11–20 of 47 posts
Fable will do this itself, by spawning Opus/Sonnet subagents to do easy work.
I exclusively use sonnet and advisor is basically “hey opus chime in on my approach”. been working great as far as i can tell.
Fable will do this itself, by spawning Opus/Sonnet subagents to do easy work.
GPT 5.5 xhigh is better than Opus and Sonnet.
Reduce Fable tokens by 80%, simply by not using it! > I am fairly convinced this is the shape serious agent work keeps converging toward. "this" being "plan with expensive model, implement with cheap model". Anyone who follows HN would be hard-pressed to disagree; this architecture is re-invented twice monthly. https://www.facebook.com/groups/vibecodinglife/posts/1946207... https://github.com/openai/codex/discussions…
wow linking a facebook groups post might actually be worse than x, is there an xcancel alternative for facebook?
Last night I switched back to Codex for a minute having burned through my tokens for the week with Fable and oh boy I had a terrible experience. Running in circles over simple problems (which I ended up solving myself, like a peasant) and running "terraform apply" several times despite several instructions all over the place to never do that. The performance difference was stark.
Could you provide some details, if possible, like what model & thinking effort, what kinds of tasks? I used to swap between Claude Code and Codex often, and these days use Codex more because of the usage limits. Wondering if I should go to Claude for a month, I get a strange FOMO when I read vague comments like this. The one major difference I noticed is that the GPT models are more analytical (e.g. better at mathema…
I was using gpt-5.5 high. Writing terraform code for GCP, debugging app launch and Dockerfile issues, that sort of thing. It was going in loops hallucinating features of GCP, looking things up in strange ways, running terraform apply after being explicitly told in the last interaction not to, and overall not solving problems. These were very straightforward tasks and it couldn't be trusted for five minutes. It's the difference in what I would trust an early senior engineer to do vs what I would trust an unreliable high school intern to do.
Earlier quoted context omitted.
GPT 5.5 xhigh is better than Opus and Sonnet.
I don’t know why you’re getting downvoted. It’s true. Averaged across a wide variety of benchmarks Fable is the only Anthropic model that performs better than GPT 5.5 xhigh.
I am a GPT 5.x booster since to me it just feels smarter, and I generally felt like the benchmarks backed me up, but it's not every benchmark, so sadly we're mostly arguing about vibes.
SWEBench-Pro was a big one, though apparently Claude was reading solutions out of the .git folder it wasn't meant to have access to among other problems.
> Each rule below is enforced mechanically by the skill, not left to vibes.
> R1. Repo docs are the memory; not in HANDOFF.md = didn't happen
SKILL.md:
> Not in docs/HANDOFF.md = didn't happen. Refuse to judge results that exist only in conversation or builder chat output.
"Mechnical enforcement" just means "prompting the LLM a bit extra" these days? It (still) amazes me how much effort and tokens we expend on what could and should be a two line script...
Earlier quoted context omitted.
I don’t know why you’re getting downvoted. It’s true. Averaged across a wide variety of benchmarks Fable is the only Anthropic model that performs better than GPT 5.5 xhigh.
The problem is that there are a bunch of benchmarks, the model providers often don't even use the same benchmarks, a bunch of them have known problems, and it's expensive to do your own benchmarks. I am a GPT 5.x booster since to me it just feels smarter, and I generally felt like the benchmarks backed me up, but it's not every benchmark, so sadly we're mostly arguing about vibes. SWEBench-Pro was a big one, though a…
I’m currently working on two projects/clients one using Claude, one using Codex. I have a strong preference for the latter, but not because I think it is much more intelligent or writes much better code. It is simply because I find the way of interacting with it more pleasant: more literal, mechanical, makes fewer assumption and or double checks, and is less proactive in my experience. At least until some updates over the last few weeks.
Reduce Fable tokens by 80%, simply by not using it! > I am fairly convinced this is the shape serious agent work keeps converging toward. "this" being "plan with expensive model, implement with cheap model". Anyone who follows HN would be hard-pressed to disagree; this architecture is re-invented twice monthly. https://www.facebook.com/groups/vibecodinglife/posts/1946207... https://github.com/openai/codex/discussions…