[aarvin_roshin]

Thoughts[^0] from Theo, who had early access:

> It's a damn good model. Not quite as "smart" as Fable, but it is incredibly capable. Fixed all the problems I had with GPT-5.5.

> It is incredibly determined. Will run for a day without even using a /goal. It understands subagents incredibly well and is great at orchestrating. It's super pleasant in use cases like OpenClaw and Hermes Agent. It knows iOS dev incredibly well.

> It has rough edges too, but FAR fewer than 5.5 did.

> For many things, gpt-5.6-sol will become my obvious defaults.

> It is better about [following instructions] than 5.5 was. Understands intent well and hammers until it gets there. Sometimes a bit too hard.

Also[^1]:

> gpt-5.6-sol is world leading in computer use. It made me use it 100x more. When we lost access to 5.6, I quickly started to go insane without it

[^0]: https://nitter.net/theo/status/2074708892341481755 [^1]: https://nitter.net/theo/status/2074720467395756499

[bashtoni]

I feel like listening to Theo about anything technical is like consulting a Labrador retriever for advice on quantum physics.

Every time I've ever seen one of his videos it's pretty clear he has very little understanding of development or engineering. I first became aware of him from his early "unit tests are a waste of time" stuff, and it seems his skillset is building a personal brand. Fair play, he's clearly talented at that, but that doesn't make his opinion on anything else worthwhile.

[patates]

> it's pretty clear he has very little understanding of development or engineering

I cannot prove it but I have a feeling that you may be conflating "he clearly has different opinions on things I consider non-negotiable" to "he doesn't know what he's talking about".

I also watched a lot of his videos. I wildly disagree with him a lot of times, but he has his reasoning, and I can see (and verify!) that those ideas are coming from an engineering perspective.

[esperent]

The problem is that he's a tech influencer first, a tech expert second.

That's his motivation, influencing. Not teaching.

I'm not so against him as the previous commentor but I feel basically all YouTubers who have succeeded in building a brand have the same problem. They have to present their opinions as unassailable truth, they can't allow nuance. Within reason of course, they also have to play the game of appearing considerate and understanding of other people but it will always boil down to proving they are the real experts, their ultimate goal is always to get you watching more of their content.

If they don't do this, they appear less trustworthy and their brand wouldn't have grown as much as it did. They might genuinely have some expertise to share, and even contrary or downright wrong takes could teach us something if they were only presented in a way that encourages critical thinking. But as the person above said, their real deep expertise is in brand building.

[0dayz]

I sort of disagree, the issue is that he like so many professionals (prime agent, being the other) becoming youtubers uses their experiences to make their opinion the only opinion when said opinion is nuanced or plain wrong objectively.

[patates]

No he usually acknowledges other opinions (including the ones that I share) and tells from his perspective why they are wrong. It feels condescending when you see a face on screen, roasting what you think is right, but I personally could get over it and learn to take the bits that challenge my ideas.

Of course, youtube isn't interactive and when you see something that you think is objectively wrong, your options are writing a comment nobody will read or ignoring it, which is frustrating, but that, in my opinion, doesn't discredit the content producer itself.

[satvikpendem]

You can make a counter argument video, which I've seen done, and then sometimes the original YouTuber will reply or collab. This happened when Theo had some truly awful takes on Flutter while knowing nothing about it, a prominent Flutter dev replied rebutting each point made, then they both collaborated to make a video where they switch technologies for a few hours to build something, and it was enlightening for both parties.

[steve_adams_86]

He's clearly very knowledgeable about some things, but I think he has harmed his credibility be becoming a 'tuber who prioritizes thumbnails and hot takes over engineering.

[satvikpendem]

Not really. If you're a YouTuber it's necessary to follow the algorithm which includes making such a YouTuber face, clickbait actually works and has a direct financial correlation as Linus Tech Tips has shown.

[steve_adams_86]

That’s fine, but I trust him to play the YouTube game as a result, not as an engineer.

