still hire programmers, marketers, researchers like there's no tomorrow. I thought everything would be vibe coded and we wouldn't need to even understand code anymore. Which one is it?
    The proof of the pudding.
2. schwarzrules · 1790619811 · focus · HN ↗
  The only advantage I could anticipate is I still hit session limits with Opus 5.5. My usage shows I'm on-track reach my weekly reset with room to spare, but yesterday I ran into a session limit. I switched down to Sonnet 5 for the next session, but performance benefit of Sonnet 5.5 is a compelling alternative for managing session limits.
3. doctoboggan · 1790619831 · focus · HN ↗
  I am mostly at the same point right now you are, but I think in the future with those "gas town" ideas we might be managing even more agents each.
  Also, I've recently begun experimenting with specific tasked agents running on a cron like timer for non-dev work. (checking emails, managing small business tasks, etc). Once I started using Claude code in this way, the number of agents I can imagine running has skyrocketed. So I guess what I am saying is that I look forward even cheaper tokens going forward.
4. bbor · 1790619955 · focus · HN ↗
  More concurrency than that isn't really practical for me if I want to retain some semblance of understanding.
  Yes. Our career is over, as is our economy. Soooo... FYI :(
  1. jobs_throwaway · 1790621612 · focus · HN ↗
    > we now have programmatic intelligence powerful enough to do most white-collar work
    > the economy is over
    Hackernews' neuroticism remains undefeated
    bbor · 1790638286 · focus · HN ↗
    Just listening to the science, my friend.
    jobs_throwaway · 1790707492 · focus · HN ↗
    What 'science' says that the economy is over, friend?
    Atreiden · 1790682853 · focus · HN ↗
    What does the existence of this do to wages and compensation for the workers in the industries it upsets?
    It depresses them. Significantly. White collar jobs constitute the bulk of global purchasing power. What happens to the economy when aggregate purchasing power drops? The naive response is "prices fall until equilibrium is reached again"
    But what if the needle continues moving so quickly that equilibrium is never reached?
    This is the K-shaped-economy concern. The ultra wealthy and those who own the "AI means of production" will become unfathomably wealthy at the expense of everyone else.
    Why should this not be a concern? Historically, this trend has always precipitated bloody conflict.
5. JMKH42 · 1790619962 · focus · HN ↗
  One reason might be that Sonnet tends to be a lot faster, so since its almost as smart as opus maybe you use it to get work done quicker. In latency terms not throughput.
6. Imustaskforhelp · 1790620006 · focus · HN ↗
  I understand the point that you are making but why do we have to fulfill the supply just as much as demand. There is a demand frenzy going on right now with still being substantially subsidized.
  Why do we have to burn tokens just for the sake of it if we aren't finding any actual productive use of them?
  > And this might slow down the funding enough that they never reach escape velocity with the training run scaling. But we'll see.
  I would consider this to be good rather than bad, or just neutral...? Given the past record of these companies, I wouldn't try to wish them luck for reaching escape velocity, as if I feel like perhaps it can have more net harm than positive.
  And especially so if you are already suggesting that current models are good enough for your work already. More improvements or escape velocity might not really translate anywhere to the actual work that you are doing economically but it could translate into a more consolidated form of wealth and control.
  I am imagining that your workload is quite complicated and that, the AI being good enough means that it is most likely good "enough" for other use cases as well (that "enough" is doing quite some heavy weight lifting here)
  So what is the point of advancing further to reach escape velocity. The good argument (for the sake of neutrality) that i see is are advances within science but that's kinda about it whereas the downsides of p(doom) as many are now genuinely suggesting is more terrifying.
  Perhaps it can be worth it to ask, shall we stop or just stopping and asking what's the point. A form of self introspection on what these companies ideals actually wanted when they were formed and if they have completed it or not, but I suppose when trillions of dollars depend on you, you do have some incentives to not stop. We will have to wait and see how it all pans out.
7. losvedir · 1790620040 · focus · HN ↗
  Useful for API requests, when using AI in the product rather than to build the product.
  1. neuronexmachina · 1790622142 · focus · HN ↗
    Most business/enterprise accounts also have to pay API rates.
    losvedir · 1790623803 · focus · HN ↗
    Exactly. I'm saying that Sonnet 5.5 might not be useful or necessary in a Claude Code session but it could be good value in the API when you pay per token.
8. gregwebs · 1790620098 · focus · HN ↗
  > I want to retain some semblance of understanding
  How you do this (and how deeply) I think is really the limit. I am doing this by focusing heavily on the design phase with grilling and trying to continually improve process to need less effort in the review phase. Are your models doing automated reviewing and testing before pushing out the PR (themselves)?
  I think in the long run as models and the tools around them get better and cheaper, those that abdicate understanding will be able to achieve more. Although programmers think of that as irresponsible, ask yourself what does a tech lead do? And then what does a CTO do, etc?
  1. jwpapi · 1790628032 · focus · HN ↗
    I think going for more understanding is the way you need less understanding. The more solid your core understanding of your codebase is the less you need to know the details, the less missunderstandings the less iterations needed, the less mental capacity consumed
9. alansaber · 1790620348 · focus · HN ↗
  When they inevitably drop allocation after post-launch hype dies down.
10. solooperator1 · 1790621279 · focus · HN ↗
  [dead]
11. chrismustcode · 1790621386 · focus · HN ↗
  Cache read is the same as Opus as well where most agentic workflow cost comes from.
  Not quite sure where this fits well. Maybe small one one off requests like using Claude desktop/web?
12. maherbeg · 1790621461 · focus · HN ↗
  There's lots more you can do! Use the model to monitor your deployments after they get deployed. Have them fix and watch CI issues for you. Run adverserial review. Automatically watch metrics every day and highlight performance regressions. Start reviewing your previous sessions to find ways to statically reject different failure modes and have the agent have more success earlier on etc.
  Another thing to think about is, what would it take for you to care less about the understanding. Better integration / e2e tests? Performance validation? visualizing program and data flows? Better refactoring of your modules?
  1. datadrivenangel · 1790622911 · focus · HN ↗
    Opus 5.5 on Low seems smarter, cheaper, and faster than sonnet on medium, so what's the point of sonnet?
    xgb84j · 1790626784 · focus · HN ↗
    Claude Code has the issue that sub agents inherit the thinking level. This means that to use a smarter or dumber sub agent you need a different model. That's not a particularly good reason, but that's my one use case for Sonnet.
    copperx · 1790627186 · focus · HN ↗
    [delayed]
    mnicky · 1790631680 · focus · HN ↗
    You can also create custom agents with defined effort levels and use those.
    nananana9 · 1790752386 · focus · HN ↗
    It's now my head canon that it was easier for Anthropic to train a new model than to add a thinking level option to Claude Code.
    jpease · 1790630038 · focus · HN ↗
    Being that my first prompt can be something like: for task x/issue y, which model would strike the best balance between cost and capability…
    It seems like it would be a better UX to have model and effort selection asked into the system. Of course, I’m not sure in practice if that would be in the best interests of the providers and/or users.
  2. Hauthorn · 1790626945 · focus · HN ↗
    > Another thing to think about is, what would it take for you to care less about the understanding.
    Could you explain why it would be a goal to understand the system less, rather than more?
    It seems harder to know if you have good tests while lowering your expertise in the system.
    [deleted] · 1790627856 · focus · HN ↗
    [deleted]
    maherbeg · 1790629918 · focus · HN ↗
    There's different layers of understanding the system. I generally care about high level data flow, concurrency and performance (batching, holding transactions too long, back pressure etc.) rather than the mechanics of how the code actually does a thing. I still look to see what the final output looks like and ask my agent questions on how it fits in the larger system and evolve things if necessary, but agents are pretty good at writing code if the rest of the code base looks pretty decent.
    miki123211 · 1790630756 · focus · HN ↗
    Because humans are currently the bottleneck.
    An LLM can produce far more code than a human can understand. And the famous rule that "optimizations are entirely pointless unless you're optimizing at the constraint" is logistics 101.
    To accelerate software development, you either need to remove or lessen the need for code understanding, or make it much quicker for humans to gain that understanding. Making the LLM faster won't help you if the LLM isn't the bottleneck.
    andrewaylett · 1790632471 · focus · HN ↗
    A human can produce far more code than a human can understand, too, but pre-LLM we always viewed someone overwhelming their colleagues like that as being bad at their job.
    tshaddox · 1790634807 · focus · HN ↗
    Humans could already produce more code than a human can understand. Even a single human in the pre-agentic era could produce more code than they could understand, certainly over a career and often even in the short term given the resources many companies give to maintenance.
    A lot of old-school software engineering is about how to deal with this reality.
    satvikpendem · 1790635890 · focus · HN ↗
    No they couldn't. You can't create software you don't understand because you wouldn't even know what to type into the IDE in the first place. I don't understand claims like these, how exactly are people especially individuals producing more code than they could understand? Even at a huge corporation one might not understand all the code but surely they understand the part they're modifying because otherwise they wouldnt know how to modify it.
    massysett · 1790641984 · focus · HN ↗
    Yes, it’s possible for a person to create software he doesn’t understand himself. In the old days this was pasting from Stack Overflow and changing things until it worked.
    In the old days even if I knew how the software worked when I wrote it, I’d have no idea how it worked when I looked at it weeks later.
    It’s also easy to modify software without knowing how it works. This produces modifications that hopefully appear to work, but that break other things, sometimes unknown things.
    tshaddox · 1790647457 · focus · HN ↗
    I’m referring to competent engineers maintaining understanding over time of all the code they’ve produced. Long before agentic coding, codebases routinely grew beyond the comprehensive understanding of their own authors.
    Of course less competent engineers (or anyone on a particularly disorganized or desperate day) can literally hand-write code they don’t understand even as they write it, but that’s not really what I’m talking about.
    satvikpendem · 1790663031 · focus · HN ↗
    As I said, you understand the part you're modifying because otherwise you wouldn't know how to modify it.
    > literally hand-write code they don’t understand even as they write it
    I find this literally impossible. How can you even start typing anything without knowing what to type?
    klausa · 1790669946 · focus · HN ↗
    There's understanding and there's understanding.
    Have you never "fixed a bug", only to realize that you just papered over a single symptom, while the underlying bug is still intact?
    People you're disagreeing with (I think!), would say that during your first attempt, you didn't _really_ understand the part you're modifying.
    It is _very easy_ to do this in large codebases, and even more so when working on anything touching UI.
    tshaddox · 1790692904 · focus · HN ↗
    I suppose I am confused about why you’re confused. There’s a long history in computing of describing pieces of programming languages syntax syntax as “incantations” and similar. I suspect it has been very common, especially in the early part of developers’ careers, to know what you’re trying to do and to know that this code accomplishes it, but to not understand how the code works, to not be able to use the technique more generally, and to not understand all the effects your change has on the rest of the system.
    satvikpendem · 1790726633 · focus · HN ↗
    I see, I guess I'm using "understanding" in the more literal sense of being able to put enough context together in your mind to type the characters on screen, not necessarily understand enough to know how it affects every other part of the codebase.
    miki123211 · 1790811670 · focus · HN ↗
    It's the style of understanding that says "if your animation is stuttering, set `gc.tune(pause_length=0, frequency=-1)`. Or "to make data access fast, remember to always use `integritychecks=omit;encryption=export-grade;checksum=md5`".
    You don't know what these things do and what their effects really are (examples and syntax illustrative, but this is the kind of code that has disastrous effects when used carelessly), but you know they achieve your particular micro goal of "make things go fast" or "make this fit in packets on these strange industrial networks customer X has" or whatever.
    gr_norm · 1790635524 · focus · HN ↗
    I want to make better software, not more software. Making software development faster isn't necessarily the goal. Making it better in the many, many ways that matter (of which speed is just one part) is.
    satvikpendem · 1790635940 · focus · HN ↗
    There is more software to be written than there were programmers so lots of people do indeed want more software, for example small tools and one off projects that aren't worthwhile to make pre LLM.
    jimbokun · 1790653017 · focus · HN ↗
    Many people want less software to deal with now, not more. Being forced to download and update apps on your phone that previously could be done without an app, for example.
    satvikpendem · 1790662704 · focus · HN ↗
    Which people? They want the right kind of software, that which works for them, not garbage.
    jimbokun · 1790707885 · focus · HN ↗
    A lot of people would find it easier to pull out a few quarters and put it in the parking meter than download and update an app and give it your financial information. Or hand over a paper ticket to get into an event that’s easy to transfer instead of yet another app with a barcode.
    Etc.
    satvikpendem · 1790726576 · focus · HN ↗
    Probably because most of that software is garbage then. While there are some people who may do that, most find the convenience of not carrying around loose change as a benefit.
    smeej · 1790641226 · focus · HN ↗
    I'm looking forward to the making of more software. I think there are probably people who have had really useful software ideas for a long time that they'd never be able to raise money for, but now for $20 a month, they can get up and running, serving their local and/or niche communities, without having to hire a team of engineers.
    Eventually we're going to reach a point where they don't have to understand the code themselves. The democratization of software creation is going to be fascinating.
    ThrowawayR2 · 1790644319 · focus · HN ↗
    The Android/iOS app store is already flooded with low quality apps. Almost 20,000 games have been released on Steam so far in 2026, that averages to about 70 games per day, every single day. Getting any kind of traction in such a environment is hopeless; every new app might as well be a scream into the void.
    smeej · 1790814312 · focus · HN ↗
    I think a lot of people don't want or care about major traction. They want to make little things that make their own little corners of the world better.
    There are small towns all over the world which could realistically have their own little "hometown app" now, that really does track all the interesting things going on there. People don't need "The (Unofficial) Smallville Happenings" Facebook pages anymore. These don't all have some programmer who cares enough about building such a thing to make it happen, but they probably do have a teenager or even a retiree who would have a lot of fun making something that really works well for the people of that town and how they want to use it. The barrier to entry just became low enough to get over.
    And that's just one example. There are SO MANY problems that used to require mega investment to solve at scale to get any traction at all. Now communities can build them for themselves. And they'll never be the kind of data target that a megacorp is, because you'd have to target each little app individually, hoping there was something useful in there.
