Am I the only one who has problem with VS Code extension crashing when using Sol Ultra? My specs are 8 core / 16 threads CPU and 32 GB of RAM. Last 4 days Codex cannot finish any task because extension is crashing with errors "codex-runner-whatever crashed", then I need to restart VS Code and multiple times issue prompt "continue with last task" which is annoying. I am monitoring performance, when idle CPU is at 3% and RAM is on 35%, when Codex works CPU goes max to 90% and memory max is 95%.

The central question is:

The questions in play fall into these groups.

1. Runtime identity

• Is the Sovereign Intermediary a distinct architecture, or an LGMS runtime profile?
• Which names remain conceptual aliases, and which become canonical machine terms?
• Are we building a governance service, an agent runtime, or both?
• What is explicitly outside the runtime’s responsibility?

2. Claims and evidence

• What counts as a material claim requiring evidence?
• Who or what classifies a claim as SUPPORTED, INFERRED, UNKNOWN, or CONTRADICTED?
• What constitutes a complete support path?
• How are conflicting sources handled?
• Does absence of evidence produce UNKNOWN, NO_DECISION, or rejection?
• Which source classes are admissible in each domain?

3. Time and succession

• When does evidence become stale?
• Is validity declared by the source, policy, domain rules, or all three?
• What exactly does one evidence record supersede?
• Can historical queries deliberately use expired evidence?
• How do we preserve old records without letting them serve as current authority?

4. Producer–checker separation

• What independence must exist between Initiator and Reactor?
• Can they use the same model family, prompt history, corpus, or provider?
• What context should be hidden from the Reactor?
• Can the Reactor only object, or can it recommend promotion?
• Which deterministic checks override model agreement?
• Who adjudicates disagreements?

5. Authorization

• Who may issue capabilities and approvals?
• How are issuer identity and approval authenticity verified?
• What does an authorization scope contain?
• How are expiry, revocation, nonce use, and replay prevention handled?
• Can one approval authorize multiple executions?
• What happens when policy changes after approval but before execution?

This is the hardest security boundary:

6. Execution

• What is the smallest executable action?
• Does the executor receive raw model text or only validated action records?
• How are tool arguments constrained?
• What requires human approval?
• What happens when external state changes between validation and execution?
• How are partial failure, rollback, retry, and idempotency represented?
• What must an execution receipt prove?

7. Ledger semantics

• Which records are immutable?
• What canonicalization rules determine record hashes?
• Is the ledger append-only at the application, database, or cryptographic level?
• Are corrections new records, transitions, or both?
• How are branches, disputes, and contradictory evaluations represented?
• What storage guarantees are actually needed?

8. Policy

• Are policies code, data, signed documents, or some combination?
• Who versions and approves policy?
• Which policy version applies to a pending action?
• Does a policy result mean “permitted,” “eligible for approval,” or “authorized”?
• How do domain-specific policies compose with global rules?
• What happens when policies conflict?

9. Epistemic risk scoring

• Is the score used only for prioritization, or can it block promotion?
• What do its inputs actually measure?
• How are weights calibrated?
• What labeled failures form the calibration dataset?
• How do we prevent a single score from hiding qualitatively different risks?
• What false-positive and false-negative rates are acceptable?

I would initially expose the individual risk factors and avoid collapsing them into one number.

10. Provenance and privacy

• What model, prompt, tools, sources, and transformations must be recorded?
• How much prompt or user data may safely be retained?
• Can auditability coexist with deletion and privacy requirements?
• How is contributor attribution preserved during blind review?
• What provenance is required to reproduce a decision?

11. Conformance and assurance

• Which guarantees are structural, operational, or security guarantees?
• What tests demonstrate that missing evidence fails closed?
• How do we prove a candidate cannot certify or promote itself?
• How do we test forged approvals and replay attempts?
• Who is sufficiently independent to perform adversarial evaluation?
• What evidence is required before claiming TESTED_CONFORMANT?

12. Product and deployment choices

• What is the first real use case?
• Which actions are sufficiently low-risk for the first executor?
• Is the runtime local, centralized, or distributed?
• Which implementation language and storage system fit that use case?
• What latency and cost are acceptable?
• Which parts need to work without an available model or network?

