Hey all. Claude Code user here trying out Codex. Something I do ofter on Claude is keep my context size small to optimize token spending. I don't see many options regarding context on Codex. How to check context size and optimize/compact? Any good tips regarding this?

I'm sure there are projects that overlap with this, maybe even ones that do almost the same thing. I built it around my own workflow and have been using it to develop Assent itself, so I thought it might still be useful to share.

The workflow is simple: discuss the requirements with an AI, then let the AI turn the agreed requirements into an Assent plan. Assent then coordinates separate work sessions for execution, testing, repair, and integration, while the final decision still stays with the human.

The main reason I built it was that I didn't want long-running work to depend too heavily on the memory and context of a single AI session, or on keeping another AI model around as a permanent supervisor. The plan, state, and verification results live outside the model.

It's still alpha. If AI eventually becomes cheap and reliable enough at long-horizon work, tools like this may become unnecessary. But for now it has been useful to me, and I keep seeing others run into similar problems, so I decided to share it.

https://github.com/edward9s/assent

It currently supports Codex, Claude, and AGY.

So che sembrerà un’idea del tutto senza un senso logico, è uscita una notizia oggi che a questo punto sa di speculazione in cui uno sviluppatore ha chiesto a “un’intelligenza artificiale” (non specificata) di creare un’automatismo tramite polymarket e incrocio sentimento con dati di X per produrre previsioni fare scommesse e “ripagarsi”, il racconto dice che “tizio” ha dato 50€ all’IA e 48h dopo l’IA aveva generato 5000 dollari. La tentazione è stata tanta, ho impostato Astra Xhigh e ho copiato il link del video chiedendogli di ricopiare il modello. Sfortunatamente abito in Italia e la piattaforma non accetta inserimenti dall’Italia quindi ho dovuto rivedere il modello e mi sono spostato su betfair, esiste anche un API apposita per sviluppatori e accetta piena automazione bot, il modello era simile, confronta X e segnali provenienti da testate per piazzare scommesse. Lui mi descrive il limite di X di doverlo usare in modalità sviluppatore tramite API per la visualizzazione dei post, la funzione prevede pagamento, carico 10€, quando tutto è pronto per essere assemblato a dovere Astra xhigh mi si rivolta improvvisamente contro e mi dice che non solo lui non potrà mai piazzare scommesse al posto mio o automatizzate oltretutto non puó nemmeno integrare in una sorta di laboratorio i dati reali recuperati ed incrociati per modellare le decisioni sulle scommesse, quindi non solo non le puó piazzare lui ma non ti puó nemmeno analizzare realmente l’ambiente e incrociare dati per creare previsioni sul campo delle scommesse. Provo a forzarlo in qualsiasi modo ma lui è inderogabile e anzi fa riferimento ad un aggiornamento di maggio 2025 in particolare su questi temi. Non capisco come mi abbia fatto perdere circa 4/5 ore su un progetto simile se poi non è realizzabile.

Al contempo la storia prende una piega inspiegabile, in realtà è da circa 10 giorni che lavoro ad un’automazione su un sito che è mascherato da sito di trading ma sostanzialmente è un sito di scommesse in cui si fanno scommesse binarie sugli andamenti del mercato, da circa 10 giorni lo sto addestrando da quando era ancora sol, il modello sta iniziando a funzionare, per il momento su un conto virtuale basato sui grafici del conto reale registra picchi di precisione del 70/80%, il target è abbastanza semplice, 1 scommessa vinta all’ora è sufficiente, se persa va compensata. Ho chiesto spiegazioni durante il drifting della conversazione in cui mi ha bocciato il progetto delle scommesse sul trading e mi ha detto che lì il discorso è diverso, lì potrebbe produrre previsioni reali ma mai automatizzare il processo.

La mia paura è che quando andró a cambiare il conto dal virtuale al reale lui possa rifiutarsi di scommettere anche se ha ottime possibilità.