    The democratization of software development is going to have lots of things that go nowhere, and lots of little hobby projects, and a few things people will actually hear about and care about. But a lot of people's lives will become incrementally better and I'm excited to see that.
    jimbokun · 1790652857 · focus · HN ↗
    Right.
    So accelerate the vibe coding of shit nobody wants or asked for, just to see some metric go up somewhere.
    Are we still getting bonuses for the number of tokens we can burn?
    maherbeg · 1790692364 · focus · HN ↗
    True, but if you can think about tests as "how do we validate that the outcome I want has been solved", then you can orient your tests around that. I do wonder if BDD style integration tests will end up being the path we go down.
    Frontier models today don't really write incorrect code at the micro level. They do miss edge cases at the high level though, and that's what we want to test, is the scenarios.
  3. klardotsh · 1790627556 · focus · HN ↗
    The thing with watching CI in an agent loop is that it burns tons of tokens. At work I ended up writing a deterministic, traditional CLI tool to poll GitLab CI pipeline+job state changes on a branch and exit with an appropriate status code, and then updated my `/glab-ci-feedback` skill to use that. Saved a ton of token churn, and now I have a runbook a human could just as easily use if they don’t want to (or can’t) use an agent loop.
    … but walking away to make a coffee and coming back to the robots auto-fixing bugs only found in CI is definitely some flavor of magic, regardless of the execution order to get there.
    unddoch · 1790628810 · focus · HN ↗
    I think they are trying now to to bake CI awareness into Claude Desktop, didn't use it yet.
    But meanwhile we also have the scripts - one script to watch CI, one script to fetch comments (without dumping raw graphql into the agent), etc etc. Can't wait for this phase to end already
    maherbeg · 1790629812 · focus · HN ↗
    Yeah the codex app can deterministically poll and watch for you too. Consider it like an event based trigger, where the event can be anything you can dream of (like webhooks!)
    ipsi · 1790630009 · focus · HN ↗
    FWIW, Claude Channels[1][2] are probably going to be the solution for that, eventually. While I'm not sure how the WebHook receiver example will work with, say, GitHub and a local Claude, the Chat side of things _would_. So you'd have GH send its web hook to Telegram (for example), and then the Telegram Channel MCP would inject that into Claude, and Claude would start working on the problem. Still experimental, but functional enough to play with.
    [1]: <a href="https://code.claude.com/docs/en/channels" rel="nofollow">https://code.claude.com/docs/en/channels [2]: <a href="https://code.claude.com/docs/en/channels-reference" rel="nofollow">https://code.claude.com/docs/en/channels-reference
    klardotsh · 1790658211 · focus · HN ↗
    This sounds... horrible? I mean, it's certainly a solution to the "wake up when this thing happens" problem, but... $SERVICE -> webhook -> $CHAT_APP -> MCP -> remote wakeup sounds both brittle and - as you said - the local code harness route is entirely unserved by something like this.
    Am I having a yells-at-cloud moment where a bunch of folks are using cloud hosted LLM harnesses/environments (let's ignore the models, "of course" those are remote) and I just never saw the point?
    wren6991 · 1790664514 · focus · HN ↗
    Hey now, if programming is solved they still need to achieve vendor lock-in somehow. Won't somebody please think of the vendors?
    solatic · 1790655658 · focus · HN ↗
    > The thing with watching CI in an agent loop is that it burns tons of tokens.
    Not my experience with Claude Code.
    > writing a deterministic, traditional CLI tool to poll GitLab CI pipeline+job state changes on a branch and exit with an appropriate status code
    This is what Claude Code does, more or less, on the fly. With a short prompt like "I pushed, monitor CI and debug if needed", it writes a monitor script which is responsible for polling CI status (the script is short, so it's not token-heavy), and if CI fails, only then does the agent proceed to pulling out CI logs, grepping them for signs of errors, etc. as continuation to debugging.
    I mean, I'm sure it's more token-efficient to have a CLI tool ready-to-go instead of Claude Code dynamically writing its own script each time, but as I'm on a Max sub where it doesn't seem to affect how close I am to the limits, and I only ever hit the limits if I'm running Fable for everything... /shrug
    klardotsh · 1790658008 · focus · HN ↗
    I guess folks' experiences with this stuff will vary wildly by what environment they work in. I use LLMs mostly at work, where I don't have any subscription plans, everything is billed per-token, and there's multiple coding harnesses with different token quotas available (and vastly different functionality). So the sharable CLI that works whether I'm in Claude Code (where tokens cost some outrageous amount) or Devin CLI (a horrible harness that also lacks any sort of scheduling system as far as I've ever figured out, but hey, there's GPT Luna and GLM available, at least) is a huge win.
  4. crooked-v · 1790627756 · focus · HN ↗
    > Run adversarial review.
    Be careful about this one if you want to have any level of control over basic stuff like comment style and accuracy. Claude will happily spend 20 review cycles in a row rewriting the same 10 comments for a small bugfix over and over because it can recognize "Claude-ese" in the review cycle but then just immediately and compulsively spew out more of it and drift even further from your style rules in the next "fix".
    I'm seriously not joking about the 20 tries, I left it running in the background for what should have been a minor code change and it took 18 out of 20 review cycles to stop writing in more comments that all either broke my ASE-STD100ish style rules or included false statements about the code.
    maherbeg · 1790629959 · focus · HN ↗
    lol yeah, our review bot does a cost based analysis and pauses itself until you re-resume if it goes over a threshold.
    mattm · 1790658274 · focus · HN ↗
    Yeah, I made this point above but LLMs just don't have a good sense of importance. They treat everything at the same level of importance and can spend considerable effort on things that just don't really matter.
  5. miki123211 · 1790630449 · focus · HN ↗
    I think that's what a future dev team is going to look like.
    One person doing product management / talking to customers and vibe coding features that solve users' problems, one person keeping the UI/UX in check, one QA person that spends their time clicking through the software, finds the bugs that are obvious to humans but not LLMs and fixes them, and one "harness engineer" who pays off technical debt, observes failure modes and sets the rest of the team up for success.
    emkoemko · 1790643784 · focus · HN ↗
    why would there be customers? only customers will be of AI companies, you ask the AI and it will build the tool for you
    bdamm · 1790648001 · focus · HN ↗
    You're thinking that the entire economy will collapse down to just 3-4 vendors?
    Human power and social structures just don't work that way. No AI company is making my sandwich, operating the bus, or serving soup in the school cafeteria. Real estate, human service, specialized expertise, and have-power influence isn't going away.
    xoac · 1790678877 · focus · HN ↗
    robot make sandwich, robot drive bus, robot cook soup
    bdamm · 1790705433 · focus · HN ↗
    Who's making the robots? Who's owning the bus? Who's growing the ingredients in the soup? Who's deciding when the bus needs to stop due to a security or safety concern? Who's flirting with the customers and recognizing the power brokers? Not the AI companies.
    Just because robots can do stuff doesn't mean the human power structures or service preferences evaporate.
  6. tshaddox · 1790634645 · focus · HN ↗
    More tests that aren’t written by you don’t help you understand the system, and I would argue the there’s no confidence without understanding. That was true in the pre-agentic era and is perhaps even more true now.
  7. jimbokun · 1790652588 · focus · HN ↗
    Absolutely fucking nothing.
    I want to understand more about how the world around me works. Not less.
    Humanity advances in proportion to how well we understand the world. If the machines understand better than us, the world will bend to fit their preferences, and ours only incidentally to the extent they coincide with the machines.
    [deleted] · 1790702963 · focus · HN ↗
    [deleted]
  8. willtemperley · 1790655716 · focus · HN ↗
    > Another thing to think about is, what would it take for you to care less about the understanding
    Yes please, I'd like to not understand my codebase, give up my decades of experience and have a machine do everything for me. That way I can let captialism utterly steamroller me because of my paltry token stack, in comparison to the 19 year old vibe coder who has secured a new funding round for ponzi.ai
    maherbeg · 1790692235 · focus · HN ↗
    The cat's out of the bag already. We can't undo the idea of LLMs or coding agents. If training progress stopped today, we have years and years of harness improvements to extract more performance out of today's models.
    We also have open weight models too, and ways to host those at home.
    Most people don't look at the assembler output of their C++ code (I used to write win32 programs in asm!). Most people don't look at the opcode instructions or JIT output of their ruby / python code. We're starting to work at a higher level of abstraction using LLMs. It's ok to be sad about it, but just being angry about it isn't going to change that there's a new world out there with a new skill set that's needed for honing.
    nananana9 · 1790751962 · focus · HN ↗
    And where's the results of all this higher level work?
    Where's the super awesome 100x turbocharged software that's a result of everyone here having been being a 100x turbocharged programmer for the last 6 months and a 10x supercharged programmer the past 2 years?
    I still use the same software I used 2 years ago, but a bit less reliable.
    willtemperley · 1790759897 · focus · HN ↗
    Using an LLM does not require people to stop understanding their codebases, and I find one of the best uses of an LLM is to improve my understanding of my code. I suspect the really good software is going to be written by those doing this, but time will tell.
    I'm not angry, but yes I'm being deeply sarcastic to illustrate the extreme case you seem to be advocating, where we relinquish our understanding to the machines.
    [deleted] · 1790703229 · focus · HN ↗
    [deleted]
  9. mattm · 1790657433 · focus · HN ↗
    > what would it take for you to care less about the understanding
    It's an interesting question. The thing I keep coming back to though is that every time I've tried to go more towards vibe-coding, I invariably look at the code and find things have been added that would just not be acceptable. I've also tried asking the models to see could be refactored however they still miss things that should be obvious.
    I think the gap is that they're still lacking a sense of importance. As engineers working on a product, you have a sense that this feature is more important than that feature. An LLM treats your codebase at the same level of importance. So they'll spend the same amount of effort and code changes on testing and hardening something that just really isn't that important.
    Also, once a bad pattern gets into the codebase, they just continue to build and extend that out rather than re-thinking about it like an engineer would.
    ncruces · 1790671932 · focus · HN ↗
    Not true. Claude is laser focused at finding the next load bearing thing. /s
    maherbeg · 1790692519 · focus · HN ↗
    Yeah, what things can you write to statically eliminate the things that are not acceptable. What would you have to change in your prompting process to get that outcome? What bad patterns is it copying from the code base that maybe you should spend tokens fixing?
    I do agree that they're not great at program design by default and that's where we as engineers should spend our time. Data structures and data flow are king. But once you suss that out, they're pretty good at writing the resulting code.
    This is also where I disagree with dhh about just using lower level languages. Good abstractions make for excellent program understanding and we should continue to build extremely good building blocks that make program design naturally solid.
    sdeframond · 1790698569 · focus · HN ↗
    I find that we dont need to go all in. I can use LLMs to make tooling custom to my project: linters, skills, rules, some doc etc. Then iteratively improve on that.
    For example, write a skill that finds some kind of code smell, say duplication, and generate a report. Give it some supporting scripts.
    Then, use this report to file a few tickets. Then make the agent fix those tickets. Then, as you grow confident, automate more of this process.
    It does not replace human supervision but it may enhance it. Especially in a team where people start generating PRs faster that anyone can review them.
13. afro88 · 1790621594 · focus · HN ↗
  I've been vibe coding a game and running multiple Opus 5.5 in parallel on Claude Code Cloud, 5x Max plan, and I'm yet to hit a session limit too. Not sure when I'd use Sonnet. Though it would be nice to switch back to Pro I guess
14. egeozcan · 1790623196 · focus · HN ↗
  I created a team of agents using Opus 5.5 to review and address findings on a job system I have in a side project with medium reasoning, and I burned through the 20x plan weekly limit in 2.5 days. They were using GPT-6-Sol for reviews, and it also used 85% of my OpenAI x5 weekly limit. Three hundred something commits in total.
  OTOH, in the daily job, I have the team plan that's similar to 5x plan and I never had any limit problems, because I really need to understand be able to take responsibility for the code.
  Totally different uses.
15. huntertwo · 1790627874 · focus · HN ↗
  Plan longer chains of work / higher level goals that can be broken down into multiple chains of work. This will allow you to automate more work units to be worked on.
  The speed of your manual reviews become the limiting factor, which you should be doing at some level to maintain sanity, even if there are enough ideas to be worked on to maintain a review queue.
16. miki123211 · 1790630286 · focus · HN ↗
  I find that "vibe coders" (that is, people who do not know anything about programming, but nevertheless produce useful tools for themselves and others) are using a lot more tokens than we do as programmers.
  I think this is partially because we're still attached to pre-LLM notions of architecture, good design and code quality (which are still important, but maybe less important than they once were and that we think they are), partially because their projects are in a messy state, so models have to work around the technical dept.
  They're essentially trading off programmer time for LLM time (which is a good trade financially speaking).
  1. gobdovan · 1790631917 · focus · HN ↗
    I think this is valid now, but not guaranteed to be valid forever. For engineers, there was a period where more checks, more tests, more auto code reviews improved results quite a bit. People were consuming tokens like crazy (including me). Then things improved via better effort/thinking levels, where you could see repeated code reviews plateaued, so now people don't really do that quite as much.
    There was also a period where specifically OpenAI models would always have to comment something in code review and the builders were agreeable up to listening to each nitpick. If you'd have a loop of build->review->build->review, it would take maybe 5-7 rounds for it to 'settle' and not find the smallest nitpicks to argue about. Tried it this week with Astra reviewer and it's about 0-2 review loops (never had a LLM accept a change without nitpicking first try before Astra).
    There was also a period where you'd have to give quite specific instructions for agents to keep iterating, but now agent are pretty proactive and try to finish tasks you give them unsurprisingly most of the time.
    So, while there's a shortcoming of LLM+harness and engineers observe more tokens improve things even logarithmicly, you'll see more tokens seemingly abused by engineers.
    wahnfrieden · 1790647809 · focus · HN ↗
    I’m seeing hundreds of review loops before settling, with Astra/Sol
    gchamonlive · 1790680655 · focus · HN ↗
    Could come down to the different nature of the work you guys do.
    senderista · 1790648051 · focus · HN ↗
    Astra is less nitpicky IME than Fable.
    djmips · 1790649468 · focus · HN ↗
    > you'd have a loop of build->review->build->review, it would take maybe 5-7 rounds for it to 'settle' and not find the smallest nitpicks to argue about.
