Can you share an example of the tasks you found Codex being much better? From my experience Claude Code is much better.
Claude, especially 4.5 Sonnet, is a lot nicer to interact with, so it may be a better choice in cases where you are co-working with the agent. Its output is nicer, it "improvises" really well even if you give it only vague prompts. That's valueable for interactive use.
But for delegating complete tasks, Codex is far better. The benchmarks indicate that, as do most practicioners I talk to (and it is indeed my own experience).
In my own work, I use Codex for complete end-to-end tasks, and Claude Sonnet for interactive sessions. They're actually quite different.
The output of codex is also not as great. Codex is great at the planning and investigation portion but sucks at execution and code quality.
Then I do a double take and re-read the summary message and realize that it pulled a "and then draw the rest of the owl", seemingly arbitrarily picking and choosing what it felt like doing in that session and what it punted over to "next steps to actually get it running".
Claude is more prone to occasional "cheating" with mocked data or "tbd: make this an actual conditional instead of hardcoded If True" stuff when it gets overwhelmed which is annoying and bad. But it at least has strong task adherence for the user's prompt and doesn't make me write a lawyer-esque contract to avoid any loopholes Codex will use to avoid doing work.
Claude struggled long time and still didn’t find.
They can save you some time by doing some fairly complex basic tasks that you can write in plain language instead of coding. To get good results you really need a lot of underlying knowledge yourself and essentially, I think of it as a translator. I can write a program in very good detail using normal language and then the LLM can convert it to code with reasonable accuracy.
I haven't been able to depend on it to do anything remotely advanced. They all make up API endpoints or methods or fill in data with things that simply don't exist, but that's the nature of the model.
What I'm saying was to compare my experience with Claude code vs Codex with GPT-5. CC's better than codex in my experience, contrary to GP's comment.
Sora 4.5 tends to randomly hallucinate odd/inappropriate decisions and goes to make stupid changes that have to be patched up manually.
I find that Codex generally requires me to remove code to get to what I want, whereas Claude I tend to use what it gives me and I add to it. Whether this is from additional prompting or from manual typing, i just find that codex requires removal to get to desired state, and Claude requires adding to get to desired state. I prefer adding incrementally than removing.
Edit: I'd like to reply to this comment in particular but can't in a threaded reply, so will do that here: "Ah, super secret problem domains that have been thoroughly represented in the LLM training data. Nice."
This exhibits a fundamental misunderstanding of why coding agents powered by LLMs are such a game changer.
The assumption this poster is making is that LLMs are regurgitating whole cloth after being trained on whole cloth.
This is a common mistake among lay people and non-practitioners. The reality is that LLMs have gained the ability to program, by learning from the code of others. Much like a human would learn from the code of others, and then be able to create a completely novel application.
The difference between a human programmer an an agentic coder is that the agent has much broader and deeper expertise across more programming languages, and understands more design patterns, more operating systems, more about programming history, etc etc and it uses all this knowledge to fulfill the task you've set it to. That's not possible for any single human.
It's important for the poster to take two realities on board: Firstly, agentic coding agents are not regurgitating whole cloth from whole cloth. Instead they are weaving new creations because they have learned how to program. Secondly, agentic coding agents have broader and deeper knowledge than any human that will ever exist, and they never tire, and their mood and energy level never changes. In fact that improves on a continuous basis as the months go by and progress continues. This means we can, as individual practitioners or fast moving teams, create things that were never before possible for us without raising huge amounts of money and hiring large very expensive teams, and then having the overhead of lining everyone up behind a goal AND dealing with the human issues that arise, including communication overhead.
This is a very exciting time. Especially if you're curious, energetic, and are willing to suspend disbelief to go and take a look.
The easier threading-focused approach to the conversation might be to add the additional comment as an edit at the end of the original and reply to the child https://news.ycombinator.com/item?id=45649068 directly. Of course, I've broken the ability to do that by responding to you now about it ;).
Well, that, and it’s just a bit annoying to claim that you’ve found some amazing new secret but that you refuse to share what the secret is. It doesn’t contribute to an interesting discussion whatsoever.
What honesty? We're not at the point of "the Godfather was a good/bad movie", we're at "no, trust, there's a really good movie called the Godfather".
Your honesty means nothing for an issue that isn't about taste or mostly subjectivness. How useful AI is and in what way is a technical discussion where the meat of the subject matter is. You've shared nothing on that front. I am not saying you have to, but like obviously people are going to downvote you - not because they might agree/disagree but because it's contributed nothing different from every other ai-hype man selling a course or something.
Talk is cheap, and we're tired of hearing people tell us how it's enabling them to make incredible software without actually demonstrating it. Your words might be true, or they might be just another over-exaggeration to throw on the pile. Without details we have no way of knowing, and so many make the empirically supported choice.
I recently vibe coded a video analysis pipeline with some related arduino-driven machine control. It was work to prototype an experience on some 3D printed hardware I’ve been skunking out.
By describing the pipeline and filters clearly, I had the analysis system generating useful JSON in an hour or so, including machine control simulation, all while watching TV and answering emails/slacks. Notable misses were that the JSON fields were inconsistent, and the python venvs were inconsistent for the piped way that I wanted the system to operate with.
Small fixes.
Then I wired up the hardware, and the thing absolutely crapped itself, swapping libraries, trying major structural changes, and creating two whole new copies of the machine control host code (asking me each time along the way). This went on for more than three hours, with me debugging the mess for about 20 minutes before resorting to 1) ChatGPT, which didn’t help, followed by 2) a few minutes of good old fashioned googling on serial port behavior on Mac, which, with an old sitting on the shelf Uno R3, meant that I needed to use the cu.* ports instead of tty.*, something that Claude Code had buried deeply in a tangle of files.
Curious about the failure, I told Claude Code to stop being an idiot and use a web browser to go research the problem of specifically locking up on the open operation. 30 seconds later, and with some reflective swearing from Opus 4.1, which I appreciate, I had the code I should have had 3 hours prior (along with other garbage code to clean up).
For my areas of sensing, computer vision, machine learning, etc., these systems are amazingly helpful if the algorithms can be completely and clearly described (e.g., Kalman filter to IoU, box blur followed by subsampling followed by split exponential filtering, etc.).
Attempts to let the robots work complex pipelines out for themselves haven’t gone as well for me.
The original post states "I am seeing Codex do much better than Claude Code", and when asked for examples, you have replied with "I don't have time to give you examples, go do it yourself, its obvious."
That is clearly going to rub folks (anyone) the wrong way. This refrain ("Wheres the data?") pops up frequently on HN, if its so obvious, giving 1 prompt where Codex is much greater than Claude doesn't seem like a heavy lift.
In absence of such an example, or any data, folks have nothing to go on but skepticism. Replying with such a polarizing comment is bound to set folks off further.