[frevib]

At this point Anthropic is a pure marketing and PR company. Super catchy names like Opus, Mythos and Fable trying to get you to think that these software products are actually super-human life changing experiences. Boris Cherny coming to HN “Hi! it’s Boris from the Claude Code team” to get real tech people’s goodwill.

From Opus 4.6 there are no noticeable improvements for me in code generation. It works very well, till 90% completion, if you guide it correctly. And you need a little luck. For serious production code I need to understand what I’m doing so it helps a bit, sometimes.

[matheusmoreira]

> Boris Cherny coming to HN “Hi! it’s Boris from the Claude Code team” to get real tech people’s goodwill.

This is a good thing. I wish every company would do this. I subscribed to Proton Mail after interacting with someone from their team here on HN.

[pinkmuffinere]

> catchy names like Opus, Mythos and Fable trying to get you to think that these software products are actually super-human life changing experiences

This is just good business sense. In what scenario would you ever make the names dumb and forgettable?

> Boris Cherny coming to HN “Hi! it’s Boris from the Claude Code team” to get real tech people’s goodwill.

This is good customer support, lol. From what I can tell, it is indeed Boris Cherny responding, not outsourced to AI or other staff. You're really getting a response from Boris. I suppose that is PR, but it's not unjustified PR, it's accurate.

I'm not even a crazy AI fan, but your criticisms are ridiculous here. It reminds me of the quote from Knives Out -- "Your Honor, she endeared herself to him through hard work and good humor."

[IshKebab]

> In what scenario would you ever make the names dumb and forgettable

Clearly you've never bought a TV or headphones!

[aspenmartin]

Your observations are right but pretty insane to consider them a pure PR company lol. They are making more frequent releases so yes the release-to-release quality is smaller but we’re still ascending quality and reliability curves the same way we have since GPT-3. You get a GPT4->5 leap every like 17 or 18 months I think it is

[kingkongjaffa]

The gradient of improvement is absolutely not the same.

[aspenmartin]

If anything its slightly higher. Feel free to provide any evidence to the contrary.

ECI (good aggregate measure using IRT): https://epoch.ai/eci?view=graph&tab=release-date&subset-view...

METR time horizon (now topped out): https://metr.org/time-horizons/

[WASDx]

I like this one, although its data seem to overlap with ECI.

https://artificialanalysis.ai/trends

[astrange]

> Super catchy names like Opus, Mythos and Fable trying to get you to think that these software products are actually super-human life changing experiences.

They're originally named after the blends at a nearby coffee shop.

https://postscript.co/pages/brew-guide

I've noticed nobody at HN knows what "marketing" is or how to do it. It's not just naming things and being evil and cynical is not the most successful method.

…also frontier models are a superhuman life changing experience. If they aren't, what possibly could be?

[ValentineC]

Found a tweet from a year ago about this:

https://twitter.com/brian_a_burns/status/1866987688794132816

Well, TIL.

[chroma_zone]

My life has changed, but not necessarily for the better.

[bitpush]

This is interesting. Do you have any source?

[CuriouslyC]

I dislike Anthropic but I wouldn't argue 4.8 isn't an improvement on 4.5/4.6. Your tasks just might not typically need the extra intelligence.

[jorl17]

Opus 4.7/4.8 often over-engineers on my setups, plus:

- It talks a LOT more like GPT models. You know: wrinkle, shape, gate, coarse, scope, gap, path, production-ready-workflow-of-the-day, and so on -- "that's expected, a consequence of the previous like-driven workflow". If I wanted to get a headache using AI I would have gone with GPT in the first place!

- It outputs text in a much harder way to follow along. I can't exactly say what it is. Maybe a bit of everything? Bolds are missing, bullet points are gone, paragraphs are bland and too long, and it doesn't feel like a model programming with me, but rather a somewhat full of themselves grandpa developer looking down on me. It's very weird to describe this, but it is definitely how I feel.

Granted this can totally be because of the way it reacts to the prompts now. We've got a rather large corpus of skills and "rules and good practices" that Opus 4.6 responded to great, and maybe the new models just get turned into this when fed with them....I don't know.

Either way, with Opus 4.6 being as good as it is, I need Fable to be a significant step up to justify a price increase. if it can get me to babysit opus a little bit less on some stuff, it might be worth it. Otherwise, I'm very happy with Opus 4.6 and hope they don't deprecate it.