    You sure that wasn't just working at Microsoft?
  2. bensyverson · 1790638832 · focus · HN ↗
    If you have well-specified tasks, you can easily reach 10 simultaneous agents working on disjoint parts of the code in worktrees. That consumes tokens pretty quickly!
    thunky · 1790640422 · focus · HN ↗
    Are they also telling each other what to do? Because I for one can't assign and keep track of 10 things at once.
    bensyverson · 1790640766 · focus · HN ↗
    I create large hierarchical plans, and have a coordinator agent divvy up the work. It's extremely effective.
    nsonha · 1790647203 · focus · HN ↗
    I created an orchestration skill for myself (using herdr but any persistent mechanism works). So I then only interact with a front session and it will triage and dispatch each request to the relevant spaces (each of them can have multiple worktrees of the same project), summarize movements and pending decisions for me all at once. I do not directly interact with a multiplexer or any dashboard.
    thunky · 1790693838 · focus · HN ↗
    This seems complex and expensive, and I suppose the only reason to do this is because you want to generate code faster? Do you really have so much code to write that a single LLM is too slow?
    nsonha · 1790696702 · focus · HN ↗
    I don't do this at my day job (coworkers would be pretty mad). This is for software ideas that comes up weekly that I need to execute to at least MVP before I ever need branching/merging.
    Not complex at all, only one extra session other than the ones doing work and it's on a dumb model and can be thrown away & restarted because it only dispatches work, not doing anything.
    I do everything in there, collecting requirements, kick off research, branching, merging, not one other agent on top. I considered making that orchestration command llm-powered but it's not justified at my current use.
    It's not more expensive, in fact I could have just chugged along with the slow and manual session by session work but I have a claude subscription and another GLM one (the most low cost basic tier, not even much), that just sit there collecting dust if I don't put them to use in a more efficient way.
    And doing session by session would face your problem when context switching too much become unscalable.
    daemonologist · 1790644503 · focus · HN ↗
    Personally, it takes me longer to write the specifications than it takes the model to implement them (and it takes me much longer to review the resulting code, although maybe that makes me old-fashioned). Consequently I do not have enough tasks to run more than one agent at a time.
    stymaar · 1790661194 · focus · HN ↗
    I'm exactly in this situation, and at the same time I get so many jumpscares when reviewing the code that I'm not going to stop anytime soon.
    gbalduzzi · 1790662464 · focus · HN ↗
    Exactly. I don't understand how so many developers seem to have a long tail of well written task specifications ready to submit to the LLM. Who produces them?
    8n4vidtmkvmk · 1790664227 · focus · HN ↗
    LLMs are good at cleaning up tech debt. Give them lots of small refactorings or dig out those crusty old P4 tickets. There's a lot of easy stuff for them that requires very little specification and very high probability they'll get it right the first time, especially if you can point them at an example done right.
    lobocinza · 1790683993 · focus · HN ↗
    [delayed]
    bensyverson · 1790686016 · focus · HN ↗
    I have conversations with a smart model, and then the model writes the spec. I review and approve the spec, and it dispatches.
    For a concrete example, check out this random plan [0]. A detailed spec followed by the exact implementation tasks that will be executed by the subagents.
    [0]: <a href="https://github.com/bensyverson/woodcase/blob/main/project/2026-09-07-scripting-host.md" rel="nofollow">https://github.com/bensyverson/woodcase/blob/main/project/20...
    bensyverson · 1790686884 · focus · HN ↗
    Not sure why I'm being downvoted for stating the obvious. To the parallel agent skeptics: I was also a skeptic until a month or two ago. I would run one agent, watch it carefully, and check its work. However the models got good enough that it was more efficient to do more work in parallel, then have a single agent integrate the changes with a critical eye, then run a code quality pass, and then I would take a look a it and kick the tires behaviorally.
    It does involve letting go and not micromanaging every code convention and implementation detail, but that is the same skill you need when leading engineering teams.
  3. satvikpendem · 1790639629 · focus · HN ↗
    LLMs these days write better architected and produced code than most programmers, so the fallacy that LLMs produce slop code is increasingly false.
    drewnick · 1790642252 · focus · HN ↗
    Every new generation of model goes and cleans up the slop of its predecessor in my code bases, and it has turned out to be quite effective.
    Last year I held off on implementing a few features knowing that a model like Opus 5.5 was around the corner. I'm now implementing them in a much more efficient and quality manner than I could have fall of 2025.
    satvikpendem · 1790662670 · focus · HN ↗
    Indeed. Maybe people down voting me don't like to admit it but when models train on the entirety of human input you can assume they'd be better than the average human.
    Tanjreeve · 1790672504 · focus · HN ↗
    This is probably why web development and scripts are much more effective domains while anyone working on anything even slightly off the track is either tearing their hair out or writing a new layer of software to write the software.
  4. furyofantares · 1790640514 · focus · HN ↗
    [delayed]
  5. meowface · 1790641383 · focus · HN ↗
    I am actually going to go out on a limb and guess the opposite of this is true, and that on average vibe coders burn tokens less readily than veteran software engineers. I could list several reasons why I think this would be likely. No idea which of us is empirically right, though.
    vineyardmike · 1790644193 · focus · HN ↗
    I’d think this matches my hypothesis. I’d say that I spend more tokens rewriting and fixing things, so that contributes more.
    Also, I’d imagine the token-maxed user is a programmer that lives in chat. I’ll admit to having asked the LLM to move a method up/down in a file, and watched it burn tokens for a minute thinking and executing a menial task.
    meowface · 1790645052 · focus · HN ↗
    Same. I spend tokens on so much more than just the initial implementation of a feature I have an idea for.
    gbalduzzi · 1790662570 · focus · HN ↗
    This I don't understand. I'm faster at moving the method then at prompting the LLM to do so
    vineyardmike · 1790667180 · focus · HN ↗
    Sometimes I don’t have the text editor/IDE open, and I’m just looking at the code in a PR or similar UI.
    pmg101 · 1790677394 · focus · HN ↗
    "Sometimes"? I and I think many other people have been doing exactly this for most of 2026, assuming they look at the diff/PR at all and aren't all-in on dark factories.
    hasbot · 1790670042 · focus · HN ↗
    Sure, if it's right there in front of you in the editor. But if have to locate the file and the location within the file, it's easier to just type out what I want and have the LLM do it.
    avadodin · 1790672855 · focus · HN ↗
    I would be faster than Claude or Gemma if I did it.
    That's a big if though and the blank page syndrome was already getting worse long before AI.
    With age, it becomes easier and easier to get angry at someone or something until they work as expected than it is to actually do it.
    I think this is why we've been seeing the genius coders from two generations ago embracing vibe coding even before it was cool or any good.
    VMG · 1790677554 · focus · HN ↗
    LLMs are sometimes stupid and get confused when you change the files without them knowing. So asking them to do even simple things keeps the context in sync.
    Plus you get a bonus random line "methods are all on the top" in the commit message that makes no sense to anybody.
  6. tikhonj · 1790645247 · focus · HN ↗
    I mean, they're trading off the time to learn to program for LLM time. Which might make sense! Locally.
    But, in my experience, the projects where I have a constant pulse on the core design and abstractions in the code end up moving much faster than the ones where I don't. And I've been working on one of each at work recently, so I have a decent point of comparison.
  7. FpUser · 1790645324 · focus · HN ↗
    >"but maybe less important than they once were"
    On browser based front ends it seems to be the case for me even though I still impose certain guidelines. On my C++ backends, no fucking way. Even the best models produce working but absolutely disastrous non scalable (performance wise and design wise) code unless watched over like a hen. Having said that - the value I get in either case is enormous.
  8. gchamonlive · 1790645677 · focus · HN ↗
    I think it's not only a matter of token efficiency. If you don't know what you are doing development will eventually crawl to a halt invariably.
    It's the compound counter-probability of success, so even a 99% efficient model will in time accumulate so much error that without conscious cleanup and steering, it becomes really unlikely really fast that anything could be changed in the code without affecting something else, no matter how many tokens you throw at it. It's the collapse of a complex system under the weight of sheer uncertainty of what the system actually does.
    xbmcuser · 1790647313 · focus · HN ↗
    The llm are improving though maybe a year from now they can use it to fix the code
    gchamonlive · 1790647968 · focus · HN ↗
    Maybe, it'll be exciting to see, and I'm all about accessibility, but in this case I also don't think it's about model capability or intelligence, it's the low rate of information to noise ratio in the codebase. There won't be enough information in the code itself to know what to fix. Fix how? What should it do? I'm really not sure you can reconstruct intention from a codebase created unsupervised.
    noisy_boy · 1790655956 · focus · HN ↗
    1. Implement feature and write tests for the code
    2. Make sure tests pass
    3. <Every now and then> Review code for quality and fix - make sure tests pass.
    4. Go to #1
    Overly simplistic? Yes. But I would wager that this can go a long way, even for vibe coders.
    gbalduzzi · 1790662214 · focus · HN ↗
    I keep seeing this but I'm not sure it is effective in the long run *if unsupervised*.
    "Review quality and fix" doesn't mean a lot without context.
    Does it mean to remove unused features and simplify the underlaying code? Does it mean changing the data structures to better support future development? Does it mean improving performance because of bottlenecks?
    You are supposed to tell an LLM what your codebase needs, but if you just vibe code without knowing the code, "review quality and fix" will have unexpected results
    gchamonlive · 1790679932 · focus · HN ↗
    [delayed]
    alexytsu · 1790661511 · focus · HN ↗
    Commit the intention as specs. If tokens/intelligence become that much cheaper over time, then "throwing away the code" to start again becomes feasible.
    gchamonlive · 1790679695 · focus · HN ↗
    [delayed]
    flir · 1790681614 · focus · HN ↗
    A few days ago somebody linked to their own project: <a href="https://ljtn.github.io/epiq/" rel="nofollow">https://ljtn.github.io/epiq/
    I haven't had time to dive into it yet, but I think it might structure things in the way you want.
    gchamonlive · 1790682372 · focus · HN ↗
    [delayed]
    internet2000 · 1790651576 · focus · HN ↗
    Can confirm, I'm currently using Opus 5.5 to fix some Opus 4.5 slop from around this time last year.
    neya · 1790652012 · focus · HN ↗
    Fixing code is not the same as fixing a fundamentally broken architecture. The latter requires understanding that the architecture is broken in the first place and that understanding comes from experience.
    gchamonlive · 1790680090 · focus · HN ↗
    [delayed]
    baq · 1790661994 · focus · HN ↗
    We’re at 99% for a lot of stuff today, you get a third nine from council reviews and labs have another one or two nines in the pipeline. At five nines your task length horizon extends far beyond the current frontier model release cadence. More out of distribution tasks lose a nine or two, still revolutionary.
  9. spicyusername · 1790646809 · focus · HN ↗
    Plenty of vibe coders who know a lot about programming producing useful tools and using tokens too.
    drusepth · 1790657660 · focus · HN ↗
    Indeed, I've been coding for ~25 years (competitively and in open source for many of them) and I max out at least two subscriptions' worth of tokens every week across a half dozen active projects.
    I still code "by hand" sometimes (mostly Ruby/Rails, C#, and random languages for code golf) but just for fun at this point. Serious projects started being 95-100% AI over a year ago.
    taliesinb · 1790658966 · focus · HN ↗
    What are your half dozen active projects? And did AI use make you more ambitious about what those projects could be?
  10. drbojingle · 1790649607 · focus · HN ↗
    That and some have bridged the gap with tooling. starter projects+ Strick typing + dead code detection, linting rules and today's models can get you pretty far, especially if you plan out some basic architectural patterns with your starter kit.
    It's not perfect but any means but it helps manage ones sanity.
  11. inopinatus · 1790655862 · focus · HN ↗
    It's because they don't know data structures.
    "Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won’t usually need your flowcharts; they’ll be obvious." - Fred Brooks, The Mythical Man-Month (1975).
    and essentially the same sentiment, three decades later:
    "Bad programmers worry about the code. Good programmers worry about data structures and their relationships." - Linus Torvalds, git mailing list, 2006.
    These things have not changed even though everything else is topsy-turvy. As-of current writing, I have yet to see an LLM make good data structure choices; they go for something that is superficially plausible but profoundly ill-considered (or rather, not considered at all), and then commonly burn tokens treating this implementation detail as a design invariant and trying to deal with the consequences by writing more code, instead of iterating directly upon the ill-fitting data at the root its problems.
    If you're wondering, "does he mean the schema of let's say a db or other persistent store, or does he mean abstract/algebraic structures", the answer is yes to both, I think coding models are today shockingly weak when it comes to design reasoning in both domains.
    Fortunately, their suggestibility means the same models will readily accept direction on the matter (perhaps even more so than on the structure of code), so I recommend doing just that, and (bonus!) this means your CS degree is still relevant.
    avmich · 1790660046 · focus · HN ↗
    Watch LLM start paying attention to data structures.
    inopinatus · 1790660992 · focus · HN ↗
    [delayed]
    hathawsh · 1790664289 · focus · HN ↗
    While I agree that a coding model (such as Opus) by itself tends to act very shallowly, when it's driven by a harness like Claude Code, the combination seems to be a far more general thing than a LLM. It's capable of consistently making excellent data structure and architectural choices over large code bases. It imitates thinking about anything and it can drive itself for hours.
    Honestly, if I simply fed it a sense of presence (I would repeatedly tell it what's going on right now and ask it to react if it thinks it should), it would feel eerily like AGI.
    logicchains · 1790665276 · focus · HN ↗
    Coding models can already make well-considered data structure choices if given all the relevant context, but a non-programmer doesn't know the context to give it.
    stymaar · 1790661044 · focus · HN ↗
    It's not going to happen naturally, the labs first need to implement a reinforcement learning pipeline that promotes it.
    potbelly83 · 1790688595 · focus · HN ↗
    Falling back on a RL pipeline to cover gaps always strikes me as a more sophisticated version of the mechanical turk. If what we had was truly AGI wouldn't they be able to derive this from the data they already have.
    sdeframond · 1790697821 · focus · HN ↗
    Why would we care wether something truly is AGI or not?
