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Comment by jumploops | Hacker News Reader

Not suddenly, it's been better since GPT-5 launched.

Prompting is different, but in a good way.

With Claude Code, you can use less prompting, and Claude will get token happy and expand on your request. Great for greenfield/vibing, bad for iterating on existing projects.

With Codex CLI, GPT-5 seems to handle instructions much more precisely. It won't just go off on it's own and do a bunch of work, it will do what you ask.

I've found that being more specific up-front gets better results with GPT-5, whereas with Claude, being more specific doesn't necessarily stop the eagerness of it's output.

As with all LLMs, you can't compare apples to oranges, so to clarify, my experiences are primarily with Typescript and Rust codebases.

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Codex CLI of course will sometimes do the wrong thing, or sometimes do something extra that you didn't intend for it to do.

It seems about half my sessions quickly become "why did you do that? rip __ out and just do ___". Then again, most of the other sessions involve Codex correctly inferring what I wanted without having to be so specific.

Yeah, I tried Claude Code CLI and never found it too useful, but that was Claude 3.5 era. Still using Claude 3.7/4.0 via Cursor were much better but still had to micro managed.

GPT5 + Codex CLI has been pretty productive for me. It's able to get a lot right in a simple prompt without getting too distracted with other crap. It's not perfect, but it's pretty good.

I actually worry GPT5-Codex will make it worse on that aspect though. One of the best parts of GPT5/Codex CLI is that it tends to plan and research first, then make code.

Sounds like the difference between finding what needs to be done, making a plan, and executing on it remains something to consider and be aware of.

Claude Code has been a revelation and a bit of a let down the past 45 days.

Some open acknowledgement would have been great, but in lieu of it, it seems it's best to hop on a new tool and make sure you learn how to prompt better and not rely on the model to read between until usage is "optimized" and it no longer seems to work for those folks.

I've seen some interesting files that help any model understand a programming language as it's strong suit and it might not even be an expert in and how to best develop with it.

Anthropic acknowledged there were bugs that are now resolved, see their status page for latest info:

https://status.anthropic.com/

The models themselves are responding differently to prior chat requests being run again.

So is gpt-5-codex-high better than gpt-5-high? I find it hard to believe that with half the instruction tokens a MOE model could significantly outperform, but I am certainly not knowledgable in fine-tuning.

Yea, I have struggled with Claude to keep it focused on what I want and only what I want. I have no experience with GPT-5-Codex, but maybe I should.

This has been my experience even in Cursor. I often select the GPT-5 option because I know it will "know" better how much reasoning effort it needs

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