[taormina]

I'd argue that 4.8 is a straight downgrade. For every type of task I've tried. It's been a gambit at this point. If 4.6 quits being available, I'm out at this point.

[coronapl]

Reading so many contrary positions about which model is better or worse shows how difficult it is to measure intelligence based on personal experiences. Of course, benchmarks try to make the process as objective as possible, but they often don't correlate with our personal experiences.

The other day 4.6 was fantastic for x task. Today, 4.6 overengineered everything and I had to revert all my changes. When evaluating models, perhaps it makes sense to consider luck as an ingredient before reaching any personal conclusion.

[surgical_fire]

I actually experience 4.8 as worse than 4.6 for everyday coding tasks.

[dcchambers]

IME Opus 4.8 (and 4.7) is often a downgrade from 4.6. I find that it tends to overthink and overcomplicate things.

[aspenmartin]

Yes but there’s a reason we don’t evaluate these models this way and instead do it as carefully and thoughtfully as we can at scale. Human evaluations are important but they are an absolute minefield of footguns. 4.8 is not a downgrade from 4.6 there is an insane amount of hard data that contradicts this.

[computerex]

The flip side is that benchmarks are gamed even by the top labs. Benchmark performance doesn't necessarily correlate with real world performance.

[aspenmartin]

Again correct but it overstates the issue. I can say labs don’t want this. This happened arguably unintentionally in Metas llama 4 release, it went horribly, heads rolled, and like several billion dollars were paid for new talent and the org that built llama 4 was destroyed.

Evals come from a million places and new evals and robust perturbations of existing evals abound. They test a variety of tasks in a variety of ways. All of them individually are flawed. Taken together the aggregate signal is highly useful as you more or less marginalize over a lot of different things. Not to mention these companies have plenty of proprietary internal measurements, they build benchmarks themselves to probe their models and then also have flywheel traffic and A/B tests.

You are right to call out benchmarks but to dismiss them or not take them seriously is a mistake.

[taormina]

Listen, you can say “but benchmarks, the benchmarks!” all day long, but consumer know when we are being sold a lemon. If it can’t do the most basic of things at least as good as it used to, this is table stakes. Nevermind that if you can’t do the basic stuff, how on earth can you be trusted with more?

[gen220]

Actually anecdata I gather on my job from myself and coworkers is the only benchmark I trust anymore, because it so heavily diverges from the “benchmarks”.

[aspenmartin]

That’s your call just don’t expect anyone ever to take that seriously. It’s not like we don’t have exact evaluations like this.

[gen220]

I would encourage you to look into the open evals of some of these benchmarks (find one that actually is open-data, this is itself a good challenge), read the results generated and assess them for yourself.

This is what myself and my coworkers (and many other people in this thread) are doing on a daily basis with real stakes and real tasks – which these benchmarks are all aiming to be a proxy for. There's a real, tangible [cost]benefit to [not] using the highest-ROI models and harnesses.

The people with real incentives and skin in the game are telling you that the data diverges from "the data".

I don't mind if you don't take it seriously, our jobs are more important to us than a benchmark is.

But I wouldn't opt-out of using your own eyes and the eyes of others so easily, especially when there are literally hundreds of billions of dollars in invested capital with an interest in a certain outcome... this is how you end up in "Emperor's New Clothes" situations.

[recitedropper]

"Carefully and thoughtfully" is antithetical to the approach to benchmarks these days.

Maybe back when this was a scientific endeavor; not now when enormous, enormous amounts of capital are on the line. Along with an entire cult's chosen eschatology.

[aspenmartin]

You can call it a cult but it’s several thousand skilled workers who know what they’re doing, by and large, most of whom have a PhD and know how science and statistics work. Benchmarks are incredibly hard, and any PR or comms department at any company is going to obviously want to make things as rosy as possible, but beneath this are earnest, expensive efforts to get good quality measurements. The better you can do this the better you can compete. If you want to make a modeling decision you run an ablation, and the quality of that decision is only as good as your measurements.

[recitedropper]

The cult in this case is TESCREAL, not everyone working on AI. Last I checked not all the "several thousand skilled workers" in AI subscribe to TESCREAL ideology, although it has been a while since I've been to the Bay. Maybe things have changed since my time at Berkeley, and Dario's belief that he will eventually be made immortal by mind uploading is more widespread.

Otherwise we agree that benchmarking is hard, the benchmarks contain hard problems, and that there are many hard working people trying to accurately gauge what is going on. It is getting harder to watch though as all that is on the line taints the overall endeavor.