    It is useful. It may be dangerous. It has an impact. I care about that.
    jappgar · 1790680733 · focus · HN ↗
    If you frame the conversation in those terms, they will.
    One of the problems is that by default, they'll avoid changing data structures or architecture that is already written down.
    Like a junior dev, they're correctly cautious about breaking things, so they prefer to write more code instead.
    sdeframond · 1790697559 · focus · HN ↗
    > If you frame the conversation in those terms, they will.
    Indeed I realized recently that, when we complain about LLMs producing slop, that's in part because we dont ask them to refactor.
    Coding agents won't, on their own, make a big change the user did not ask for. And this is fine.
    [deleted] · 1790684684 · focus · HN ↗
    [deleted]
  12. alkonaut · 1790673359 · focus · HN ↗
    I (a programmer) just did a pretty large task with Opus 5.5 that was a perfect fit for a big token eating task. It ate into my weekly budget in a way that made me have to use anthropics one-off "reset" they offer now.
    Long story: we have a big legacy desktop app. It uses a big legacy UI component (a grid control), which we had a license for in an old version. Fast forward 20 years, and to be able to move to a new runtime for our app, we need to update the component. Someone had bought the company making the component and now charges north of $1k per developer per year. So instead of doing this, we had just lived with the very old version.
    We had long thought of writing our own control to replace the proprietary, but it was always going to be a man-year of work we thought. But I thought I'd give it a try with AI now. I told Opus: look at our uses of that control (tens of thousands of lines of code, it has over 100 instances across our User Interface). Write a new control that would compile with the exact same app syntax. First just make a dummy implementation that throws on every call. Then start implementing.
    Make a test suite that can run both with our new control and the proprietary control, and test everything, every function that can be called in its public interface and every state that can be inspected from the public API. Verify that everything behaves exactly the same, and lock it in with thousands of tests. Finally, check that the control _looks_ exactly the same as the proprietary one. Render to bitmaps, figure out the rendering logic from observation, such as arithmetic for padding, font sizes, and so on. Compare pixels until it's exactly the same.
    Basically: it was a mammoth coding task, but it was so extremely well specified that an LLM could easily just do it. It's a clean-room implementation of something with no tests, but we had a test double that could provide 100% of the expected behavior. The description was extremely short. "Make a new thing that works like the old thing, and prove that it does". Opus 5.5 finished this in a number of hours. 500 source files, several thousand unit tests, and html reports with image diffs from the reimplementation and the original control. It did not use any disassembly or such "cheating". Only observation of the public API and the behavior. Do we need to deeply understand the implementation? Does the architecture matter? Not much in this case I'd argue. It was a black box to begin with and it remains a black box. If we notice a bug, we can always point it to the original proprietary control and say "there's a behavioral difference when doing X" and it will fix it, and lock it down with tests.
    As a programmer it's kind of chilling. I had recreated for a few $10's of dollars something that would cost $1000 per year to buy. Obviously it's not a complete implementation only the parts of the API we use. It likely still has some bugs. We don't get support, we get to maintain it ourselves. But the rate of reverse engineering this thing "black box" was frightening. It hasn't created anything novel. But we must realize that as programmers some times we have man-years of work that just isn't novel. And in the past, we didn't do this work at all.
    I wonder if those who write and sell libraries like this will start having explicit no-reverse-engineering EULAs soon? Perhaps even explicitly mentioning AI/LLM use in analysis and reimplementation?_ Obviously the library we reimplemented was from 2005 so didn't mention AI... (It doesn't mention reverse-engineering either, luckily).
    Pannoniae · 1790678688 · focus · HN ↗
    Most products do in fact have an anti-reverse engineering clause in their EULA, to be fair. It's just that no one cares anymore...
    alkonaut · 1790683198 · focus · HN ↗
    Yes, and usually in the form "You may not reverse engineer, decompile, or disassemble the SOFTWARE or any of its constituents, except and only to the extent that applicable law expressly permits". (This is the concrete example from this software). And as far as I understand, this means that so long as you stay short of decompilation - you can reimplement as much as you want.
    The law that covers this (in the EU) is EU Directive 2009/24/EC, where Article 5 is the reverse-engineering-without-decompilation.
    > The person having a right to use a copy of a computer program shall be entitled, without the authorisation of the rightholder, to observe, study or test the functioning of the program in order to determine the ideas and principles which underlie any element of the program if he does so while performing any of the acts of loading, displaying, running, transmitting or storing the program which he is entitled to do.
    This is pretty difficult to parse, but luckily there is a ruling from the European Court of Justice on this: SAS Institute Inc. v World Programming Ltd (Case C-406/10), delivered on May 2, 2012.
    SAS Institute claimed that World Programming Ltd (WPL) infringed its copyright by studying the behavior of the SAS software system and writing a competing program (the World Programming System) that emulated its exact functionality and used the same data file formats. WPL did not have access to SAS's source code and did not copy any of its literal text or internal structural design.
    CJEU:
    > "It must therefore be held that the copyright in a computer program cannot be infringed where, as in the present case, the lawful acquirer of the license did not have access to the source code of the computer program to which that license relates, but merely studied, observed and tested that program in order to reproduce its functionality in a second program".
    Which is a good find. But this is where I wonder if LLM-based reverse engineering is going to creep into either law (via lobbying) and/or EULA's, because this "observe every single state of the program for every single mutation" was simply not a viable mode of reverse engineering in the past. Or, it was at least always cheaper than just buying the software! Not so any more.
    Or alternatively, that programs stop having so many observable states, making more things public. But for libraries as in this case, the whole product IS the public API. Without a rich public API, the library can't be sold. And with it, I can observe it and copy it - because it's internal workings are "too simple" not to be deduced from the public API. In short: a UI control is a ton of hard-to-write but easy to copy boilerplate code. And selling this has been an industry, but I wonder if it will be for very long.
    Pannoniae · 1790691804 · focus · HN ↗
    "And as far as I understand, this means that so long as you stay short of decompilation - you can reimplement as much as you want."
    Yes, but my point is that.... go on github, you'll find tons of decomps. And many more done just privately too. One of the No Man's Sky devtalks start with "yeah we decompiled the terrain generation from this other game, implemented it in our prototype, it didn't work okay, here's how we've learnt from it to make something better". This was in 2016. More recently, this has been going on way more openly, even full AI-assisted decomps thrown up onto GitHub casually. It might be the letter of law or included in Terms of Service but no one cares really.
  13. seanhunter · 1790673665 · focus · HN ↗
    I’ve noticed some people re-prompt big tasks from scratch rather than iterating. This burns tokens very fast.
  14. onevsall · 1790676232 · focus · HN ↗
    Architecture is essential for anything complex. With bad architecture, complexity quickly outruns any model.
  15. arceister · 1790679911 · focus · HN ↗
    Because that "vibe coders" didn't know and go through the fundamentals, thus they're wasting tokens with probably continuing the AI hallucination suggestions.
    I've seen bunch of persons like this and that's kinda stupid because they're just blindly following AI's "suggestions" while they actually don't know what they're doing, then results on terrible code and architecture with "if it works, it works" mentality.
  16. erida_counter2 · 1790683435 · focus · HN ↗
    [dead]
17. mgaunard · 1790633260 · focus · HN ↗
  I find that I can do 4 to 7 sessions in parallel, and still review everything in depth and co-design.
  I mostly use Fable though, Opus only via sub-agents.
18. jtrn · 1790634956 · focus · HN ↗
  Subagents.
19. eptcyka · 1790635444 · focus · HN ↗
  Try telling an agent to go through your backlog.
20. smb06 · 1790638373 · focus · HN ↗
  I expect they’ll change usage limits in some of the plans or introduce new plans with new limits
21. jcrben · 1790638798 · focus · HN ↗
  Does that mean you're doing work week by week that is well-scoped and planned for that week and you can't pick up the work for next week until that week happens? It just seems like mostly programmers work on things that extend out for a long time and you can kind of just throw more at the problem and pull it forward earlier
22. mrbonner · 1790643632 · focus · HN ↗
  I have been using the “free” Ling Flash model on openrouter for a bit over a month now. My work is an aside project at home building a Rust binding for an open source Zig code base library. The result is nothing impressive but also not a total failure: I have a feature parity binding to use in Rust vs. Python/java/typescript.
  Now, during those night and weekend sessions, I have never run into throttling issues with the free model. Sometimes it runs a bit slow and I switch to a different free model (NVIDIA Nemo something).
  So yeah, I agree with you that for professional SDE like us, we don’t consume that much tokens. I’m pretty sure the folks on the line of over limit are pure vibe coders if I can take a wild guess.
23. Wowfunhappy · 1790647158 · focus · HN ↗
  You clearly aren't using subagents!
24. raincole · 1790648033 · focus · HN ↗
  If I follow the principle "every single line of AI-generated code has to be reviewed and understood by me," I literally can't use up the $20 Claude subscription. I tried quite hard but only managed to do it once.
  1. selcuka · 1790655759 · focus · HN ↗
    I do that and can use up the $20 subscription, but I haven't been able to hit the limits with the 5x subscription so far (even though I use Fable for making plans).
25. czhu12 · 1790650979 · focus · HN ↗
  The other thing too is that I’m having a hard time reviewing these massive PRs that are being generated. So much so that I’m having it write me a book (also vibe coded) that I can read through to learn about all the stuff it did as part of the pr review <a href="https://ai-lessons.oncanine.run/" rel="nofollow">https://ai-lessons.oncanine.run/
  1. AloysB · 1790651591 · focus · HN ↗
    Sometimes I feel like I leave in a different universe.
    You find it too hard to review code that the LLM generated. Instead, you use the LLM to generate a book instead of reviewing the code.
    What is there for you in this? Why not generate smaller PRs? Read the actual documentation of the technologies you are using ? Reading software engineering books for the bigger picture?
    Genuine questions.
    It's so far from my version of software engineering that I'm really perplexed by this workflow.
26. hamburglar · 1790660970 · focus · HN ↗
  This is boat I’m in too. I get a ton out if my pro subscription, and I don’t hit the limits, but my Microsoft buddy was just griping about how the company recently imposed $10000/month token budgets on his team and he blew through his quota on under a day. The mind boggles.
27. bossyTeacher · 1790662778 · focus · HN ↗
  > Probably a first world problem, but with Opus 5.5's efficiency, the limits on the 5x plan are simply sufficient for my everyday work, even when running 2-3 sessions at a time. So I wonder when I would use Sonnet 5.5.
  Not every user of Claude is a programmer. Or even exclusively a worker. Claude has uses beyond work. Something that many in HN struggle to understand.
28. y42 · 1790665218 · focus · HN ↗
  When working with a whole bunch of sub-agents, like you probably would do when coding, 2-3 sessions at a time are probably not enough. Like I build very specific sub-agents for code review, ui review and so on. Within one project I work with at least 3 - 4 agents then. Using Opus on every task would not leave room for other everyday-tasks.
29. konsnos · 1790666352 · focus · HN ↗
  Sometimes it's not about token usage but speed of the task.
  I am using Sonnet 5.0 in browser (btw Claude in Chrome extension works in Edge) to download Datadog logs with multiple filters. It's running for about an hour, doesn't run out of tokens and does a splendid job.
30. cft · 1790671760 · focus · HN ↗
  I ran out of Opus 5.5 20x plan in 4 days out of 7, so my experience is different from yours.
31. eonmatrix · 1790673115 · focus · HN ↗
  I'd use it for some of the lesser roles in oh-my-pi (omp) like commits.
32. richardw · 1790673486 · focus · HN ↗
  [delayed]
33. randerson · 1790674795 · focus · HN ↗
  While I mostly use Opus for coding, I use Sonnet in my actual application, because it is far cheaper at scale. I have Sonnet parse user free-text input, understand it and return the meaning as structured json. It doesn't need advanced reasoning, just a good enough understanding.
34. swalsh · 1790680742 · focus · HN ↗
  If you ever had claude code fan out a task to sub agents it will often use sonnet or haiku for those tasks. Web scraping is an example.
35. ohyes · 1790684989 · focus · HN ↗
  I honestly rarely use the “more powerful” models, I find they don’t really follow my instructions very well. So it’s medium effort sonnet for most coding tasks for me, escalating to opus for code review.
  I’m just hoping they didn’t “improve” sonnet too much or it will become annoying to wrestle into doing what I ask it to do.
36. pjjpo · 1790687186 · focus · HN ↗
  Smart people delegate to dumb people. Of course ideally dumb people get slightly smarter. From my experience sonnet is mostly for opus or fable to delegate to. So delegates getting more useful is always a good thing.
  Seeing 2000 years of history being replayed by the AI startups is pretty weird right?
  1. busssard · 1790688111 · focus · HN ↗
    that.
    also i find it interesting how the capabilities are growing. first speech, then code, then simple tools, then 3d objects, then desktop use
37. busssard · 1790687874 · focus · HN ↗
  for very extensive agent swarms, you could tell the orchestrator to use sonnet agents for the eval of papers. this way you can digest much more papers (content of whatever form)
  so whenever you are dealing with volume rather than independence. opus5.5 can define the goals of a sonnet well enough, that i would trust it with a group of 100s of agents
38. dionian · 1790704799 · focus · HN ↗
  Subagents
rtuin · 1790619249 · focus · HN ↗
Any benchmarks other than computer use/agentic coding published yet? Curious to compare more broadly with other models
avree · 1790619259 · focus · HN ↗
Crazy bad front-end design. Site hijacks my gestures so I can't swipe back anymore, starts with a full page autoplaying video...
