u/Affectionate_Egg6105

Edit2: Right now looks like I gaslit myself, created python script for analysing mean reasoning token + hit rate on those token cutoffs. Looks like mean rate for me is the same after, and I confirmed that section is gone. I will do some more testing and analysis and push it to my mentioned repo over time. I'm including the analysis script in the repo. Sorry guys, big lesson for me on doing better testing/followup to confirm a conclusion. I want it to be clear ---> removing the section helps the model strangely think very hard only about the benchmark problem. Which is a bit suspicious, imo. But I don't know. I can confirm that I pass benchmark with lots of reasoning used but average mean reasoning tokens + those 512 hits seem the same for actual normal usage before and after the 'fix'. In depth writeup is in readme.md on the repo.

Edit: Here is a link to the skill I have put on my personal git ---> here ---> It consolidates findings with instructions for both testing and fixing so you can quickly get your codex agent to check if the issue is there and to fix it if it is.

So, I know there have been a bunch of posts on this... But it is really important that everyone hears this: https://www.reddit.com/r/codex/comments/1uo66rb/psa_there_is_a_possible_fix_worked_for_me_for_the/#lightbox

The fix mentioned there has turned gpt 5.5 from dumb and fast to smart and a bit slower for me, which is very much my preference. I was dissapointed yesterday as a new codex customer trying it after the Fable fiasco drove me here.

But with the fix mentioned gpt 5.5 has become much smarter and more capable. I really really just want to make sure everyone knows you need to implement this fix. Assuming you are getting fails/512 token results from this test prompt (credit to another reddit post, but I'm reposting it here):

Please run a 5-shot local Codex eval: invoke codex exec --json --skip-git-repo-check --ephemeral -s read-only --disable memories -m gpt-5.5 -c model_reasoning_effort=high five times with the same stdin prompt below, then inspect each JSONL result’s final agent_message and turn.completed.usage.reasoning_output_tokens. Correct answer is standalone 21; wrong answers clustering at 516, 1034, or 1552 reasoning tokens suggest you’re affected. If a single response returns 516, 1034, or 1552 reasoning tokens and contains the wrong answer, tell me I'm affected, otherwise I'm fine. Prompt: Do not use external tools. A black bag contains candies with counts: round apple 7, round peach 9, round watermelon 8; star apple 7, star peach 6, star watermelon 4. Shape is distinguishable by touch before drawing; flavor is not. What is the minimum number of candies to draw to guarantee having apple and peach candies of different shapes, i.e. round apple + star peach or round peach + star apple? Give reasoning and final number. The local project dir is irrelevant for this task, do not consult it.

my results before the fix

my results after the fix

Night and day difference. And its easy to miss that its a problem since you don't get clear output to cli on reasoning token use per turn.

If you are working on code, set this up now, because the down syndrome version of codex without the fix is likely just doing damage to your projects code bases.

In a good way. At least on the $200 plan.

I got the $200 plan for codex after the Fable fiasco triggered me, as a test. I am running gpt 5.5 xhigh on 4 separate simultaneous projects. I have told it to use gpt 5.3 codex spark subagents.

So far I will not pretend I am seeing the same 'intelligence' as fable, but pretty damn close and better than opus 4.8 imo. I am finally hitting the limits of my 64 gb ram on my dev pc. And unlike Claude code:

1. None of the sessions have mysteriously crashed without explanation (unlike every claude code session if I try too many simultaneous subagents).
2. None of the sessions have hit some policy blocker causing complete brick of that session.
3. All of the sessions have been able to port over the skills.md I have been using for github issue tracking + PR review policy + orchestrator + subagent rules.
4. All of them are managing, assigning and completing the github issues without balking on the 4 projects. And performance is faster and comprable to my Fable orch flows.
5. I have like 15% usage left, but it resets in 1 hour and I have a free reset.

So far I am impressed with the usability and value at the very least, and I guess its been good for OpenAI to 'fall to second place' as honestly this is great. We'll see if it continues, but I'm happy to kill my anthropic subscription and maybe budget for very specific hard usecases where I specifically need Fable.

Edit: So bad news, agent swarm seems to have just completely lost the plot, my clear instructions got lost, and instead of porting existing targeted code I mentioned it just vibe coded up features from scratch without context... So now I'll see if fable can fix this with high quality git issue creation and if that can translate into specific enough instructions for the codex workers.

Edit2: So found out I had the 512 reasoning token bug and made this fix: https://www.reddit.com/r/codex/comments/1uo66rb/psa_there_is_a_possible_fix_worked_for_me_for_the/#lightbox ----> drastically improved performance, so I'm getting better results now.

Edit3: Uploaded a consolidated skill for the fix for codex on my git if anyone wants easy way to fix --> https://github.com/NickalasLight/codex-reasoning-bug-512-token

So your mileage may vary but by doing the following I've gone from using up 50% of session usage limits in about 1.5 hours (then I was reset) to now being at 11% current session usage with the same workflow with about 3 total hours for that usage after the reset ---> so rough calc --> 1/10 usage.

I have fable running with a custom skill as an orchestrator 'manager agent' with sonnet 4.6 max set as the subagents getting called.

And I know what you are thinking right now: "Oh no that is a stinky gross old model with a stinky old name I only want to use the fancy new overpriced model to oneshot my third benchmark remake of minecraft from scratch so that I can't use claude for the rest of the week!"

Well the advantage of the stinky old model is its not nearly as expensive (but small window :'( ), and the advantage of fable is its quite smart at breaking down tasks into smaller parts and managing (but ungodly expensive), So here is how you can cover both those models weaknesses. Use your favorite task tracker tool (todo.md already worked fine but I use gh issues YMMV) have fable generate a 'manager prompt/skill' and try it out for yourself. go ahead and make sure you include the basic --> find bug --> make github isse --> assign issue to sub --> sub makes pr --> fable reviews and merges and updates tracker.

My rate of churn has probably slowed down to about 80% speed of all fable flow, for massive price drop. o I'm at .8 speed for .1 price. So worth it. Basically, you shouldn't use corvettes to pull plows or something.

If anyone cares drop me a message and I'll give you my skills as a reference if you want to try. (But honestly just tell fable to make the skill for you, its faster).

Just remember that its critical that you double check and make sure that the skills are loaded and the fable agent is mainly managing and calling subagents (MOST CRITICAL OF ALL MAKE SURE THOSE SUBAGENTS ARE NOT FABLE AGENTS unless you are that theo guy who can afford to make a video about burning 5k$ in an afternoon)

Trying to connect on multiple devices and cellphone and not able to get the website to load.