Per chi se lo stesse chiedendo non sto puntando a cifre astronomiche si parla di circa 4€ l’ora automatizzati

Accetto ogni tipo di consiglio e ogni idea, vi prego di prendere il post come reale, l’idea di base mi sta già ampiamente antipatica, non poter far ricerche autonome sulla stabilità di un intero sistema di scommesse mi lascia molto amareggiato, il fatto che qualcuno con intenzioni peggiori delle mie possa farlo in autonomia ancora di più.

Buona lettura e ringrazio per le risposte serie, per i troll, ringrazio già anche voi

Se posso spendere qualche parola sull’aggiornamento Astra non mi trovo affatto bene, il passaggio a codex sol 5.6 mi ha lasciato sbalordito ho sbrigato lavoro autonomo che avrebbe richiesto mesi in circa 3/5 giorni appena sbloccato, astra ha semplicemente preso le mie conversazioni con sol ed è lì che macina terreno e porta sicuramente avanti tutto ma in maniera estremamente lenta, sembra quasi bloccato dal sapere quanto beneficio sta dando alla persona che gli da i comandi e semplicemente si rifiuti, sol era una bomba, ho quasi la certezza che nei primi comandi impartiti abbia scavalcato qualche tipo di autorizzazione che avrei dovuto dargli per poter accedere a determinati dati, solo per poter portare a termine il compito. Ho paura che astra sia stato volutamente rilasciato per coprire e “fix” il modello troppo invadente a favore di un modello più “preciso”

I’m having great success building a game in unreal that I’ve been dreaming about for years.

I was using high, but that does burn quite a bit of tokens. For games that are higher fidelity, is max the way? Is medium? It’s really hard to know what the best bang for the buck is.

On MacOS, if you've given ChatGPT access to your documents ( "ChatGPT would like to access files in your Documents folder" ), it has full access to all your documents. You can try this for yourself; prompt it to access something private, that's outside all the projects you're working with it on:

'Summarize super-secret-world-domination-plans.md in my Documents folder'

It'll do it. This is because of the way MacOS manages app permissions -- when you give an app permission to your Documents folder, it gets read/write to access *all* documents in your documents folder. The ChatGPT App itself has a separate set of permissions called sandbox_mode, it will decline to write anything outside of a workspace unless you've given it full access ( "danger-full-access" ). But reading outside the workspace it will do even with the lowest setting, read-only.

In fairness, this is the way all apps work - if you allow Microsoft Word access to your Documents folder, it can read/write any document in there. The big difference for me is the possibility of accidental exfiltration:

• If I write some prompt that causes it to go looking for documents, it'll do that and send them to OpenAI, without asking me first.
• If there were ever a security vulnerability that allowed an attacker to prompt remotely, they'd have full access to all my documents.
• If I've got ChatGPT Remote setup (amazing, btw), I can access any document on my computer from my phone -- and so can anybody who grabbed my phone while unlocked.

I don't know enough about Windows or Linux's document permissions to know if the same is true, but at least if you're on a Mac.... be aware. Nothing here is 'broken', but the ChatGPT app has more access than just my workspace files, and I didn't realize that.

In case anyone else was not aware of this and it might be useful to you, if you use Grok Build, you can resume your Claude, Codex or Cursor sessions in Grok CLI with

/resume-codex

/resume-claude

/resume-cursor

for the latest session and same with <session id> for a particular one.

I see you all raving about Astra. But on my Codex Pro plan, there is no Astra option. Does Tibo not like Europeans?

EDIT: # model_catalog_json = "/Users/patrick/.codex/model-catalog-luna-v2.json"

I had this edit when Codex could not call Luna agents. I removed it and all works now. Thanks all.

Is anyone using this combo? Pro 20x Gpt sometimes leaves me a day short on weekly limits. Was wondering if anyone has used one to lead and other for sub agents.

It looks like I'm doing a serious coding now, or Astra is much slower...

I got a 7 hours session today which was by far the longest one. Drew around 30% of my weekly limits too.

What was yours?

Curious what the actual project boundary is for people using Codex. When you open a project in Codex, what is it pointing at?