[incrudible]

If you are a competent engineer already why do you need to create self demeaning clickbait content on YouTube? Narcissism? I aggressively block any such content, because if you click on any of it, you easily get sent down the YouTube spiral of crap.

[satvikpendem]

One can be multiple things. That you find it demeaning is your personal opinion and frankly is more a reflection on yourself. There are many like Casey Muratori that are competent engineers as well as YouTubers.

[patates]

> he has demolished his credibility be becoming a 'tuber who prioritizes thumbnails and hot takes over engineering

I don't agree that he has demolished his credibility. I also dislike the youtube face and sensationalization but I personally don't hold it against him, given the Youtube algorithm.

Regardless of his style, I like hearing the take from an engineer who's working in a different country/culture and has a completely different perspective.

edit: it seems you changed "demolished" to "harmed". I still don't agree but it reads more defensible IMHO, thank you.

[torginus]

He has big 'theatre kid' energy (at least certainly had, watched him years ago) - he desperately wants to make clear that there's a group of cool kids and he's in it.

His youtube channel used to be about talking about the new FOTM Javascript framework/technology - not presented as 'here's a cool thing, let's check it out' but 'everyone worth a damn already uses this, get with the times grandpa'

[satvikpendem]

"Average Theo video be like": https://youtu.be/h1p9zdUtUdo

It's shocking how many accurate tropes this hits.

[zarzavat]

There's a simpler explanation. Social media rewards surprise and hype, not truth. Don't expect objectivity from someone who gets paid by the view.

[Havoc]

And half his videos are him coming up with indirect ways of saying look how amazing I am.

[scotty79]

It's curious how so many people get triggered by a smart person saying what he believes to be true. Yes, he is pretty amazing. Yes, he is rarely wrong. No, it doesn't affect you or me in any way because he is not in competition with you. Go do something else if you don't enjoy his takes.

I don't get many programmer influencers in my feed that deal with newsworthy relevant stuff. Theo is the least wrong and most humble one in my perception.

[ttul]

I disagree with this assessment. Theo is nerdy and, yes, he has a healthy ego. But, he provides insightful commentary on his channel and he works very hard to present what he believes is the truth. Compared to many YouTubers, whose content is vacuous, Theo is mostly the real deal.

[ttoinou]

There is a whole religion about tests that is worth attacking though

[bashtoni]

Sure. If his take was "100% unit test coverage is a waste of time" I think that's not unreasonable. You could make a case that the "you must write tests before you write code, every single time!" stuff is needlessly dogmatic. I also think that sometimes people focus too much on unit tests to the detriment of end to end tests that better model actual system interactions.

None of these were Theo's take. He was pushing the idea that unit tests in general were a waste of time because you could be shipping new features instead.

https://www.youtube.com/watch?v=pvBHyip4peo for an example of this. The nicest possible interpretation on this is that he's deliberately saying something he knows is wrong to attract attention.

[theshrike79]

Tests before code makes sense when fixing bugs. Red-green specifically.

1: get bug

2: write tests that should work, but don’t because of bug

3: fix bug

4: confirm fix by running tests

Makes things a LOT easier for people checking the PR, they can just confirm the tests are correct pretty much.

As a bonus the same bug can’t surface again.

[bashtoni]

Yep, I'm in full agreement. When extending functionality of some already existing code it also generally makes sense to write tests first.

I think the value is much lower (maybe even negative) when you're still trying to work out what shape the code will take, in an initial implementation.

Of course, as others have pointed out, nuanced opinion doesn't get clicks or YouTube views.

[ttoinou]

Oh I do that naturally as my rational problem investigation. Sometimes you can’t write a test for that, you need to test it yourself

[scotty79]

He doesn't believe that unit tests are complete waste of time. Just a relative waste of time. He doesn't mind AI agents writing tests. It's just mostly waste of time for humans. Because the value you get for them is not worth developer time in most cases. It's worth agent time.