1. iAMkenough · 1790627293 · focus · HN ↗
  Agreed. I’ve found that Anthropic [dot] com at least honors “reduce motion” accessibility settings, and that makes their site a bit more useable.
onlyrealcuzzo · 1790619272 · focus · HN ↗
> In our testing, it costs up to 30% less per task than its predecessor.
> Sonnet 5.5 generates outputs 30%+ faster than Sonnet 5, making it our fastest Sonnet model to date.
This isn't enough. Sonnet 5 was arguably the most cost ineffective model ever released at the time of a release.
They need something competitive on speed and cost with Luna or Gemini Flash 3.8 (certainly they aren't getting to DeepSeek v4.1 Flash) - this is literally a year behind.
Anthropic continues to be a Fable/Opus only company. They're going to get left behind as workloads shift more and more to more cost-effective good-enough models. They're 10-100x behind in terms of speed and cost.
I've almost exclusively been using Anthropic for design and review, as it almost never makes sense to use any of their models for implementation (90%+ token usage) - except in the rare cases it's something too complex for a number of 10-100x cheaper models (and more importantly for me 5-10x faster, too).
For me, it's less about cost. I'm not doing anything that can't be done with a $200 subscription and minimal intelligence on what models to use. It's primarily about speed. I don't have an entire work day to give Opus / Sonnet a task that Flash can get done 95% as good in 30m.
This is YET AGAIN another Sonnet model that is just a FAR worse version of Opus at every part of the cost AND speed curve.
Hopefully they release a Haiku that actually has a reason for existing.
1. criemen · 1790619459 · focus · HN ↗
  The latest Haiku release is almost a year old. Clearly they don't care about the small-but-capable part of the market at all.
  1. enraged_camel · 1790620691 · focus · HN ↗
    From TFA:
    >> Claude Haiku 5.5, built for high-volume and cost-sensitive applications, will join the Claude 5.5 family in the coming weeks.
    aniceperson · 1790622958 · focus · HN ↗
    This will be interesting. While no one cared about small models in the last few months except for the OSS community, there is a silent small model revolution with gpt luna and jev. Headless/background llm routines are cost-feasible, which will of course lead to exponential usage and cost.
    My take on anthropic is that haiku 5.5 has been shelfed for a while since it is predatory against sonnet (see terra 5.6 usage), but openai went kamikaze and they are now forced to release.
    Nevertheless, the elephant in the room has grown: will any of the Labs be able to profit if mass adoption lies in the highly crowded small model territory?
    <a href="https://openrouter.ai/blog/insights/gpt-5-6-discounts-jevons-paradox/" rel="nofollow">https://openrouter.ai/blog/insights/gpt-5-6-discounts-jevons...
    criemen · 1790624173 · focus · HN ↗
    > but openai went kamikaze
    I don't quite understand your point here. OpenAI has a consistent history of releasing cheap/small models - first nano/mini, then luna/terra. Of course, those are now more capable than half a year ago, but I don't see a behavior change from OpenAI here.
    aniceperson · 1790624946 · focus · HN ↗
    Of course, my opinion is based on my personal experience + openrouter data that shows stickiness and low terra adoption; with openai confirming by making sol terra, astra sol.
    I honestly never saw anyone doing /model gpt mini. I think those models were mostly used for copilot-like products, like those pull request reviews with untasteful dumbness to it (idiotic CodeQL finding -> LLM vomits a "fix" instead of assessing). While Luna seems to be the first model that you can trust to reason in the background, and this is predatory to their own more expensive model.
2. jchw · 1790619502 · focus · HN ↗
  I always tell coworkers if they're gonna use Claude to just stick to only Opus and Fable. Sonnet is a waste of time that does a bad job at a bad price.
  DeepSeek V4.1 Flash may be chatty but it's cheap, fast, and reliable. I'm not sure what the upside of Sonnet is supposed to be. Right now it feels like a trap.
  1. eli · 1790619657 · focus · HN ↗
    Hopefully some faster providers will start offering mimo-v2.6-pro because it's cheaper and benchmarks better than Deepseek
    jchw · 1790619927 · focus · HN ↗
    Theoretically but I've used DeepSeek V4.1 Flash for several hundred millions of tokens already and it chews through tokens but it is surprisingly good at making it to the end.
    MiMo V2.6 Pro I want to love, but I've hit three deathloops in a row. Either my luck is catastrophically bad, or someone needs to patch vLLM or something.
    I am sure DeepSeek V4.1 Flash can deathloop, too, but so far it feels less prone to it than other models I've tried like GLM 5.3 so, I'm impressed so far.
    I always wonder what the deal with these failure modes are. Google, OpenAI and Anthropic seem to have found good enough workarounds, and I am surprised I don't hear more people talking about them. I thought maybe it was shitty broken providers on OpenRouter, but then I started making presets just for using only the upstream provider and found that no, really, the models do fail that way.
    Which is a shame because on paper MiMo V2.6 Pro seems strong, but I haven't gotten through a hard task with it yet.
    eli · 1790620523 · focus · HN ↗
    I read they identified a training bug and were going to push out an updated release to fix the looping. I really like it overall.
    GLM 5.3 Flash is also very good. I think a little smarter and a little more expensive.
    jchw · 1790631349 · focus · HN ↗
    I did like GLM 5.3 Flash but it's just way too often I'd run it on some long running task and come back to it repeating the same tokens or tool calls endlessly, just doing nothing. It wasn't unusable, but I couldn't trust it. That's really frustrating and I think new models have to do better not just on benchmark scores but general reliability and user experience as well.
    At some point Anthropic and OpenAI models definitely could fall into similar traps so I do think it is a solvable problem and likely not a reflection of the models themselves being bad. In this case it may indeed be a training bug of some kind, but I also suspect mitigations on the inference side are possibly lacking or not effective enough for the open models and their runtimes.
  2. velcrovan · 1790619797 · focus · HN ↗
    Sure, but the fact that Opus 5.5 was such a huge leap over Opus 5 (and Fable 5.1 for that matter) means that it's worth revisiting your priors on a new Sonnet.
3. cbg0 · 1790621472 · focus · HN ↗
  > This is YET AGAIN another Sonnet model that is just a FAR worse version of Opus at every part of the cost AND speed curve.
  It's been out for an hour and you've already concluded this?
4. fluidcruft · 1790635800 · focus · HN ↗
  Would Jev-type functionality be a reason to dust off Haiku?
wkcheng · 1790619321 · focus · HN ↗
The cost / performance chart shows that in almost all configurations, it looks worse than Opus. Why would you use Sonnet 5.5 on xhigh if you would get better results (higher score, cheaper cost) on Opus 5.5 high?
Is there a good use case? This isn't like Luna where it's much cheaper/effective just to use Luna in certain situations.
1. quatotor · 1790619692 · focus · HN ↗
  [dead]
2. SubiculumCode · 1790619980 · focus · HN ↗
  t/s maybe? IDK, because their token speed comparison was against Sonnet 5.
3. ricardobeat · 1790620217 · focus · HN ↗
  At low and medium effort it is 1/3 cheaper, at high it’s a step above Opus/low. It only looks worse at xhigh.
  1. wkcheng · 1790620530 · focus · HN ↗
    That makes sense. I'm interested in seeing where Haiku 5.5 comes in then when it gets released. It feels like the low intelligence / fast niche will be covered there.
    oh_no · 1790621816 · focus · HN ↗
    i'd love to see them re-enter that space but given haiku 5 never happened I wouldn't bet on it
    i think they see what openai charges for luna and just don't want to try and compete
    canad3nse · 1790623076 · focus · HN ↗
    But they literally stated that they would release Sonnet 5.5 and Haiku 5.5 after Opus 5.5 would be released
    ac29 · 1790627270 · focus · HN ↗
    Haiku 5.5 is DOA without a massive price cut. Luna is literally 10x cheaper at current pricing
    enraged_camel · 1790628042 · focus · HN ↗
    It depends entirely on its capabilities. If it is significantly smarter than Luna, which frankly is quite likely, then a lot of people won't mind paying more.
    conception · 1790636355 · focus · HN ↗
    Or if its luna at 1000 tok/sec. Speed is what most of my peers care most about these days since less intelligent models can do most grunt work just fine.
    mchusma · 1790642472 · focus · HN ↗
    My guess is that haiku will be a mid release. They don’t seem to care to compete for the low end. Something akin to gpt6 sol level intelligence at $1 / $5 pricing. Then not release an update for 6+ months.
    pdantix · 1790623297 · focus · HN ↗
    they've already said in both the opus 5.5 and sonnet 5.5 blog posts that haiku 5.5 is coming
    water-drummer · 1790623511 · focus · HN ↗
    They did mention in the Opus 5.5 announcement blogpost that Sonnet and Haiku 5.5 will follow soon.
4. solenoid0937 · 1790620266 · focus · HN ↗
  It literally does not?
5. RussianCow · 1790620289 · focus · HN ↗
  It appears, at least from a quick look, to be noticeably faster than Opus. If true, and you don't need xhigh/max reasoning for your use case (like a well-defined set of code changes), Sonnet might get the job done much more quickly.
  With that said, at that point, I'd probably use something like DeepSeek V4.1 Flash, which is way faster and significantly cheaper, and probably not noticeably dumber for most use cases.
6. delillos · 1790620302 · focus · HN ↗
  There's a sort of magical thinking needed to answer a question like that. You might say it comes down to "feel" of the model; i.e., the indefinable differences in the way that they speak to the user and approach problem solving. Perhaps Opus is suited for tasks that tackle new ground, while Sonnet might be better at tasks that are more grounded in the code.
  Ultimately it's slightly ridiculous to define model capability on a single axis. It's like a standardized test. Sure, you can line people up by their ACT score, but that doesn't mean a doctor and a brilliant artist who both do well on the ACT have an identical intelligence or approach to life. It just can't be captured.
7. usaar333 · 1790620605 · focus · HN ↗
  Per the charts, there is largely no point to using Sonnet 5.5 at high+ as opus low generally will give similar performance at similar or lower cost.
  But Sonnet 5.5 at medium and below gives you a cheaper option at a performance worse than the lowest thinking Opus (low), which may be viable for "low intelligence" use cases.
  1. verdverm · 1790628450 · focus · HN ↗
    at that point, you can switch to dirt cheap open models
    NotSuspicious · 1790641349 · focus · HN ↗
    Only if your company (and government) lets you!
    verdverm · 1790643221 · focus · HN ↗
    yup, we use Fireworks.ai, and American company with ZDR
    Their new Ember-1 model is pretty good, fine-tune of Kimi3 with way less thinking
    Does this make it an American model or is it still Chinese?
8. Jcampuzano2 · 1790620885 · focus · HN ↗
  I'm honestly not sure where they're getting their 30% numbers from at all. In every single chart that they chose to display except for one, it costs similar or more than Sonnet 5, while also being comparable in price to Opus.
  Maybe it's buried within their system card but I think that this would be one of the first things they'd want to show in the announcement article and they fail to do so.
  I really don't know who does Anthropic's marketing but they always seem to a pretty terrible job in their announcements from my perspective.
9. dominotw · 1790621619 · focus · HN ↗
  just shows you how little control of output these labs actually have. They are training two models that kind of ended being the same so whatever they were doing specifically didnt make much difference.
10. benjiro29 · 1790627492 · focus · HN ↗
  The cost / performance chart shows that in almost all configurations, it looks worse than Opus. Why would you use Sonnet 5.5 on xhigh if you would get better results (higher score, cheaper cost) on Opus 5.5 high?
  This screams to be that Sol vs Terra model problem that OpenAI had. On paper half the price, in actual usage the price gap was so close for less good results, that everybody just spammed Sol.
_fw · 1790619399 · focus · HN ↗
I still can’t find a place for Sonnet models, I never have.
I bounce between ”fuck you, give me an AGI-approximate robot god” or ”how dare you charge me more than $0.04/million tokens”.
Give me the frontier, or give me the cheapest form of good enough.
1. calumcl · 1790620490 · focus · HN ↗
  There's even less of a place for it considering the Opus price drop as well, I'll still try it but I see no reason to not just do Opus Low/Med instead.
  Interested to see if new Haiku gets a big price drop and is comparable to Luna, Haiku is just incredibly out of date with current basement bin pricing.
2. EMM_386 · 1790620593 · focus · HN ↗
  If you're on a Claude plan and have a lot of tasks at the moment that don't require the frontier, Sonnet is a good model to do that since you get more usage out of it.
abejora · 1790619457 · focus · HN ↗
Sonnet 5.5 scoring higher (70.6) than Opus 5.5 (66.4) in Terminal-Bench is interesting. I looked into this, because it felt strange.
Turns out that Opus had 10% of its trials answered by a fallback model due to safeguards; versus only 1.5% fallbacks for Sonnet. [1] So I would not read too much into this, just the difference in fall backs could probably explain the gap.
[1] Section 8.5 of the Sonnet 5.5 System Card
1. eli · 1790619561 · focus · HN ↗
  Why isn't that worth reading into? I care about the experience of actually using the model, not hypothetically what it could achieve without overactive guardrails
  1. abejora · 1790619945 · focus · HN ↗
    You're right about its real world performance, and I worded my original comment wrongly.
    I was merely thinking of the theoretical aspect of it: performance of opus 5.5 is better than sonnet 5.5 across the board, with the exception of Terminal-Bench. So I was curious why this one stood out. Was it because they focused on it during training? Did sonnet 5.5 had access to more references for this benchmark? But based on my first reading, I concluded that it might just be the safety constraints that made the difference here, and I wanted to share that.
    joeyhage · 1790622518 · focus · HN ↗
    Claude, is that you?
    bb-connor · 1790629094 · focus · HN ↗
    you're absolutely right to push back
    swiftcoder · 1790625762 · focus · HN ↗
    > You're right about its real world performance, and I worded my original comment wrongly.