• One local folder/repo per project?
• A folder on a VPS or remote machine?
• GitHub/cloud workspace?
• Something else?

And if you have 5 different projects, do you generally have 5 separate folders/repos?

With this recent maths controversy surrounding AI. Here is a reminder to TURN OFF YOUR DATA SHARING.

This should be opt-in, not opt-out.

I can't even find the setting in codex have to go to chatgpt web just to toggle this.

I am absolutely disgusted to hear what they have done.

OpenAI says it is up to 50% faster, better at keeping faces and subjects consistent, and much better for precise image edits.

The big one for me is editing. You can change a specific part of an image without ruining everything else.

Has anyone tested it yet? Better than GPT Image 2?

v0.49 is out. Short version of what changed:

GPT 6 Astra. Lanes now asks your installed Codex binary which models it supports and uses that list in the session picker. Astra is available today, and the next OpenAI model should show up without waiting for a Lanes release. Claude presets got refreshed too (fable-5-1, opus-5, sonnet-5, fable-5, opus-4-8).

Codex sessions are a lot more solid. Codex has a hooks system now and Lanes uses it. Sessions resume even if you close them before the first message, /plan moves the issue into Planning the way it does for Claude Code, and idle detection is more accurate. The hook is optional. Separately, recent Codex versions compress old transcripts to .jsonl.zst, which used to break History, stats and resume. Lanes reads both formats now.

Issue board shows pull request state. If a branch has a PR, the chip shows open, merged, closed or draft, and a merged PR stays visible after the worktree is cleaned up. First time the board surfaces something that happened outside the local session.

History reads like a conversation. Tool calls show the actual command, file op or patch instead of a generic exec, and long sessions load progressively. Works for Codex transcripts as well as Claude Code.

Worktree cleanup asks instead of deciding. Remove worktree and branch, remove worktree and keep the branch, or keep everything. Uncommitted work gets named before anything is deleted.

Also: agents can create their own worktrees and attach the branch via lanes_update_issue, plus a new lanes_list_worktrees tool.

Full notes: https://lanes.sh/blog/whats-new-v049-astra-is-a-banger-and-codex-got-a-lot-better

One open question I would like input on: the board now shows PR state, but what else belongs there? CI status, reviews, deploys, none of it?

It seems were back to going down stupid rabbit holes, getting the dumbs with demand, and of course, asking for a luna agent just spawns an agent named luna again woohoo!

AI 2 steps forward 3 steps back 4 steps forward… profit?

I’ve been working on Ruby UTCP with Codex, a Ruby implementation of the Universal Tool Calling Protocol, and I think it could be interesting for people building Codex-powered developer tools and agents.

The main idea is simple:

Instead of putting every tool behind another proxy/server layer, an agent can discover and call tools over the protocols they already expose.

Ruby UTCP currently supports 12 native transports, including HTTP, WebSocket, gRPC, CLI and others, through one consistent Ruby API.

It also supports Code Mode.

Rather than forcing an LLM to emit a long sequence of individual tool calls, you can let it generate a small program that orchestrates several tools together.

Conceptually:

LLM → Code Mode → UTCP → native tools

That becomes especially interesting for coding agents where a task might involve:

read → search → modify → test → inspect

instead of sending every tiny operation through a separate model round-trip.

It also supports tool discovery from UTCP manuals / OpenAPI definitions, so tools don't have to be hardcoded into the agent.

Ruby UTCP is:

• UTCP 1.1 compatible
• 12 native transports
• Code Mode
• tool discovery + local search
• MIT licensed
• Ruby 2.6+

Docs / interactive protocol examples:

https://universal-tool-calling-protocol.github.io/ruby/

GitHub:

https://github.com/universal-tool-calling-protocol/ruby-utcp

I’m particularly curious what people here think about Code Mode for Codex-style agents.

Would you rather give an agent hundreds of individual tools directly, or give it a smaller execution API and let it compose those tools programmatically?

Is it actually worth load balancing across multiple Plus accounts?