[ah1508]

When I start using a chainsaw or a car I hope it has been tested (!) Without tests before delivery the one who tests is the end user. Disaster for a unreliable chainsaw, very unpleasant for a software.

But you're right, the goal is not to write test but to ensure delivery of a reliable software. However each software is a prototype, something that has never been made before (unlike a manufactured car or chainsaw) so the customer must be ready to some unexpected behaviors when the software is released.

Since tests are often sloppy or does not cover every edge case, I see a real value for GenAI. It also forces to write good spec: very clear about inputs and the invariants for each use case. I think that AI (especially GenAI) should first be a solution to existing problem, lack of tests and good specs is often one of them.

[ttoinou]

If you write too many preconditions, postconditions, invariants etc. Then you cement your software and you will spend most of your time on the tests rather than on the actual useful software

[pdantix]

i already found his clear shilling of nextjs a bit distasteful, but his whole gpt-5 thing really just made it clear he's just not worth listening to.

[isoprophlex]

Increased tenacity & goal following is exactly what I want in this model, to make it compete with Claude models.

(A little toning down of the goblin fetish would be nice too, haha.)

[jeswin]

> Thoughts[^0] from Theo, who had early access:

I looked at his YouTube, and found a stream of industry gossip and beginner content like "web dev tutorials". I have nothing against such content and it may be useful and good fun to watch.

But does that say anything about this particular model? People have been using models effectively for web code since Gpt 3.x.

[jychang]

> Not quite as "smart" as Fable, but it is incredibly capable.

THIS IS BECAUSE GPT-5.6 SOL IS... just a more posttrained version of GPT-5.5, not a brand new bigger model than GPT-5.5. It's not like how Mythos is bigger than Opus.

OpenAI switching to Sol/Terra/Luna renaming is just a way to rip off people and charge more usage for the same sized model.

GPT-5.6 --------> GPT-5.6 Sol

GPT-5.6-mini ---> GPT-5.6 Terra

GPT-5.6-nano ---> GPT-5.6 Luna

Except OpenAI is about to advertise GPT-5.6 Sol and GPT-5.6 Terra as a whole tier better, than if they named it GPT-5.6 and GPT-5.6-mini.

[threatripper]

My feeling is that GPT-5.5 doesn't lack the raw intelligence so much as it lacks "methodology". I don't know how exactly to put it... how to approach a problem, how to take care of the details and side effects, how to handle unexpected difficulties and bugs, how to not spin out of control, how to write solid code, how to clean up afterwards, how to document, how to give useful feedback... the things that you learn on the job.

So, if they improved a lot in those areas, then GPT-5.6 could become a lot more useful compared to GPT-5.5 even though it might score lower in many benchmarks. It's possible but unlikely since their approach was mostly brute force in the past.

[gck1]

Is Fable really that much different? I almost instinctively create elaborate processes, workflows, set up a bunch of linters and dump research docs any time I bootstrap a new project regardless of what model I'm using. They all spiral out of control if they're not following a predefined process.

[theshrike79]

(Based purely on my feels of using both daily since forever)

Claudes are more creative and get shit done, suggesting and implementing stuff you didn’t ask for but actually kinda needed. Will leave gaps and bugs though. More of an artist, communicates a bunch during the dev process too.

GPT is the engineer, given exact specs it’ll disappear into its dark corner and putter away at doing exactly what was asked, nothing more nothing less. Very very good at spotting gaps from Claude’s get shit done code.

[satvikpendem]

Yes it is. With Fable you don't need to create any sort of elaborate process, it seems to understand the user's intent much better than Opus class models.

[solenoid0937]

There's been a ton of discussion on HN about this but yes. It's a totally different level from Opus.

[Topfi]

Very. Fable 5 is incredibly efficient token wise, second only to GPT-5.5 and is far more affordable run-to-run than the pure input/ouput costs would suggest. Task adherence, task inference, tool calling and task assessment are all significantly ahead of GPT-5.5, especially as the later strongly degrades the second compaction comes into the mix, I suspect because of OpenAIs obsessive optimisation of reasoning tokens into a hard to read (and thus also hard to compact) mess.