[OtomotO]

There is no data that I would trust that contradicts it.

Frankly I don't give a damn about data that could be made up on the spot or appears to be scientific or meaningful while it's not at all clear how it was made (up).

Claude was heavily lobotomised for my work starting somewhen in February.

I talked to friends and people I know and trust and many felt the same. (I didn't ask them whether they felt like I did, but what they felt, how happy they were with agentic coding etc.)

I quit my abo in March and talked to said friends who are still on a plan just last week: they are still not happy, but company pays so whatever...

[aspenmartin]

That’s ok but at what point is this getting into conspiracy territory? You have just said there is nothing you would believe to the contrary, but then by definition that’s not exactly a very thoughtful or insightful position.

[OtomotO]

I never said that I am not willing to believe the contrary.

I am not willing to believe the contrary from strangers on the interwebs or PR departments of companies who want to sell me something.

If people I genuinely trust tell me about their experiences, I am willing to try again.

But yes, if it doesn't work for me (for whatever reason, could be that I am holding it wrong), then I can accept that it works for everyone but me and still not use it.

Also "scientific" doesn't mean what it used to mean. When the n is small or it's just anecdotes (I am aware of the irony) blown out of proportion I really can't take the data and conclusions seriously

[pythonaut_16]

Seems like a bunch of noise. What does this even mean?

It sounds like you're saying "Actually you, as a human, are simply not smart enough to evaluate Opus 4.8"

[aspenmartin]

No it’s: evaluating these systems are complex and there’s a reason why sociology, cognitive psychology, medicine, etc are all done in careful double blind conditions with pre registered tests. It’s not that humans are not smart enough, as I said human evaluations are incredibly important. And yet they are a minefield of biases you have to worry about and correct for.

- evaluations need to be done at the same time to avoid drift in your bias

- you need to worry about your test set: which questions are you asking? How many of them? Are they representative of your work?

- which one did you do first? Raters have a tendency to bias in one direction or another

- you also know the label! You know which model is which! This biases your assessment…

And on and on and on. Careful science exists for a reason.

[BoorishBears]

"Fable 5" is Opus 4.7, and the Opus 4.7 we got is a Sonnet sized model on a stronger base.

That's where all the regressions and inconsistency in experiences stem from: RL can still only go so far vs having more parameters

[OtomotO]

Lol. If you're doing anything non trivial that's not a CRUD webapp but e.g. some physics simulation or high performance GPU code any and all models I've tried suck.

They are not just leagues behind what experts would code, they are not even playing the same game.

Which is to be expected, as there isn't so much physics or high performance gpu code available as there is for your typical CRUD API and JS frontend.

[rweichler]

I can attest to this, I had a very simple 20-line shader that I asked Claude to do a basic 90-degree rotation on it, and it just completely got it wrong. Frequently adds pointless abstractions / intermediate variables even when I tell it explicitly not to in the system prompt. I can go on and on, these things just don't understand architecture. And why would they? They were trained on text.

There is something remarkable about turning speech into code (don't need to hunch over a keyboard nearly as much these days, can just talk into a mic) and it's good for first drafts / exploring ideas. But it's obvious to anyone that's paying attention we're hitting the top of the S-curve. It's no wonder the IPOs are around the corner. I mean even Dario admitted he doesn't know how they're gonna substantially increase the context window size. That says a lot.

[rweichler]

That being said I think the harnesses are only getting better. And maybe we will get multi-modal models that understand architecture eventually. But the growing-the-blob-of-text training method that's being used now appears to be getting diminishing returns

[gruez]

I don't get it, your complaint is that they have catchy names rather than dry names like GPT-5.6? Does OpenAI hype their models less?

[Aperocky]

Oh, Far less.

It's getting to a point that it's offputting, and the next step would be to put it into "untrusted" bucket. Opus 4.7 already burned their credibility once, 2 more strikes remain.

[aenis]

Not my impression. I felt 4.7 was a regression, but I am again badly in love with 4.8 with the level of insights it produces in design discussions, and how long can it go unattended while producing spec-adhering quality code. There are problems it still can't solve well, from the edges of algorithmics and far from the mainstream, but for lots of stuff it is godlike.

Also, I dont think Boris C. is coming here for PR. He is a tech guy, and this is the best place for tech discussions. Why so cynical? The guy is an engineer.