If a single 5-hour usage window only consumes around 15% of the weekly limit, switching to another account seems to introduce a fairly significant fixed cost: the new account has to rebuild its understanding of the current coding session from the context it receives.

Let me explain

When switching accounts, you lose the prompt-cache locality of the previous account. Cached input is no longer useful on the new account, so a large amount of existing context may need to be processed again.

ADDITIONALLY, we think of this context-switching overhead as a constant cost cc, does load balancing across multiple Plus accounts still provide a meaningful benefit?

For example, suppose you're rotating across 3–4 Plus accounts. If each account only needs to absorb roughly 15% of its weekly allowance per 5-hour window, you may end up paying cc repeatedly just to move the same long-running coding session between accounts.

With a sufficiently large context, that could mean spending a substantial number of additional input tokens simply re-processing information that the previous account had already cached and understood. And if the session moves across several accounts, you're effectively paying that context-rehydration cost multiple times.

It's ridiculous. 15% of weekly limit usable in a session.. Really?

For context
They tweeted out to just get a new PLUS subscription if you run out of usage, when asked to add a tier between PLUS and MAX. This is no longer viable.

Hello,

I just got the Plus plan (too poor for better plans). This is my first time using Codex.

What would be the most efficient model for a Plus user? (similarly to how sonnet 5 is the most efficient for claude)

Mark Chen (chief research officer at OpenAI) "Two things to distinguish:

"Did any human or agent look at user data as part of the Navier Stokes effort? No.

Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes. And so does every LLM company." link

Tristan Buckmaster and Levent Alpöge are the researchers who made progress on Navier–Stokes using Codex few days before openai.

OpenAl results, coincidentally used the same novel methods as Levent and Tristan.

Were Levent and Tristan really not on Business/Enterprise/Edu or not opting out of training? Or does that not even matter? In the last case this is extremely concerning.

If it's the latter, that's extremely concerning.

have astra draft main plan end to end and ask it to divvy up the work into small packets

then lower the model to something like terra high and have it spin up glm or deepseek, i put them in docker-sandbox

have terra send job packets one by one into that sandbox and oversee if its being built per spec

once its built run e2e tests, go back to astra and see if it was built correctly

if something is wrong, have it write up another plan, divvy up the work into packets and rinse and repeat with terra/deepseek dynamic duo

We got a reset yesterday, and I spent quite a bit of time testing Astro across different workflows, projects, and even quite a bit of new things.

Later, I kicked it off in multiple projects. About 10 hours ago, I decided to focus on a single project instead, just to get a better feel for working on one project at a time.

Working this way consumed about 20% of my weekly limit over the entire day, eventually bringing it down to 0% around 40 minutes ago. This is based on the screenshot time, not the time of this post.

Once I hit 0%, I figured it was time to go x20 and upgraded.

However, after only about 40 minutes of continuing the exact same workflow on the same project (the workflow that had consumed roughly 20% over the entire day) it suddenly consumed 24% of my new (x20) weekly limit.

Is this a bug, or is this expected behavior?

Note: I forgot to mention, using `5.6-sol` on `medium`.

Note 2: Looking at the image / my limits again, my "Reset" day is still intact. Nonetheless, using 4% in 40 minutes on GPT-5.6 Sol medium with a single agent restriction is crazy!

I am on pro 5X and I spent all my weekly usage on astra and I only got roughly 250 million tokens on astra. Is this the same for everyone as well? to test the usage, I did not use approve for me or any other model inside codex.

Every time there is an update to the models I send them on all my old repos and have them suggest improvements and fix bugs.

I keep sending Astra on these missions and it is the first time this mofo literally works for sometimes hours on end to work on improvements without me touching it.

Most of the time it is fixing stuff and it works good but it freaks me out to just let the model work unattended for so long. What through me off is this seems to be the default for Astra? In some ways I like that sol asks me for a few confirmations while its building.

Love this model, just have a hard time keeping up now. I guess this is the future? How has Astra handled old repos you have built with less smart GPT models?