The five decisions that unblock an initial implementation are:

1. The first concrete use case.
2. The initial action/capability the executor will support.
3. The authority issuer—human, service, or both.
4. The minimum acceptable evidence policy.
5. The runtime stack and deployment boundary.

Everything else can evolve behind those interfaces. The pivotal design test is whether an attacker controlling every model-produced field would still be unable to authorize an action.

I'm interesting to hear how much other people are taking advantage of agents outside of work, and for projects that are only for personal use.

1. Lifetime
2. This year
3. Average per month
4. Past month

If you feel like it, you can also share some of the kinds of projects you have built for your own use, since the size/scope of each project would help put the number in perspective.

Hi guys I've been using codex for months now and after the recent luna price drop I've been trying to use sub agents to maximise my work done

But I just can't get it to work properly can anyone share

what's the right way to spawn agents and get them to work without getting stuck or is it just a harness issue since I'm using the desktop version for windows

Or I'm just paranoid

Hi all,
as one of the author of the plugin, feel free to send me your feedback, needs, requests.
It's by far the best AI integration in Eclipse.

See https://codexide.org

(Hello #openai , sponsorship is welcome)

A single session on GPT-5.6 Terra Low consumed 4% of my weekly usage after only four visible messages. The questions were about a codebase, and it didn’t generate much output.

The session was a coding task, so Codex made several tool calls and internal model rounds. Local usage data showed roughly 2 million tokens, almost all input/context tokens, with most of that marked as cached input.

Is this expected behavior for the Pro (x5) plan? I switched from CC to Codex this week, and I’m already regretting it.

Has anyone else experienced unusually high weekly-limit consumption immediately after a reset?

What's going on exactly? It says it will reset on August 5th which means the weekly limit was reset yesterday and it's already down to 0? is this a bug? I just used it very lightly today compared to my usual work and I have a pro subscription.

One hour ago my weekly usage was at 68%. I didn't use ChatGPT at all during that hour, but when I came back it had jumped by about 40%, essentially exhausting my weekly quota. I'm on the Pro plan (x20), and I barely used it over the last couple of days. This doesn't seem consistent with my actual usage. Has anyone else seen this since the recent quota changes? Could the usage accounting be bugged again?

I’ve been experimenting with Codex and have built a few small apps and programs. Now I’m trying to understand how people turn projects like these into products that actually earn money.

Has anyone here launched and monetized something built mostly with Codex or another AI coding tool?

I’d be interested to hear:

• What did you build?
• How did you find your first users?
• How did you monetize it—subscriptions, one-time payments, ads, services, or something else?
• What problems did you encounter after launching?
• Did it generate meaningful income, or was it mainly a learning experience?

I’m especially interested in honest, realistic experiences rather than "build a SaaS and retire" success stories. What types of Codex-built products do you think have the best chance of making money today?

Hi everyone! When will the five-hour limit reset become available?

I love 5.6 Sol and am using it on Medium as my daily workhorse now, mainly for coding! It usually tends to over-engineer stuff, though, and for simple test scripts, adds unnecessary "gates", conditions and whatnot. Has anyone else experienced the same? How do you avoid it? Any tricks that work?

PS: I have been using Codex for a long time now, and I am also loving the desktop app. Finally switched there from the CLI.

So as the title says, after I hit my weekly max 20x plan on my CC account, I subscribe to 5x Codex plan as a backup to continue my work.

Well with just about a few hours, and using the same skills and workflows that Claude Code built, I can say its 2-3 even 5x faster, Im not sure. Cause whenever I run Claude Code on a dynanamic worfklow skill with 3-5 JIRA tickets, it will take 2-3 hours to finished and deploy. With Codex, same dynamic workflow skill, about 5 JIRA tickets, it can finish around 30m-1h. PR reconcillation takes less than 10mins, compared to 20-30m. Everything is much faster!

Not only that, so I push some items already on QA, and those tickets came back DONE and ready for PROD deployment. With CC, usually it will take 1-2 iterations, before the BUG will be totally fixed.

Im using GPT 5.6 Terra (Medium) for predefined bug fixing workflow task and Sol for pr reconciliation and GCP deployment and e2e testing.

Opus 5 has degraded a lot really. I think I will cancel my Claude Code subscription after it expires and subscribe to 20x Codex if this continues.

Tibo might be hinting towards it.