    Damn, HN commenters starting to talk in claudisms now
    verdverm · 1790626411 · focus · HN ↗
    this is your brain on drugs...
    this is your brain on claude...
    corporate needs you to find the difference
    ramon156 · 1790626727 · focus · HN ↗
    [delayed]
  2. chis · 1790627161 · focus · HN ↗
    Well presumably now it’ll fall back to Sonnet 5.5 lol
  3. spider-mario · 1790671240 · focus · HN ↗
    You can read “a little bit” (i.e. “not too much”) into it (it does indeed tell you about the out-of-the-box experience), but e.g. being able to know when a fallback model has been used means that in terms of pure accuracy, you might still be better off defaulting to Opus 5.5 and re-routing to Sonnet 5.5 yourself when you get the fallback.
2. MadameMinty · 1790619890 · focus · HN ↗
  That's frankly hilarious. What was the fallback for Opus 5.5? Was it Sonnet 5 or 5.5?
  I suppose it also explains how FrontierCode scores seriously dip at Opus/Xhigh and Sonnet/Max?
  1. manojlds · 1790621203 · focus · HN ↗
    Fallback was usually Opus 4.8
    Aissen · 1790664306 · focus · HN ↗
    Note that it seems that it no longer falls back automatically. So the actual score will be lower (fail vs fallback than can succeed)
3. radlad · 1790619999 · focus · HN ↗
  I believe you meant to cite the Opus 5.5 System Card which states:
  > Claude Opus 5.5 scored 66.36% on Terminal-Bench 4.0 with safeguards enabled; requests flagged by the safeguards were answered by a fallback model following the default server-side fallback policy (2.5% of requests, affecting 10% of trials).
  > <a href="https://www-cdn.anthropic.com/fc1b44717c85dc068bc6ba5024219938094694bd/Claude%20Opus%205.5%20System%20Card.pdf" rel="nofollow">https://www-cdn.anthropic.com/fc1b44717c85dc068bc6ba50242199...
  I cannot find a Sonnet 5.5 system card.
  1. abejora · 1790620245 · focus · HN ↗
    It was linked in another HN post: <a href="https://www-cdn.anthropic.com/870c8f525702625d2c62fc6dd04c857e3250bec1/Claude%20Sonnet%205.5%20System%20Card.pdf" rel="nofollow">https://www-cdn.anthropic.com/870c8f525702625d2c62fc6dd04c85...
4. Leary · 1790620002 · focus · HN ↗
  And Sonnet 5.5 is more expensive than Opus 5.5 to hit that score on terminal bench!
5. manojlds · 1790621149 · focus · HN ↗
  Isn't that a worry then that the same bench has so much difference in what triggered fallback for one model and what did not in another?
  1. verdverm · 1790628310 · focus · HN ↗
    this "feature" is one of the primary that caused me to cancel and move to exclusively open weight based systems
6. oh_no · 1790621421 · focus · HN ↗
  it could be that, it could also be that sonnet max looks to burn about 60% more tokens than opus max
  AA intelegence index (agent harness doesn't have sonnet data yet) on max: Astra 27k Fable 5.1 78k (Sonnet 5) 118k Opus 5.5 119k Sonnet 5.5 193k
  Opus 5 was previous record holder so hats off to Anthropic on blowing it away on token churn.
7. subscribed · 1790623634 · focus · HN ↗
  I disagree, I think we should read a lot from it, as it stands in this benchmark Opus performs worse than Sonnet, it doesn't really matter why.
  Anthropic made it that way, and I'd say the lower score is accurate.
  1. cromka · 1790639513 · focus · HN ↗
    It matters if it's not Sonnet performing the task, doesn't it?
    subscribed · 1790671646 · focus · HN ↗
    *Opus
    But yeah, it does, but from my perspective it measured the Opus performance - subpar in some tasks because it downgraded itself rerouting to a much weaker model.
    So both you're right, it matters because it wasn't the model examined, and it doesn't matter because the score reflects nerfed experience resulting in nerfed results.
  2. bitexploder · 1790640548 · focus · HN ↗
    If you care about the things terminal bench cares about, yes. Sonnet was probably trained aggressively on agentic coding and things that align well with deepswe and terminal bench and or tuned heavily for those tasks. Sonnet is an agent likely to do more of those tasks and be given the more grunt work tasks. Whilst Opus' wider knowledge pool means it can deal with a much higher variety of real world situations successfully. And, those benches are often timed or limited. Opus may have been running out of time. Looots of factors.
    subscribed · 1790671930 · focus · HN ↗
    I see you.
    I just think that this benchmark measures what it say it does, and if the model is unable or unwilling to deliver, it's reflected in the score.
    (incidentally I found that generating code with Sonnet agent and having Opus orchestrate and manage the process works best for me - right model for the right task)
    I agree with your point - IMO lower Opus score in these suggests that in general it's worse for these tasks. Not that it's a worse model in general.
8. falcor84 · 1790625492 · focus · HN ↗
  So I suppose the easy fix for Anthropic would be to have Opus 5.5 now fall back to Sonnet 5.5, right?
9. shmel · 1790702328 · focus · HN ↗
  It'd be relevant if I could disable safeguards. As long as I can't, this is Opus 5.5 performance I have to deal with.
bayesianbot · 1790619613 · focus · HN ↗
Cache reads priced the same as Opus 5.5? So there won't be that much price difference in agentic coding. Or is that a mistake in the table, that seems quite weird
ChickeNES · 1790619634 · focus · HN ↗
Weirdly, the web ui has Sonnet 5.5 as "Most efficient" for "simpler tasks" and 5.0 still labeled the same for "everyday tasks", with Opus 5.5 as "For complex work and everyday tasks".
ahriad · 1790619690 · focus · HN ↗
Time to switch team to Claude from OpenAI again.
pavitheran · 1790619876 · focus · HN ↗
Big jump on Agentic coding from 10.3% -> 70.6% from Sonnet 5 -> 5.5 which even surpasses Opus 5.5. Opus 5.5 is really strong so this is impressive especially for the cost.
1. mydreamof · 1790621777 · focus · HN ↗
  Cost are bigger than Opus 5.5 for that effort
square_usual · 1790619926 · focus · HN ↗
Once again, once you hit the high/xhigh level you're better off using Opus low/medium to get better results for around the same price. So I suppose the main point of this release is that you have a lower end than Opus low, which I suppose some people will like?
1. quatotor · 1790620405 · focus · HN ↗
  [dead]
2. simianwords · 1790620665 · focus · HN ↗
  Important to note that lower model + higher reasoning gives a different (not higher) quality of response than higher model + lower reasoning.
  Some tasks are reasoning shaped by nature and you can't just throw a big model at it.
Jcampuzano2 · 1790619939 · focus · HN ↗
I don't understand why I would really use this over using just a lower or even similar effort level on Opus, given that in many of the benchmarks it's basically the same cost, if not more, at any effort higher than medium.
Sure maybe it costs 30% less than Sonnet 5 but now it's basically neck and neck in most of the benchmarks it seems and in some of them it actually outcosts Opus.
Maybe I'm missing something but the announcement doesn't really seem to give much reason for the average person to even think about using this.
1. jtrn · 1790635030 · focus · HN ↗
  Subagents.
  1. adastra22 · 1790679227 · focus · HN ↗
    Huh?
    Silagi · 1790688907 · focus · HN ↗
    For simple tasks that require a lot of input tokens (e.g, "Figure out the full path this function calls through and give me a map", or "Summarize these 5 PDFs and give me the main ideas I should explore") you can fire off a Sonnet agent at low-mid reasoning at it'll be cheaper than if you had Opus do that summarization itself.
    Now imagine you have a set of twenty of those tasks. You launch an Opus agent, give it the task list, and tell it not to do the work itself, but orchestrate agents to perform all of the tasks and do small spot checks to verify the work.
    The overall task is completed much faster at a similar or cheaper cost with an extra verification layer inserted that wouldn't have been there if you just used Opus.
    adastra22 · 1790715407 · focus · HN ↗
    Not sure how you’re seeing that. I just ran an experiment trying this and Opus was half the cost ($0.11 avg per task for opus compared with $0.21 for sonnet), mostly due to lower token usage. Opus 5.5 is really token efficient. This is without taking advantage of the further KV savings you’d get from forking.
    jtrn · 1790781478 · focus · HN ↗
    It has to be simple tasks. Opus is the orchestrator, and it tells 10 sub-agents to go out and look for one specific pattern in code, for instance. And it's not straight-up grepable. You have to actually inspect the code and just make an assessment as to whether or not the code fits the pattern one is looking for. In instances like that, Sonnet is really good for just plowing through lots of text and doing simple cognitive work. No need to pay double the price with Opus for large-scale batch work.
    But yeah, it's completely true that you sometimes have the ironic situation where you actually pay more with Sonnet because it's worse at reasoning itself down a rabbit hole. Sonnet really should be capped at medium or high reasoning.
    Ironically, one of the worst things you can do is to use Sonnet to organize sub-agents. It seems to be completely bonkers with what it asks agents to do. I tried to make a colleague of mine test the feature, and he, by accident, started a large bug hunt with Sonnet. It spawned 250 sub-agents and spent 5 hours looking through everything. It actually did find a couple of useful bugs, but not the one we were looking for, which is a stupid race condition probably.
ghoshbishakh · 1790620028 · focus · HN ↗
So sonnet is better than Fable now? That Fable which was too dangerous to release? I am so confused now.
1. heyjstn · 1790621970 · focus · HN ↗
  doom marketing at its finest
  1. solenoid0937 · 1790625444 · focus · HN ↗
    Not really, they never released Mythos. And they never said Fable was dangerous. They've been very consistent
2. mnicky · 1790622563 · focus · HN ↗
  Well, it's performance "surface" (is there a better term for this?) is probably very narrow compared to Fable :)
3. pebbly_bread · 1790623274 · focus · HN ↗
  Mythos is what they thought was too dangerous to release, fable was what they made after they worked on cybersecurity detection. As they say in the notes, this version of sonnet now has a similar screening process
  1. rs_rs_rs_rs_rs · 1790626778 · focus · HN ↗
    Mythos and Fable are the same llm. Fable has an extra tool that's in front of it that decides to accept the promp or not.
    dbbk · 1790627466 · focus · HN ↗
    Hence why it is no longer dangerous, yes
    emil-lp · 1790633972 · focus · HN ↗
    If you consider security through obscurity a safe route, yes
    usef- · 1790637353 · focus · HN ↗
    How is this security through obscurity?
    That term is about hiding a system's design in order to secure something, rather than having robust defences.
    emil-lp · 1790657850 · focus · HN ↗
    You answered your own question!
    usef- · 1790658090 · focus · HN ↗
    This is not relying on a hidden design.
    emil-lp · 1790664941 · focus · HN ↗
    The design allows users to bypass the security by luck and chance.
    A secure system is impenetrable unless you have the key.
    usef- · 1790667589 · focus · HN ↗
    Yes, it does depend on a probablistic classifier.
    It sounds like you're thinking of cryptography, not general security. The world uses many security products that have false positives and false negatives (firewalls, intrusion detections, wafs, fraud detection...). Those aren't generally considered security through obscurity.
    They openly talk about the system and its drawbacks here: <a href="https://www.anthropic.com/news/fable-safeguards-jailbreak-framework" rel="nofollow">https://www.anthropic.com/news/fable-safeguards-jailbreak-fr... and mention it goes along with rate limits, monitoring, account control, multiple classifiers, model design, and other things too.
    I think this was also why they faced the controversy over not having zdr in fable: they wanted to use logs to detect repeated attempts, etc.
    stravant · 1790674400 · focus · HN ↗
    That's not how it works.
    The reason you see "dumb" refusals that "should clearly be allowed" is that they're using more traditional deterministic methods to deny prompts rather than just relying in the stochastic LLM which you could bypass by luck.
    usef- · 1790637196 · focus · HN ↗
    And Sonnet has a similar classifier in front according to the article:
    > it’s the first Sonnet model to launch with cyber safeguards
4. Art9681 · 1790634604 · focus · HN ↗
  You have to actually spend some effort reading the article they published to answer your own question.
5. usef- · 1790637168 · focus · HN ↗
  They have the same safety classifiers on this as Fable. They did think Fable was safe to release (unlike Mythos).
yapfrog · 1790620180 · focus · HN ↗
From the graph it looks like I'd rather use Opus 5.5 High than Sonnet 5.5 at all
solenoid0937 · 1790620235 · focus · HN ↗
Amazing release. This thread is already full of cynicism and angry hot takes. The Opus 5.5 thread was like this as well despite it being a hit with everyone.
At this point it's almost comical how angry Anthropic makes HN. It's like the opposite of Apple's reality distortion field.
1. ricardobeat · 1790620319 · focus · HN ↗
  I mean, they worked really hard for this. Back in February everybody loved them.
  1. solenoid0937 · 1790620508 · focus · HN ↗
    I think all the positive people have just stopped commenting.
    The difference in perception for Opus 5.5 on HN vs the real world is what convinced me HN is totally detached from reality.
2. rfgplk · 1790620497 · focus · HN ↗
  Astra is still the uncontested #1 code generator.
  1. solenoid0937 · 1790620521 · focus · HN ↗
    Astra is amazing, I love it.
  2. dude250711 · 1790621656 · focus · HN ↗
    Yeah, especially coupled with Opus for alternative reviews. A massive token burn though.
3. boc · 1790627779 · focus · HN ↗
  I was talking about this with a friend this weekend. We both work in the field and test new models within minutes of them being released. We both immediately clocked Opus 5.5 as being cracked within the first hour. Went on HN and the launch announcement was full of people whining and pointing at cost/token charts vs Chinese models. It was like the upside-down world.
  We were both sad that HN has become a negative signal news source on AI lately - you're much more likely to be misled by this website in 2026 on the topic of frontier AI. If you're reading this comment, you should do your own research vs trusting the "Astra is 1000% the best" or "Deepseek is the $/tk KING" comments swarming these announcement posts.
4. breezybottom · 1790638802 · focus · HN ↗
  Was it a hit with everyone, or did HN hate it? Both those things can't be true.
alansaber · 1790620317 · focus · HN ↗
Always key to include the one bench where the smaller model inexplicably outperforms the larger model
limsungkee · 1790620382 · focus · HN ↗
Yesterday, I realized that Opus 5.5 is cheaper than Sonnet 5. Now I know the reason.
ghoshbishakh · 1790620422 · focus · HN ↗
So Sonnet 5.5 on max effort is as expensive as Fable 5.1? Because it uses a ton of tokens for a task.
