That's kinda hilarious. Pretty soon they might just ask people to write code themselves.

interesting, our enterprise account here in Australia doesn't have access to it yet.

Are corporate employees not allowed to use personal subscriptions?

I wonder if clues like this will be what are written in history books as the beginning of the bubble bursting.

> 2 months ago management was showing us scoreboards, praising leaders who used most tokens.

Everyone is insane.

Pro also makes you ask it to use sub-agents instead of just doing it when useful.

Hopefully, 5.6 will automatically spawn sub-agents without needing to ask.

For pro mode the agents worked independently and only when they all finished did a new agent take a look at everything to merge the work into a single response. The new thing involves subagents that have been trained to cooperatively pursue a task and are allowed to communicate with each other along the way.

How is this any different than what we have already? We've had this ability for ages (6+ months, decades in the AI world), you can literally today easily prompt CC or Codex to use subagents to accomplish tasks and they'll do it well. My entire workflow is one top level orchestrator chat creating tickets to dispatch to subagents to implement, and other subagents to verify. Why is this being sold as a new thing? Have HN users never tried tried asking CC or Codex to use subagents?

I imagine this is something like Anthropic's dynamic workflows where a JS file is created to make a little AI harness on the spot

i would believe this will be matched with something like orchestrator-focused model: https://news.ycombinator.com/item?id=48624782

https://archive.ph/NEwVz

"However, these inference optimizations, which rival Anthropic refers to as “compute multipliers,” are a big focus for all the labs. Anthropic CEO Dario Amodei has been publicly talking about the concept since at least mid-2023, when he said on a podcast that the company limits “the number of people who are aware of a given compute multiplier” because it could give other AI labs a leg up if they were to be able to replicate them. (Compute multipliers can also refer to efficiency optimizations in the model-training phase.)"

Yes, on a world with finite resources where your industry is singlehandedly siphoning ALL THE RESOURCES - hoard general efficiency optimizations and treat them as trade secrets - winning is all that matters, normal people and other species and the planet be damned.

Everything I hear about Dario these days makes me like him less and less. He sure did seem to speed run the 'tech leader with scruples' to 'tech villain' path! I guess all the cycles are compressing as we approach the singularity..

Semi-related, has anyone noticed their GPT 5.5 usage in Codex being cut in half as of a couple days ago? I got a lot more mileage out of my session usage yesterday for the same workload.

What’s the technique? And did they buy it from thinking machines?

Maybe you jest, but I'll bite.

> Tf is sol?

It's a proper noun: the name given to their latest and greatest model. Means "Sun" in Latin. Similar to how Anthropic has been naming its models Fable, Opus, Sonnet etc. Their other models are called Terra (Latin: Earth) and Luna (Latin: Moon) [0].

> Tf is ultra?

The name of the "harness" around the model. It'll use deeper thinking, subagents and all that jazz in response to a prompt. Other options include max, high, medium etc I suppose.

> Tf is codex?

"Coding agent" similar to Claude Code [1], something with a more descriptive name.

> Tf happened to descriptive nomenclature?

Something like GLM-4-32B-0414-128K (not made up [2]) doesn't quite roll off the tongue I suppose.

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

[1]: https://openai.com/codex/

[2]: https://docs.z.ai/guides/llm/glm-4-32b-0414-128k

Here's the correct link, not sure what happened with that first one https://xcancel.com/thsottiaux/status/2073933490513752151

It doesn't load. It uselessly keeps showing this in a loop:

> This process is automatic. Your browser will redirect to your requested content shortly. Please allow up to 0 second…

I would assume yes - their goal is to capture consumer subscribers. Claude are going to take Fable away, and they're going to swoop in and give it to us.

API pricing ends up being something like 20x more expensive for GPT 5.5 Pro than GPT 5.5 for actual work, even though the token cost is "only" 6x. On benchmarks where I've run both, I saw $1.12 mean per task with 5.5 and nearly $23 per task with 5.5 Pro, I guess it chews longer and harder on the problem.

If that's at all reflective of what it costs them to run it, I imagine they're in the same boat as Anthropic with Fable; they probably can't afford to offer it at subscription prices given current cost to operate it.

If 5.6 Sol Ultra has efficiency improvements (at one or more layers), and it allows OpenAI to offer a model that's competitive with Fable on the subscription plans, I'll guess a lot of folks will switch.

Fable is notably better than what came before. I watched it figure out stuff on its own over and over, on extremely hard problems, that I previously needed to guide a model to an understanding about, or work with them back and forth for several turns to figure it out together. Like, I've been reverse engineering a hardware device lately, and I've tried to tackle it a few times in the past with both some version of GPT and a couple of versions of Opus (most recently 4.7). In all cases, I barely made progress...would have gotten there eventually, probably, as I'm stubborn, but there were roadblocks constantly, with me and the models getting stumped and going around in circles in the end on every prior attempts.

Fable figured out other ways to find out what's happening, it dug into config files, found and extracted Boost-serialized data, compared that data to the observed behavior, built tools to compare the observed data with our emulated behavior, without being prompted. Would I have gotten there? Eventually, maybe. All prior models didn't; they mostly just tried the things I suggested and stopped at "well, that didn't work" or declared success after seeing results that matched their misunderstanding of the problem. I guess it's possible my prior attempts with other models had "loosened the lid" on the problem; we did already have a long list of documented "this didn't work" and a pile of tools for finding out if something worked. But, even so, I was impressed.

There probably will still be a "OK, let's rewrite this so it's not using lookup tables to precisely simulate the hardware behavior in software, because we don't need the noise, too" stage of the process...but, in one day with Fable, it solved a problem that I'd banged on for at least a week or too in the past with very little real progress. I don't think the models write exceedingly good code, even the best ones, but it sure does figure shit out quick.

I recently have been testing ChatGPT business at work and the quota seems to disappear almost instantly even using weaker models. Unless they dramatically increase their quotas it’ll be unusable.

many of us and myself have been using chatgpt pro from codex cli for months now

https://github.com/agentify-sh/desktop

Is it as good as Fable..? Fable is the first model that mostly writes without the AI slop format for me, and so I can comfortably actually copy and paste most of what it spits out.

OpenAI models have always been the worst in my experience for verbose, slop formatted responses, with each generation increasing in sloppiness.

https://xcancel.com/haider1/status/2073695124220006575#m

Check out LibRedirect or Predirect (MV3), it automatically redirects youtube, X, etc links to privacy-respecting frontends.

https://news.ycombinator.com/item?id=44344246

107 comments, 1 year ago.

Given that it is #1 on the front page now, people most definitely care.

Also, from the Guidelines:

> Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes.

You.