Oy. We are aware that some Codex users are experiencing high error rates with "model at capacity" and are working to bring things back to being stable.
status.openai.com
Oy. We are aware that some Codex users are experiencing high error rates with "model at capacity" and are working to bring things back to being stable.
status.openai.com
Karpathy said something you'll regret ignoring:
"Remove yourself as the bottleneck. Maximize your leverage. Put in very few tokens, and a huge amount of stuff happens on your behalf."
Loop engineering is the exact thing that does that.
In a hand-run session, the operator handles two things:
- deciding what the agent runs next
- and checking its output before the next step
Both are manual, and both decide how far the agent gets on its own without the operator.
Loop engineering moves both steps into the system.
A core operating structure surrounds the loop, and the diagram below depicts it.
- A schedule decides what to run
- Loop is the maker that produces the work
- A separate checker agent grades the output
- A file on disk holds the state they both read.
The loop runs until either done, max iterations, or an exhausted budget.
Here are some practical engineering considerations:
1) A model grading its own output justifies what it already did instead of catching where it failed.
That's why a separate checker's findings return to the maker as the next instruction. And the cycle repeats until the checker finds nothing left to fix.
2) A loop with no stop condition burns tokens, and the cost climbs fast once sub-agents and long runs add up.
That's why the exit must be set before the loop runs, not while it is running.
A simple exit could be:
โณ fix only the major issues, run one final pass, and stop after two loops, with "all tests pass and lint clean" as the rule that ends it.
3) State has to live on disk, not in context.
The model forgets everything between runs, so an MD file or a knowledge graph holds what is done and what is still open.
Each run reads it and writes back to it, which lets a loop pick up again after days.
4) The lower the verification bar, the safer the loop.
Boring, repetitive checks like a stale version string or a missing test are trivial to verify, so a loop runs them with little risk while the operator is away.
Judgment-heavy work is loopable too, but only as far as the checker can confirm the result.
Let's look at how an unattended loop fails in two ways.
1) It reports done when nothing is actually verified.
The separate checker exists to prevent it, but it merges code faster than anyone reads it, so over weeks, the team stops understanding its own codebase while every check stays green.
Green tests say the code passed the tests, not that anyone knows what shipped. Someone still has to read what the loop merges.
2) The checker keeps a running loop honest, but it only catches failures inside a run.
The harness around the loop, like the prompts, tools, and checks wrapped around the model, still drifts and breaks in production as models change.
That repair loop is usually run by hand based on observability traces.
My co-founder wrote a detailed walkthrough (with code) on making that harness repair itself, where a failing trace gets diagnosed, the fix is verified against the exact input that failed, and the failure is locked as a regression test so it cannot recur.
Read it below.
Heard your (amusing) feedback that it was at times annoying to receive a reset of your Codex usage without warning.
Next time we press the button you will get to choose when it actually applies. Happy codexing.
We heard you wanted to use Codex rate limit resets on your own time.
Starting today, weโre rolling out the ability to save rate limit resets to use later.
Weโre starting Go, Plus, Pro, and Business users with one free reset:
For the next two weeks, Plus and Pro users can invite up to three friends to try Codex.
When a friend sends their first Codex message, youโll both get another banked reset.
what if i told youโฆ
hello sammy
if you havenโt figured out by now that they have a model waiting to crush fable on thursday i canโt help you.
it will be cheap, it will be fast, it wonโt be gated.
enjoy chat. have a great wednesday.
60 Followers 500 FollowingPremium web templates, frameworks & components
Built for developers, designers & indie founders
๐ Building UIXTRA in public
๐งฉ Free & paid products
588K Followers 51K FollowingSan Francisco/Silicon Valley AI | Robots, holodecks, BCIs, analysis of new things | Ex-Microsoft, Rackspace, Fast Company | Wrote eight books about the future.
3K Followers 3K FollowingAuthor + AI
Worlds first typo infused Author โ๏ธ
I speak my truth, write my thoughts, and vibe code my ideas into existence.
0 Followers 2K FollowingSystem Engineer | Network Architect | I design infra, automate workflows, and build AI agents that solve real business problems.
350 Followers 1K FollowingApp developer specialised in Artificial Intelligence (IBM Academy alumni)
Also pro musician graduated from Music Academy International.
Digital Audio Producer.
459 Followers 3K Followingveni, vidi, vici...
Cloud Er, AI & Blockchain enthusiast;
Generalist: Jack of all trades;
Gym, rap, F1, anime, chess, investing....
569K Followers 60 Following20 years of covering Microsoft, Windows, Xbox, and PC gaming. Tips: [email protected] | Gaming: @WinC_Gaming | Not part of Microsoft.
87K Followers 2K FollowingDesign @Cursor_ai. Early @NotionHQ, @Stripe, built startups. I make a world where anyone can make software. Aspiring k-pop idol.
464K Followers 1K FollowingML/AI research engineer. Ex stats professor.
Author of "Build a Large Language Model From Scratch" (https://t.co/O8LAAMRzzW) & reasoning (https://t.co/5TueQKx2Fk)
1.2M Followers 787 FollowingProfessor at NYU & Executive Chairman at AMI Labs.
Ex-Chief AI Scientist at Meta.
Researcher in AI, Machine Learning, Robotics, etc.
ACM Turing Award Laureate.
14K Followers 0 FollowingHigh-performance developer tools for the Python ecosystem, starting with Ruff, an extremely fast Python linter, written in Rust.
161K Followers 6 FollowingStitch by @GoogleLabs turns your ideas into beautiful interface designs, powered by some of the latest Gemini models. Try free of charge.
40K Followers 5 FollowingThe home of the vibe coding movement.
Founded by @matthewmillerai. 86K+ on YouTube.
Building to $1M in public. https://t.co/wRtHrQNvA8
62K Followers 396 Followingai, chips, systems engineering, infra & hardware ยท on a mission to build a frontier, infra-first AI Lab in the West ยท i mod GPUs on r/LocalLLaMA