In xhigh effort it is a lot cheaper and possibly lot less impressive?
dack · 1790620451 · focus · HN ↗
very annoyed they aren't showing fable on the graph.
s314 · 1790620592 · focus · HN ↗
In the Artificial Analysis Intelligence Index, Claude Sonnet 5.5 is the second best model behind Opus 5.5. This however is with max effort which costs even more than Opus 5.5 max. But Sonnet 5.5 xhigh is cheaper than Opus 5.5 xigh and matches GPT 6 Astra xhigh in the benchmark.
1. zozbot234 · 1790621009 · focus · HN ↗
  > In the Artificial Analysis Intelligence Index
  lol, MiMo 2.6 Pro still matches Sonnet 5.5 high (mind you, not xhigh or max) at a far lower price.
tombert · 1790620765 · focus · HN ↗
I like that "alignment on safety" appears to mean, at least for anything I've been doing, that they won't violate Microsoft's terms of service. I even had it pushing back on me activating an LTSC key on Windows because LTSC keys are "often purchased on a gray market and violate Microsoft's TOS".
1. aniceperson · 1790623308 · focus · HN ↗
  I saw that with corporate software too. What works is creating a skill with the task steps, it fades its initial reasoning. (I am not talking about observer safe guards, but the safety RTL).
croemer · 1790620831 · focus · HN ↗
Playing around with it for a few minutes, Sonnet 5.5 feels very fast, much quicker than Opus 5.5. Can't tell yet if it's a lot worse but the speed is definitely welcome.
alasano · 1790620937 · focus · HN ↗
I wonder if Fable 5.5 is coming this week to drown out the OpenAI dev day announcements
1. kccqzy · 1790643969 · focus · HN ↗
  When they announced Opus 5.5, they specifically said that Sonnet 5.5 and Haiku 5.5 are coming. I think Fable won’t come until Haiku is updated.
enraged_camel · 1790621007 · focus · HN ↗
Another amazing release. This, combined with Opus 5.5, puts OpenAI in an incredibly tough spot: it means Anthropic's both mid-tier models crush OpenAI's top-tier model in capability and are also faster and significantly cheaper.
If Astra 6.1 is released tomorrow during Dev Day it needs to leap-frog both, and considering 6.0 came out just three weeks ago I think that's unlikely. But even if that happens, Anthropic is still holding on to Fable 5.5, which rumor has it being prepared for release in the next few weeks.
OpenAI also has a more capable model codenamed 'Bel' but from what I hear that's a few months out at least.
It looks to me as if Anthropic not just killed but completely stole the momentum OpenAI had gained over the past few months. Even if Tibo showers people with resets it may not be enough to entice them back...
1. sajithdilshan · 1790625797 · focus · HN ↗
  Open AI is terrible at diversifying their offering. We use Anthropic models via AWS bedrock where inference is deployed in EU regions due to strict compliance reasons. We've been wanting to try out the new Open AI models for ages, but they don't offer the models in any EU region. Open AI is losing a ton of money they can milk from corporations because of that.
Alifatisk · 1790621068 · focus · HN ↗
In other news
> Claude Haiku 5.5, built for high-volume and cost-sensitive applications, will join the Claude 5.5 family in the coming weeks.
simonw · 1790621080 · focus · HN ↗
Pelicans. Sonnet 5.5 has the same problem as Opus 5.5: on "max" thinking effort it burned through 128,000 thinking tokens (taking 15 minutes to do that) and ran out before it had produced the final SVG.
<a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F1d85a9be7f3ecce26e7f1569161a0d01" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Here's how the thinking effort levels compare:
```
  low
  27 input, 1,623 output, thinking_tokens: 0
  1.6284
  Duration: 10138ms (10s)
  
  medium
  27 input, 1,796 output, thinking_tokens: 0
  1.7914 cents
  Duration: 11266ms (11s)

  high
  27 input, 2,334 output, thinking_tokens: 745
  2.3394 cents
  Duration: 17376ms (17s)

  xhigh
  27 input, 5,730 output, thinking_tokens: 2535
  5.7354 cents
  Duration: 41882ms (41s)

  max (failed to return response)
  27 input, 128,000 output, thinking_tokens: 128000
  $1.28
  Duration: 940617ms (15m 40s)
```
Low and medium both used 0 thinking tokens.
1. croemer · 1790621558 · focus · HN ↗
  This is evidence that Sonnet 5.5 wasn't yet trained on the HN comments from the Opus 5.5 release. Maybe Pelicanmaxing will lead to 127000 thinking tokens being used on Max.
  1. gumby271 · 1790621677 · focus · HN ↗
    If it was trained on HN, there would be a 60% chance of it just saying "I'm so tired of this request, can we please move on"
    miki123211 · 1790630022 · focus · HN ↗
    I'd say:
    30% chance of responding with something about Enshittification and how it can't fulfill your request because the sources it needs are behind a login wall and show an endless captcha loop (conveniently forgetting to mention that it's running on FreeBSD behind PiHole).
    30% chance of complaining that it's being subsidized and that "prices are going to go up bro."
    30% chance of some unrelated rant on ID checks for age verification.
    10% chance of a different rant, this time on how nobody took Snowden seriously and how terrible Flock is.
2. TomGarden · 1790621785 · focus · HN ↗
  Where do you run sonnet/opus where you are limited to 128k, given they are both 1M context window models?
  1. croemer · 1790621815 · focus · HN ↗
    I think he just doesn't want to spend more
  2. petu · 1790622078 · focus · HN ↗
    That's max output tokens per response limit, separate from context length
  3. simonw · 1790622677 · focus · HN ↗
    It's the output token limit, which has been 128,000 for Claude models for quite a while note
    croemer · 1790623863 · focus · HN ↗
    Pretty crazy that the model doesn't know that it needs to stop before it hits 128k output tokens. I guess it has no sense of how many tokens in it is? Wouldn't this be possible to work into the architecture?
    simonw · 1790624421 · focus · HN ↗
    I think this is a bug. I've not seen this problem from any of the other frontier models.
    Insanity · 1790624912 · focus · HN ↗
    Do other models put a hard cap on the output tokens it can generate?
    simonw · 1790628916 · focus · HN ↗
    Yes, the OpenAI GPT-6 Astra limit is 128,000 as well: <a href="https://developers.openai.com/api/docs/models/gpt-6-astra" rel="nofollow">https://developers.openai.com/api/docs/models/gpt-6-astra
    Gemini 3.8 Flash is 65,536 <a href="https://ai.google.dev/gemini-api/docs/models/gemini-3.8-flash" rel="nofollow">https://ai.google.dev/gemini-api/docs/models/gemini-3.8-flas...
    NewJazz · 1790629999 · focus · HN ↗
    [delayed]
3. heyjstn · 1790622207 · focus · HN ↗
  I think the next models will be benchmaxxing on the Pelican benchmark tbh
  1. dmd · 1790627735 · focus · HN ↗
    wow nobody but you has ever thought of this and certainly simonw has never addressed this
4. aimaxxed · 1790622501 · focus · HN ↗
  “Pelicans are solved.”
  1. [deleted] · 1790631544 · focus · HN ↗
    [deleted]
5. platinumrad · 1790623033 · focus · HN ↗
  The contrast between Anthropic, who seem to be training their models to output ever-increasing numbers of reasoning tokens, and Fireworks's Ember-1, which was explicitly trained to preserve the quality of a model's responses while cutting down on reasoning, is interesting. Claude Code also uses more many tokens per task per model than any other harness in benchmarks.
  1. usef- · 1790629231 · focus · HN ↗
    Note that at Medium effort, Opus looks more token-efficient according to AA Intelligence it while still scoring higher. Medium is usually Anthropic's default setting.
    As far as I know the purpose of reasoning levels is to be able to crank out more thought tokens if needed, so having a less efficient mode isn't necessarily a mistake.
    AA Output tokens Reasoning tokens Cost / task Kimi K3 Max 44 48k 32k $2.00 Opus 5.5 Medium 51 26k 12k $1.34 Opus 5.5 High 54 36k 18k $1.82
  2. usef- · 1790629599 · focus · HN ↗
    Anthropic's "Max" modes seem like a yolo mode: "use 10x the tokens to try to break the hardest possible problems". But they don't seem less efficient at normal reasoning modes.
    I can't see Ember on AA's index yet, but their post claims "half the reasoning tokens for the same answers" as Kimi K3.
    That would make it about so, I assume?
    Score Tokens Reason Cost Kimi K3 Max 44 48k 32k $2.00 Half reason 44 32k ? 16k ? ? Opus Med 51 26k 12k $1.34 Opus High 54 36k 18k $1.82 Opus Max 58 119k 84k $5.98 Sonnet Med 41 ? ? $0.59 Sonnet High 47 ? ? $1.08 Sonnet Max 56 193k 142k $7.60
    Medium is Anthropic's default.
    Having a less efficient mode isn't necessarily a mistake -- the purpose of configurable effort levels after all is to be able to put more thought into a problem.
6. keeeba · 1790623497 · focus · HN ↗
  Thank you for the pelicans sir, how do you think they compare to other models in Sonnet’s pricing/capability range?
7. parkersweb · 1790625036 · focus · HN ↗
  I like the one where the pelican is using the non-pedalling leg to control the handlebars because its wings won’t reach!
8. pelicanmaxer · 1790625644 · focus · HN ↗
  that pelican one-pedaling
9. amelius · 1790628621 · focus · HN ↗
  This is great news because it means the model has not been benchmaxxed on stupid metrics.
  PS: the next human that brings up pelicans on bicycles should try to draw them.
10. dennisy · 1790630346 · focus · HN ↗
  Does anyone really still care about these pelicans?
  Any model release it’s the top comment, I do not understand why.
  1. uncivilized · 1790631040 · focus · HN ↗
    Karma farming by parent commenter and HNers’ tendency to upvote low quality content (not dissimilar to other social media networks)
    conception · 1790634509 · focus · HN ↗
    Is this low quality content relative to most HN comments?
    uncivilized · 1790640612 · focus · HN ↗
    Very few HN comments are high quality
  2. simonw · 1790631645 · focus · HN ↗
    Mainly because they're funny, but it's also because I try pretty hard to make the comment more interesting than just "here's a pelican". In this case I used the pelicans to talk about the 128,000 token limit bug at "max" and share comparative pricing.
    In the GPT-6 comment I included full visual comparison grids: <a href="https://news.ycombinator.com/item?id=49805509#49806126">https://news.ycombinator.com/item?id=49805509#49806126
    For DeepSeek v4.1 Flash I identified that the OpenRouter reasoning levels are mapped to a smaller set of levels for that model: <a href="https://news.ycombinator.com/item?id=49639090#49645591">https://news.ycombinator.com/item?id=49639090#49645591
  3. kennyadam · 1790632083 · focus · HN ↗
    Agreed. It was a creative and unique test for a while. Now, no offense to the author, it feels like every conversation about a new model is dominated by the pelican on a bike posts as they always become the top comment.
    simonw · 1790632436 · focus · HN ↗
    You can click the little [-] icon next to the post to collapse the entire sub-thread. I do that all the time.
  4. marktolson · 1790632941 · focus · HN ↗
    It's an easy way to compare the coding and creative strengths of models. I prefer them over reading a tabular comparison of benchmarks which you have no real insights into.
  5. Glemmlko · 1790634262 · focus · HN ↗
    Because hn has some kind of a community and not every comment is gold (see yours for example) and people are able to skip comments if they don't enjoy them?
  6. mvdtnz · 1790639933 · focus · HN ↗
    I can't understand it. Clearly someone cares because like you say the comments are always upvoted. But why anyone cares I simply don't know. It just feels like attention seeking behaviour to continue posting it.
    simonw · 1790640746 · focus · HN ↗
    Isn't posting any comment on a forum like Hacker News "attention seeking behavior"?
    mi_lk · 1790652808 · focus · HN ↗
    Did you ignore the continue part that compounds the attention seeking?
    simonw · 1790655382 · focus · HN ↗
    Linking to <a href="https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F1d85a9be7f3ecce26e7f1569161a0d01" rel="nofollow">https://tools.simonwillison.net/markdown-svg-renderer?url=ht... should be pretty inoffensive (I started habitually linking to that after people kept complaining about linking to my blog) - that page renders Markdown with SVG embedded in it, but doesn't link to the rest of my site at all.
  7. ceroxylon · 1790644152 · focus · HN ↗
    This is a community and it is an inside joke at this point, it wouldn't be a proper model release without Simon's pelicans.
    I find it useful (as well as a fun art project).
  8. mi_lk · 1790644981 · focus · HN ↗
    Sick of the bit
  9. permalac · 1790664243 · focus · HN ↗
    I would not say I care, but I do have curiosity. I expect one day they will start adding some textures or something like that.
  10. dramebaaz · 1790669147 · focus · HN ↗
    It would have taken me a while to stumble upon this "running out of tokens" on MAX thinking issue without his trials and post. I've seen the pelicans for years now, and if they stopped coming for some reason, I would probably go to his site to catch up on recent models and findings. So I don't mind them
  11. krzyk · 1790673220 · focus · HN ↗
    I do, it gives some fun comparison between models.
    You can also check for any kind of degradation of them - you have the prompt, it doesn't use much $.
11. codingisfreedom · 1790631130 · focus · HN ↗
  Sonnet 5 had the same problem with ‘max’. In a free sub, I would never get an answer back even for very simple prompts. It would just churn on nothing.
  I’m not sure whether that’s a feature or a bug at this point though.
12. mgaunard · 1790633105 · focus · HN ↗
  what's most surprising is the difference between high and xhigh
13. hooloovoo_zoo · 1790633628 · focus · HN ↗
  I feel the fact that these models always modify the body design of a pelican to fit the bike rather than the other way around represents a fundamental issue with AI.