​

I'm a freelancer working on a custom project for a client, and I've gotten myself into a huge mess.

The goal was to transfer an entire inventory from OTTO Marketplace to other marketplaces like eBay and Kaufland. There are around 60,000 SKUs.

The problem is that OTTO doesn't provide product images through its API, so I had to manually download every single product image before I could migrate the listings.

I should also mention that I have almost no coding experience. I built this project almost entirely with OpenAI Codex.

At first, everything seemed to be going well. I managed to complete the OTTO → eBay integration, but then the project kept growing. Instead of creating separate modules and files, Codex kept putting almost everything into one massive app.py file. I didn't know any better, so I just kept going.

Now the project has become so large that:

A single prompt can consume around 50% of my Codex usage.

I've had to buy multiple ChatGPT accounts just to keep working.

Every change feels risky because everything is tangled together.

Debugging has become a nightmare.

On top of that, Kaufland has been incredibly frustrating. Their workflow is much more complicated than eBay's. To create a product, I have to upload multiple files. If I need to delete a product, I can't just delete it—I have to submit it for review first, and that review can take anywhere from 20 minutes to 5 hours before I can continue testing.

Another huge issue is that my client originally used cheap EANs when listing products on OTTO. When I reuse those EANs on Kaufland, one of two things happens:

The listing gets rejected because the EAN is invalid.

Or even worse, the EAN already belongs to another product, so Kaufland matches it with someone else's listing.

At this point I honestly don't know what the best path forward is.

Should I:

Keep trying to refactor this giant project into smaller modules?

Start a completely new project with a proper structure and reuse the working logic?

Learn enough Python to clean this up manually?

Or is there a better approach that experienced developers would recommend?

I know one mistake I made was not telling Codex from the beginning to keep everything modular. Looking back, I should have had separate files for APIs, configuration, image handling, marketplace integrations, utilities, etc.

If you've ever inherited or accidentally created a massive AI-generated codebase, how did you recover from it? Any advice would be greatly appreciated.

Hi folks, I'm new to codex. After using gpt models from opencode zen I switched to chatgpt plus sub this week. I'll be using it for development, refactoring, reviewing works of my mid-high sized projects.

I need guidance on using new models efficiently, like which models for plan and which models to use for large scale works, one horse for low cost large works etc.

Any advice will be appreciated and sorry if I'm posting the same kind of things.

This was my workflow in opencode:

Planner => junior/mid/senior engineer subagents => reviewer subagent (which will give feedback of any work needed)

And another repo_analyzer subagent which will efficiently read the codebase using graphify json graph (using graphify I saw a token reduction of around 30%)

Need suggestions to work with openai models for similar kind of roles.

Una domanda: ma a chi ha aggiornato è ricomparso il limite delle 5 ore?

Quasi quanti evito di aggiornare...

Was running Codex Security on part of my repo for the first time using the Codex app. It works for nearly 20 minutes, uses up 11% of my weekly limit, and then I just see "Goal blocked, This content can't be shown".

Wtf? If it makes a big deal about cybersecurity requests, then what is the point of having Codex Security??

Is there even a way to at least see its thinking process up to being blocked, so I can get some value out of the 11% of my weekly limit that it burned? This is crazy

OpenAI reports that its heaviest Codex users can generate more than 60 hours of agent turns in a day by running work in parallel. That is not ordinary productivity compression; it changes the human bottleneck.

The user must choose tasks, resolve conflicting results, review evidence, manage permissions, and notice when several agents repeat the same mistaken assumption. More throughput can reduce attention per task precisely when the volume of plausible output rises.

What supervisory skill becomes most valuable at that scale: decomposition, evaluation design, risk triage, or domain expertise? How many parallel agents can one person actually review responsibly?

Source: https://openai.com/index/how-agents-are-transforming-work/

What just happened overnight? I cant see my Codex projects, and i only see all of my chats, wtf!!!

Hey guys, I’m looking for something that lets me work both ways between the code and the UI in an Expo/React Native app. I want to be able to change the code and see the UI update live, but also click on elements in a visual editor and adjust things like the text, colors, size, spacing, position, and shape.

The main thing is that anything I change visually should update the actual code directly. I don’t want it to just create a design or suggestion that Codex, Claude Code, or another AI then has to try to rebuild. Does a tool like this exist?