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Comment by sigbottle | Hacker News Reader

Codex IME is just smarter, I think it shows given both anecdotes but also how OpenAI has always been at the front of programming competitions and math problems.

But Claude models seem to be better at long term problems or more ambiguous problems.

I'm curious as to what the primary benefit here. Are there secret improvements in training? There hasn't been much in fundamental model architecture, I don't think. What about harnesses? I wonder what's pushing the AI. It seems like harnesses is the main thing pushing AI ever since CoT.

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I find that OpenAI's agentic tools and models are better for building human-maintainable software. Meanwhile, Anthropic seems to be cosplaying Apple while missing out on all the exceptional engineering required to create something that polished. Their admission of predominately using Claude with little human oversight and their stealth mode is an indictment of a poor engineering culture, from what I can surmise.

Serious question: what is the secret to getting Codex to write decent code? I am on Windows. Maybe that is the issue, but I can't seem to get Codex to function anywhere near the level that I was previously able to get with even Claude Sonnet. Does Codex just not work well with Windows yet?

I got the codex to write near perfect code with somewhat strict agents.md and coding standards(a separate .md file referenced from agents.md). My .md files have examples and a long list of do's and don'ts I accumulated over the last 6 months or so, totaling 300-400 lines. I plan every feature with it until I am satisfied with the general approach it wants to take, and then it oneshots it in 95% of cases. The planning takes anywhere from 5 to 30 minutes. The actual execution has gotten stupidly fast, most of the times it is faster than making a cup of coffee.

would you mind sharing your *.md files, for someone who is new at this?

"don't make any mistakes" /s

My .md files are specific to my domain - game development using Unity. Something that is probably universal and is a good baseline for every project and domain:

- which libraries to use for standard problems - project structure, it helps if it has a name(vertical slice etc) - which things llm is free to edit, which not - naming, comments etc

And most importantly: "what not to do", and you should do this a lot: Whenever llm does something that is a code smell, make it fix it and make it add a new rule to agents.md.

Have you tried using superpower skills?

I've had the exact opposite experience. For various reasons, I've had to move from Claude to Codex and the rate at which it burns tokens for the same output I would get from Claude is ridiculous. I'm probably burning tokens at a rate that is at least twice as much as I was when using Opus 4.5 for coding tasks and still finding that just manually coding is easier than trying to get Codex to write functional code.

How smart a model is varies hour over hour, tracked over here: https://aistupidlevel.info/

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