Fable 5 meanwhile has a reliable 1m context window and compaction that the few times I did eval it does also do well. Not quite as easy to trust as GPT-5.4, but that's mainly because with thats 272k context window I simply got more familiar with GPT-5.4s incredibly dependable compaction.

Purely concerning encoded information wise, Fable 5 is near or on the same level as Gemini 3.1 Pro in my limited test set focused on those tasks, which in very niche cases can make a difference even with coding, but the truest advantage for coding assistance (besides frontend/UX) is that the code Anthropic models provide is more parsable. Hard to explain, but I can read, follow and mentally map Fable 5 (and even Opus 4.5-4.8) output far more than GPT-5.4 or GPT-5.5 code.

Task orchestration and (more importantly) knowing when to recommend against using such vs Opus 4.8 is another strength of Fable 5 I've use liberally, there is an understanding of what a tasks requirements and the most optimal setup for success are, I have not yet seen before. Computer use is also solid, albeit not as token efficient as GPT-5.5 for my limited use cases.

Lastly, I will say that the classifier has become far less intrusive for me compared to the initial release. During the previous launch window, on Claude.ai I triggered the classifier for simple frontend tasks for regular (not security vocabulary containing) webpages. Now that is no longer the case. Inside Claude Code I occasionally triggered the classifier previously, but after the re-release, I only managed one, even when working with a privacy focused section of the code base containing a significant number of code comments with security and privacy focused wording. That one instance was rectified quickly by trying again, so I really am having a hard time following how others experience the issues some describe. I do have routing to Opus 4.8 without confirmation by me deactivated too, simply because I want to know if it ever happens, so it's not that I missed reroutings.

That all being said, we are still far from a stage where I'd not want to review the output, but yes, I do rate Fable 5 very highly. GPT-5.5 can have a similar ceiling but long horizon has become less usable over GPT-5.4 and in either case, parsing their output is (far more) of a chore. Maybe post training can address some of this, hopeful on the compaction front myself. Also interested in what happened to OpenAI models on AWS Trainium, I was expecting that to be a major boon for their commercial adoption, but haven't heard anything since then...

On the post training front, I am still hopeful that the Gemini team can finally get tool calling and task adherence to an acceptable level as we do need every competitor possible and purely considering the information density the model was trained with, they have great potential.

[deadlast2]

I use Open AI and Claude a lot right like a lot everyday for hours multiple hours. Open AI gives much more value for money than Claude much more I'd say x 10. Mainly I use it for writing fiction books and literally Claude is locked 90% of everyday trying to jip me for tokens. It's not as good at coding for what I do which is a very complicated application. However it is very good at writing it's really good which is why I keep it right but over 90% maybe actually all of my work except the initial draft of a chapter is done by open AI.

[CorbenDallas]

God save us from these ai generated fiction books.

[ppaattrriicckk]

> OpenAI switching to Sol/Terra/Luna renaming is just a way to rip off people and charge more money for the same sized model.

Excuse me, but what are you on about?

Unless I'm mistaken, they have literally(1) stated that it will cost $5 per 1M tokens in, and $30 for 1M output tokens. The same as GPT-5.5.

[1] https://openai.com/index/previewing-gpt-5-6-sol/

[whs]

Sounds like the same problem as condom. Nobody want to buy the "mini" size.

[Davidzheng]

Post-training can have big gains no? I don't think the current sizes at ~1T are saturated in intelligence (it's like saying AlphaGo Master is just a post-trained version of AlphaGo Lee)

[behnamoh]

OpenAI already has a Mythos level model, it's called GPTCyber and before that, it was called gpt-5.5-pro.

[andy12_]

No, GPTCyber is specifically trained for cybersecurity, and GPT-5.5-pro is just an ensemble of many subagents, not an actual model.