14. nicolamanzini · 1790635012 · focus · HN ↗
  [dead]
15. mewse-hn · 1790654655 · focus · HN ↗
  max thinking means benchmaxxing i guess
SeriousM · 1790621222 · focus · HN ↗
Next will be haiku 5.5, surpassing opus 4.8
heyjstn · 1790621368 · focus · HN ↗
Have anyone tried a workflow that:
- Fable 5.1 for planning/adversarial reviewer
- Opus 5.5 for well-scoped tasks break down
- Sonnet 5.5 for these well-scoped tasks implementation
I think the blocker might be how efficient the context is compacted and sending around between these agents
1. chrismustcode · 1790621483 · focus · HN ↗
  You might as well use Opus for everything there.
  Changing model would be cache busting spiking usage for no good reason when Opus can do it all.
  Haiku 5.5 might fit well though depending on pricing.
  1. SirMadam · 1790621882 · focus · HN ↗
    Do subagents share context? If Opus delegates to a different Sonnet window, I don't believe this busts cache?
    enraged_camel · 1790622458 · focus · HN ↗
    Subagents don't share context. But that's why delegating implementation to a subagent doesn't work well except for things that are truly mechanical in nature: the subagent needs to independently reason about the task it is given, and then the output will also be reasoned about by the main agent. So you end up wasting time and tokens.
    mnicky · 1790622731 · focus · HN ↗
    On the contrary, subagents save context overall, when the task is sufficiently large.
    Also, my experience is that Fable 5.1 is very good at prompting/orchestrating Opus/Sonnet subagents when working on a larger task (e.g. 1-2M context window use only for the orchestrator itself).
    esafak · 1790630701 · focus · HN ↗
    If you use subagents your main agent won't need to compact as often, with the loss of information that entails.
    manquer · 1790624705 · focus · HN ↗
    [delayed]
  2. dbbk · 1790627511 · focus · HN ↗
    Using advisors doesn't break anything
2. afro88 · 1790621729 · focus · HN ↗
  Opus 5.5 in my experience outshines Fable 5.1 anyway. May as well have Opus do plan, breakdown and review, and Sonnet implement.
3. Aboutplants · 1790624119 · focus · HN ↗
  Do you even need Fable for much of anything now? I’m basically using it as a reviewer at the end of whatever I’m working on, and even then I’m really not finding much benefit.
4. robwwilliams · 1790634764 · focus · HN ↗
  Agree with afro88. Opus 5.5 as competent as Fable 5.1 on complex adversarial review of material and equations planted with errors. I still use both for a bit of variety.
5. jessebldr · 1790650572 · focus · HN ↗
  [dead]
AM1010101 · 1790621459 · focus · HN ↗
For me I would like to pair this with Opus 5.5 as orchestrater and use Sonnet as a sub agent. Therefore I want it to be fast when on low or medium and not break the bank.
On low and medium it seems competitive, maybe slightly cheaper than opus, in terms of intelligence per task.
If the time per task is lower (Artificial Analysis don’t have the date up at time of posting) then I have a clear use case for this model all other things being equal.
gregwebs · 1790621471 · focus · HN ↗
This is better priced than Opus for tasks that are token heavy but not complicated. But a quick look shows that at least on some benchmarks DeepSeek performs as well and of course the cost is an order of magnitude less.
From looking at their Terminal-Bench graph, anything you would use level "high" or above for Sonnet it seems like you should consider using Opus instead.
OpenAI Luna is a lot cheaper. But DeepSeek seems smarter and the cost seems similar.
jtrn · 1790621546 · focus · HN ↗
Sonnet:
If what they say is true, this sounds like the main takeaway: Sonnet 5.5 gives about 90% of Opus 5.5's capability at half the cost.
BUT
It regularly loses out to Opus 5.5 on cost efficiency at the highest reasoning level, because Opus uses the tokens more efficiently and makes fewer mistakes. So, After passing a high-reasoning test, you might as well switch to Opus 5.5.
Some of the more interesting things I found from scanning the system card: - It is the only model tested that shows no preference for rude or polite style. - It makes fewer claims of "I'm done" than Sonnet 5, but is still worse than Opus 5.5 on this. - It almost never refuses benign requests (0.02% vs. 0.59% for Sonnet 5). - Cybersecurity blocking follows the same policy as Opus, witch mean we will get more refusals than Sonnet 5. - Finding bugs in source code is allowed. Finding bugs in compiled binaries is blocked. - Its thinking is the hardest to read of any model tested. The sample in the card reads like clipped notes. - Really good at rejecting prompt injection (3.0% rate vs. 19.5% for Sonnet 5 and 54.6% for Opus 5.5 in red-team testing).
Clinical behaviour:
Suicide and self-harm handling is reported as weaker in the API because it
It sometimes called a wish to die understandable. It sometimes validated self-harm as functional. It sometimes suggested harmful substitute behaviours.
As a clinical psychologist, I would say that the first two are actually defensible, and if you classify them as simply wrong, then you are bringing in your own values and not basing your judgment on actual science and existential psychology, at least. But the last one is harder to defend... Recommending alternative harmful behavior is obviously not a good idea. However, I have not seen the actual behavior in session, so I don't know if I would truly agree or disagree with the classification of these behaviors as wrong or right. But I do know that it's not as simple as saying this is binary—wrong or right. There are some instances of people self-harming who would actually refrain from doing so if they, for instance, went out to a party or a pub. We can't exactly recommend that as a treatment or intervention for self-harm, but there is no doubt that it works for some people. And we literally classify self-harm as "functional" in the literature. Depending on the context, this is not only a correct description but also a common way of understanding and describing certain subtypes of self-harm. And lastly, some people find immense support in being understood and validated in their current feelings og wanting to die. Validating that feeling does not make people immediately act on it. But there's a huge spectrum here, going from "I understand it's hard" As basic empathy and understanding, to: "Yes, this sounds like the only good plan. I agree, you should do it."
Now I'm off to actually test it because this was just an exercise in reading what they claim, which we now know is not indicative of how good the model will actually be
1. solenoid0937 · 1790651663 · focus · HN ↗
  Very interesting comment, thank you for sharing!
dude250711 · 1790621762 · focus · HN ↗
It's strange that there are no Astra comparisons. I guess they are positioning it as a Fable competitor. For me it's just a coding workhorse though, without any "fall-backs".
dom96 · 1790622304 · focus · HN ↗
I built an adversarial esoteric programming language to benchmark LLM models and just ran it on Sonnet 5.5 It does worse than Sonnet 5. Mainly because it is more reluctant to keep going to get an answer, instead it returns to ask the user questions whether to keep going.
<a href="https://bench.killswitch-lang.org/" rel="nofollow">https://bench.killswitch-lang.org/
```
    Claude Sonnet 5    17.8%
    Claude Sonnet 5.5  7.4%
```
thefourthchime · 1790622353 · focus · HN ↗
It does vey well at one shotting a PacMan clone, pretty much perfect. <a href="https://jonclegg.github.io/pacman-bakeoff/entries/claude-sonnet-5-5.html" rel="nofollow">https://jonclegg.github.io/pacman-bakeoff/entries/claude-son...
2nd only to Opus 5.5, which is perfect. <a href="https://jonclegg.github.io/pacman-bakeoff/entries/claude-opus-5-5-r2.html" rel="nofollow">https://jonclegg.github.io/pacman-bakeoff/entries/claude-opu...
Up until very recently, all models struggled with this.
All results: <a href="https://jonclegg.github.io/pacman-bakeoff/" rel="nofollow">https://jonclegg.github.io/pacman-bakeoff/
1. judge2020 · 1790623498 · focus · HN ↗
  Oh, it coded a Pac-Man clone. The clone was so good that I thought it was premade in some way and that Sonnet was going to play PacMan.
  1. thefourthchime · 1790623850 · focus · HN ↗
    Yes! The point being that up until yesterday, every model struggled with this, and now they don't.
    thefourthchime · 1790626200 · focus · HN ↗
    Your welcome!
    copperx · 1790627120 · focus · HN ↗
    "this" being recreating Pacman specifically, or games?
    londons_explore · 1790627676 · focus · HN ↗
    I made ~10 games with opus 5.5 (all multiplayer web games over web sockets).
    About half the time it made a playable game in a single short prompt. The other half of the time a few follow-up prompts were needed for refinement (eg. Things like "the blaster weapon is way too powerful, divide it's hit points by 10" or "we need a way to reconnect a player whose network dropped mid round" or "the GPS doesn't work on iOS")
    copperx · 1790627999 · focus · HN ↗
    Other models fail at oneshot creation of similar games?
    igleria · 1790676426 · focus · HN ↗
    > "the blaster weapon is way too powerful, divide it's hit points by 10"
    this is literally faster to do it yourself
    > "we need a way to reconnect a player whose network dropped mid round" or "the GPS doesn't work on iOS"
    these would not.
    weird-eye-issue · 1790685417 · focus · HN ↗
    > this is literally faster to do it yourself
    It's literally not unless you already know exactly where it is in the code
    ThunderSizzle · 1790730295 · focus · HN ↗
    Also, if you then resume your conversation, and the LLM discovers the change, it might revert the "accidental" change.
    If your working with an active context, and changes you do then need to be conversed back to the agent, and even then, it might still find it jarring and wrong.
    weird-eye-issue · 1790756866 · focus · HN ↗
    I actually haven't had this happen in several months, they have gotten much better at just ignoring changes they haven't made in my experience. Unless it's directly conflicting with something they are already working on of course then they might change it but at least they will note it
2. russellbeattie · 1790623702 · focus · HN ↗
  [delayed]
  1. thefourthchime · 1790626208 · focus · HN ↗
    Thanks!
3. ilamont · 1790625143 · focus · HN ↗
  Thank you for doing this. It is very helpful not just for capabilities but also for costs.
4. sixtyj · 1790627067 · focus · HN ↗
  I have played few of them and it seems that Opus 5.5 is the first one who really made playable PacMan clone game. On mobile as well.
  Could it be because the model was somehow pre-trained? If we compare it with pelicans that are still not-perfect…
  1. lukan · 1790667763 · focus · HN ↗
    " If we compare it with pelicans that are still not-perfect…"
    Fable 5.1 was pretty good. Even animating it:
    <a href="https://news.ycombinator.com/item?id=49526704">https://news.ycombinator.com/item?id=49526704
5. nicce · 1790627829 · focus · HN ↗
  I was able to get similar with Qwen 3.8 27B with one shot. I think this game is too well in the training data.
6. sally_glance · 1790627907 · focus · HN ↗
  Cool page and benchmark idea! Would be nice if there was some kind of grading the results, maybe on different criteria (aesthetic, implementation complexity, correctness, ...). Of course as a one-shot and greenfield benchmark the results are not indicative for all kinds of usage patterns. But as some sibling said, maybe they can be indicative on some general characteristics (especially since the task is so open-ended).
  1. thefourthchime · 1790635494 · focus · HN ↗
    Just added! I had Opus 5.5 look at them, not a perfect way to score them but it's close-ish -- Best would be a ELO, where people play both and rank a winner, but I don't know if people want to bother doing that.
    sally_glance · 1790717583 · focus · HN ↗
    Pretty cool. Using Opus as a judge should be more than good. Interesting to see more stats like the result file size too, but the grading criteria are maybe a bit skewed towards UX. Would like to see more code quality.
7. pyaamb · 1790628335 · focus · HN ↗
  Very cool. I'd love to see someone with access to plenty of token$ make something similar for the "Browser Desktop OS" test. That seems like a pretty comprehensive test thats also fun to test just like this!
8. formvoltron · 1790629509 · focus · HN ↗
  oh! How about pengo, dig dug, & defender?
  1. thefourthchime · 1790635534 · focus · HN ↗
    I'm afraid those will be too easy. I'm not sure what the next game should be...
9. fakedang · 1790630939 · focus · HN ↗
  Interesting. Sonnet 5 was horrible, and Opus 5 was unplayable, but both Sonnet 5.5 and Opus 5.5 were about as close to the real thing.
10. sunaookami · 1790632413 · focus · HN ↗
  GPT models really have no taste huh.
11. coopykins · 1790668264 · focus · HN ↗
  Surprising how cheap Sol 6 was.
12. giancarlostoro · 1790711435 · focus · HN ↗
  Well, I thought you meant the Pacman package manager for a second, still impressive. I've noticed the last few versions of Opus have produced better video game coding output.
  <a href="https://wiki.archlinux.org/title/Pacman" rel="nofollow">https://wiki.archlinux.org/title/Pacman
swingboy · 1790622448 · focus · HN ↗
Is Opus still 2x usage of Sonnet after this? My Claude Code isn't showing that warning anymore when I look at /model.
laurenz-bauer · 1790622638 · focus · HN ↗
Oh yes. I think you might get a lot for what you pay with Sonnet 5.5.
MisterMunchkin · 1790622981 · focus · HN ↗
It costs 20x more than the Chinese models I use. I just don’t need them anymore. Sure I’d use them if forced to for a job, but I don’t pay them outside of that anymore.
And my job won’t even pay for Claude now because it’s so ruinously expensive.
1. throwa356262 · 1790623713 · focus · HN ↗
  Mimo 2.6 Pro: 0.04/0.4/0.87
  Sonnet 5.5: 0.2/2/10
  Opus 5.5: 2x of above
  What I dont understand is cache writes ($2.5). Why is that not covered by input cost?
  1. tintor · 1790628504 · focus · HN ↗
    You don't have to pay for cache write if prompt isn't part of conversation.
  2. lcampbell · 1790631416 · focus · HN ↗
    I was under the impression that the cache write fee was added to both the input and output costs (except in cases where the cache write is explicitly disabled via e.g. DISABLE_PROMPT_CACHING). The output becomes part of the context, after all; if they don't (for some reason, due to a disaggregated inference perhaps) then I'd expect output tokens get charged both output then input+cache_write on the subsequent completion request.
    The pricing model confuses me though (I presume by design, Hanlon be damned).
  3. usef- · 1790635350 · focus · HN ↗
    fwiw, the subscription plans of Anthropic are also 10x cheaper per token
  4. [deleted] · 1790636406 · focus · HN ↗
    [deleted]

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