- The smartest model I have used. Solves problems better than Opus-4.1.

- It can be lazy. With Claude Code / Opus, once given a problem, it will generally work until completion. Codex will often perform only the first few steps and then ask if I want to continue to do the rest. It does this even if I tell it to not stop until completion.

- I have seen severe degradation near max context. For example, I have seen it just repeat the next steps every time I tell it to continue and I have to manually compact.

I'm not sure if the problems are Gpt-5 or Codex. I suspect a better Codex could resolve them.

Gemini cli is too inconsistent, good for documentation tasks. Don’t let it write code for you

Not sure the fault it's "doing bad code", I guess it's just not being good at being agentic. Saw this on Gemini CLI and other tools.

GLM, Kimi, Qwen-Code all behaves better for me.

Probably Gemini 3 will fix this, as Gemini 2.5 Pro it's "old" by now.

Claude Code does that on longer tasks.

Time to give Codex a try I guess.

I don't like that at all. Actually running the code is the single most effective protection we have against coding mistakes, from both humans and machines.

I think it's absolutely worth the complexity and performance overhead of hooking up a real container environment.

Not to mention you can run a useful code execution container in 100MB of RAM on a single CPU (or slice thereof). Simulating that with an LLM takes at least one GPU and 100GB or more of VRAM.

What worked was getting it to first write a detailed implementation plan for a “junior contractor” then attempt it in phases (clearing task window each time) and told to use /tmp to copy files and transform them then update the original.

Looking forward to trying the new model out on the next refactor!

This model is available inside all OpenAI codex products. Yet to be available on Api

The model is supposed to be better at code reviews and Comments than the other GPT-5 variant. It can also think/work upto 7 hours.

Even shorter version:

- New coding-specialist model called GPT-5-Codex, coming soon to the API but for now available in their Codex CLI, VS Code and Codex Cloud products

- New code review product (part of Codex Cloud) that can review PRs for you

- New model promises better code review, less pointless comments and can vary its reasoning effort for simple vs complex tasks

I can't use the IDE codex at all now it seems.

> OpenAI

> We rely on many of OpenAI's models to give AI responses. Requests may be sent to OpenAI even if you have an Anthropic (or someone else's) model selected in chat (e.g. for summarization)*. We have a zero data retention agreement with OpenAI.

Source: https://cursor.com/security

I will say that the Security page by the Cursor team is a very nice overview, even going into Auth, etc. and applaud that, but see nothing here that differentiates their use of e.g. OpenAI models from the agreements OpenAI offers themselves. Essentially, I don't see why anyone would have such severely heightened trust in Cursor over competitors in this area. If they only provided self hosted models, I could understand it, but not the way they operate.

Personally, both because of the way and on what LLMs have been trained on, on top of my expectation in terms of privacy, regardless of model provider assurances, I'd treat any LLM derived/assisted/reviewed code as public the second you send it to some providers server hosted model and some form of FOSS to boot. Basically, if you used Cursor, Codex, Augment or anything of that sort, I'd reduce any future privacy expectations straight away, might as well put it on public Github for everyone to see.

Only self-hosting on prem is an option for keeping control of your codebase, though personally, I'd still consider licensing such code as FOSS, considering no model wasn't trained on EUPL, GPL, etc. Personal (very much philosophical and not at all legal, as that goes into what training is, weights, etc. arguments that can go on eternal) opinion, but I'd argue whether you are MSFT or a small startup, if you derive a significant amount of new code from LLMs, arguing that copyleft shouldn't be at the very least on the mind of your legal department isn't reasonable, but of course, this will have to be decided by courts and likely in favour of those with the best legal teams. I doubt if any of the "80% of our code is written by LLMs" were true, that'd convince a court to enforce copyleft upon the product in question, but personally, that'd be my viewpoint.

Regardless of licensing, if you send your code to Cursor, purely privacy wise, you shouldn't have reservations about OpenAI.

Jetbrains has a $30/mo subscription (with gpt5 backend) and the quota burns so fast.

Assuming Jetbrains is at breakeven price, either OpenAI has some secret sauce or they're losing money for Codex.