Mythos is simply a much bigger model in terms of parameters and I don't think OpenAI will have anything of its size anytime soon (My theory is that OpenAI had given up on scaling up parameters after GPT4.5 flopped).

[behnamoh]

how do you know gpt-5.5-pro is an ensemble? if it is, then how did OpenAI do it? why no other company has been able to pull it off?

[andy12_]

It's pretty much confirmed by OpenAI here [1].

> We generally treat GPT-5.5’s safety results as strong proxies for GPT-5.5 Pro, which is the same underlying model using a setting that makes use of parallel test time compute.

And Gemini also provides something similar. Gemini Deep Think models are pretty much the same thing [2]. As to why no other company uses this, I don't really know. Maybe compute constraints?

[1] https://deploymentsafety.openai.com/gpt-5-5

[2] https://deepmind.google/models/gemini/deep-think/

[jychang]

Plenty of other companies do this. Meta Muse Spark has a "Contemplating" which is this. Kimi had this on their website too, IIRC.

[behnamoh]

Interesting, but how do they "combine" the results of all those parallel agents? How do they know which parts of each agent response is signal vs noise?

[mejutoco]

What is the language of those words (sol, terra, luna). It does not seem to be a single language.

Spanish: Sol, tierra, luna

Italian: Sole, terra, luna

Catalan: Sol, terra, lluna

Portuguese: Sol, terra, lua

Might as well call it gelatto, siesta, fiesta if they think it sounds cool.

[jobigoud]

As you may have guessed, it's Latin.

[satvikpendem]

I wonder what those languages all stem from...

[adammarples]

What a tantalising mystery there is here waiting to be solved!

[mejutoco]

Honestly, I speak a few languages and it did not ocur to me. I deserve the snark, but downvotes?

[ingve]

Latin.

[xyzsparetimexyz]

This guy is enthusiastic about everything. Not a great benchmark

[satvikpendem]

That's sad to see Sol not beating Fable as it was explicitly stated by OpenAI that Sol benchmarks and overall performance were better than Fable.

[zuzululu]

here is the original x post

https://x.com/theo/status/2074708892341481755

5.6 sol seems to hit a lot of the gaps with 5.5

sucks its not "mythos" but i will take it

[Copenjin]

> Thoughts[^0] from Theo

I will stop here, sorry but I think we have limited time to listen to opinions and nowadays since they are abundant on social media we should give preference to the substantiated ones.

[nullbio]

Next up: Thoughts from an OnlyFans model.

[stingraycharles]

“Understands intent well and hammers until it gets there. “

If there’s anything I learned over the past 12-18 months is that this is a recipe for disaster, except for throwaway stuff.

I thought most senior engineers settled on the fact that steering a model yields much better results?

[hodgehog11]

For some tasks, there is no amount of "steering" that will produce sensible code. The model needs to be sufficiently capable as a baseline; this is the "intent" that people are referring to with Fable.

[stingraycharles]

That doesn’t sound like the “it hammers until it’s done”-type of intent.

Just last night Fable decided to get into a rabbit hole of debugging a database driver issue by packet sniffing the network traffic instead of just adding debug statements to the code. Definitely needed steering, and I don’t know many people whose first intuition would be to use pcap when they have a segfault.

[hodgehog11]

Overengineering is the name of the game with Fable. Sometimes you don't want that, sometimes you really do, especially as a researcher. It's a very nice tool to have around for those special tasks.

[oefrha]

I wouldn’t call it a recipe for disaster, but oh boy if you leave an agent that “hammers until it gets there” on its own with an underlying bug in a dependency…

[icepush]

It's very possible that would be the best strategy over the last 12-18 months and now that this is released it is no longer the best strategy.

[stingraycharles]

That would be an extremely massive leap if agents could suddenly make nuanced architectural decisions and prevent technical debt.

In my experience even Fable still requires guidance (although the options it provides are generally better).