[jwpapi]

I don’t even think that Boris is really just one person. He apparently vibe coded Claude Code and is responding on Threads, Twitter, HN and everywhere.

[guybedo]

They're good at marketing, but my first subjective assessment of Fable is that it's really smart.

I've been working with gpt 5.5 and opus 4.8 quite a lot, and interacting with Fable feels like a smart guy just entered the room.

[boc]

Yeah idk what people are talking about- it's not marketing. This thing is substantially better than opus 4.8/gpt5.5 from what I'm seeing today.

[iillexial]

>Hey! Boris from the Claude Code team!

>TOP 5 METHODS FROM BORIS ON HOW TO SPEND MORE MONEY ON TOKENS

>Boris from Claude just told he doesn't prompt anymore. He LOOPS instead

>"chatgpt has gotten soooo much better with the latest update."

>"codex is the best AI coding product and we want to make it easy to try."

Karpathy about Fable 5:

>"You can give it a lot more ambitious tasks than what you're used to, the model "gets it""

Sam Altman about gpt-5.4:

>In my experience, it "gets what to do"

What a time to be alive. Models are great, but all the slop, marketing, and fakeness around them is just unbearable.

[replwoacause]

Yeah, the marketing is cringe and it's a bummer that such a cool and powerful technology attracts such an icky group of enthusiasts. Surely, not all are bad, but man there are lots of goobers who are just AI-pilled hypemen who can't STFU about it.

[avaer]

If you truly believe this, you've discovered a superpower over everyone else in the industry.

While everyone else is wasting time and money on the slower, more expensive models, you've found a way to outpace everyone for less money. Everyone else is wrong and you will get rich.

(I don't actually believe the premise is true, I'm just pointing out the logical conclusion to what you're saying so maybe we can reconsider the premise)

[xyzsparetimexyz]

Thats not how costs work. You don't get rich off buying a €10 hammer that's the same quality as someone's €50 hammer

[atleastoptimal]

> At this point Anthropic is a pure marketing and PR company. Super catchy names like Opus, Mythos and Fable trying to get you to think that these software products are actually super-human

Lol anti-AI bias on HN is crazy. Simply giving your product a quirky name is now being considered manipulative advertising. Is just doing normal PR and marketing something AI companies aren't allowed to do?

[ausbah]

when they keep saying “oooh this new model is too big and crazy and totally can’t be released” or “this new model is a 10x game changer totally unlike our previous iterations” it feels sort like boy crying wolf. yes they’re still pretty clearly improving models, but when you’ve hit diminishing returns / more incremental gains and you’re still saying this is sounds like pure PR hype from a company that previously been the “honest good guys” in the room

[atleastoptimal]

Their model did find thousands of security vulnerabilities across the companies they previewed Mythos with via project Glasswing. Is it not sensible that, given that emergent level of capability, that they do this gated release structure, as all those vulnerabilities would be exploitable by anyone using a Mythos-level model?

[thefreeman]

How can you make this comment before even having a chance to try the new major model revision?

[piyuv]

Current AI hype is built on marketing and PR, not capabilities, and has been from the start.

I still remember Sam Altman “begging AI to be regulated” and AGI being “some thousand days away”.

Breed faster horses and hope one will birth a locomotive.

[system2]

You are right; all I noticed was a big-time slowdown. They increased the quota, but I cannot even reach the end of the day with these speeds. .NET coding somehow improved, though.

[WarmWash]

Don't forget the DoD stint that gave them this recent public boost.

Defy standard DoD precedent going back forever, that every other country has some form of too, and championing it like they are some kind of moral freedom fighters.

Like selling the DoD guns and telling them they can only shoot bad guys with those guns, and that you will be the one to decide who counts as a bad guy...

[MattGaiser]

Doesn't this suggest your use case is simply insufficiently complicated?

[reasonableklout]

I think this says more about your type of work than anything. For bugfinding/incident response in distributed systems - which often involves extensive use of Datadog/Sentry MCPs and poring over heaps of logs in addition to reading tons of code - 4.8 has been significantly better than 4.6.

[nozzlegear]

> Sentry MCPs

Oops, time to reauthenticate for the 10th time!

[xpct]

Indeed, hearing "Mythos-class model" felt very icky to me.

[b3kart]

https://en.wikipedia.org/wiki/Typhoon-class_submarine vibes

[mawadev]

When the Ai overlord is descending into pleb space to say Hi, you know stuff is real

[chis]

Hackernews not blindly hate on AI challenge: impossible