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Posted by AmazingTurtle 2 days ago

OpenAI reduces Codex Model Context Size from 372k to 272k(github.com)
367 points | 163 commentspage 3
Topology1 1 day ago|
Looks like we will be waiting quite a while to see a 1M context window from OpenAI
trilogic 2 days ago||
HugstonOne increased coding context size, from 1 to 4 Million ctx
simonw 1 day ago||
Another interesting change in that commit is the addition of this section to the system prompt:

  Before taking a destructive action:
  
  - Make sure the action is clearly within
    the user's request.
  - Resolve the exact targets with
    read-only checks when necessary.
  - Do not use `$HOME`, `~`, `/`, a
    workspace root, or another broad
    directory as the target of a
    recursive or destructive command
Looks like the fix for this bug where Codex would occasionally accidentally delete your entire home directory: https://twitter.com/thsottiaux/status/2077630111499882637
tekacs 1 day ago||
https://github.com/tekacs/fast-rm

I've overridden my rm with this, which I threw together for fast-deletes of things like Rust target/ directories, and after seeing the GPT horror story, I taught it to flatly reject deletions directly under `/` and under home directories, with a message printing the path that it's trying to delete.

Not exactly a perfect mitigation, but given that the stated risk was the model mistakenly using the wrong $HOME, it seems like a reasonable safety. I should probably make it use an even scarier rejection notice, though.

I also... have backups.

AmazingTurtle 1 day ago|||
This happened to me one time. On windows though, deleting C:/ lmao. The direction I'm heading now is a better harness, i.e. isolating codex at a container level with dedicated workspaces / mounts etc. I'm building something at the moment that serves my needs.
Razengan 1 day ago||
That's ok, if AI deletes my home directory I can just ask AI to regenerate my home directory.
hakanderyal 1 day ago||
I have rule files that guides the agent towards my coding standards, code style, house rules etc. They alone cost 60-80k tokens, and they are the backbone of my system that prevents slop. Pre 1M context, I had to build complicated tooling to re-include the relevant docs to the context upon compaction, which relied on unstable transcription file format, which was a pain to maintain. With 1M context I deleted all of those. Nowadays most of my sessions uses 300-450k context.

Another thing that's preventing me from trying Codex. (the other is @ referencing files not auto including them to the context)

1M should be table stakes for frontier models at this point for programming.

yearolinuxdsktp 1 day ago|
Try running your rule files through an LLM for optimization. 60k-80k tokens is massive.

Funnily enough, most anti-slop skills I found are both way too verbose and miss some common slop constructs.

I also reduced many rules from “When doing X, don’t do Y, but do Z.” Instead, the rule is “When doing X, do Z.” Fewer tokens and often works better.

I had one critical rule I was maintaining about searching the codebase using a structural index/graph and not grep. Every time the agent missed it, I asked it how to improve the rules. Eventually, I asked the AI to review that rule file and it rewrote it to be 30% smaller, but, crucially, structured to be more understandable by the LLM.

Another helpful thing was to ask AI to review my rules for things it can load on-demand when it works in that area.

hakanderyal 1 day ago|||
It’s optimized to death. Every word, every comma. I have a rule file for writing rule files.

Problem stems from using my own abstractions instead of common frameworks.

For a full stack session, backend + front end + docs about the part we are working on adds to that amount.

I’ve accepted it because it results in code exactly the style I would’ve written. It’s a good tradeoff to cut off the slop.

wonnage 1 day ago|||
AI cannot tell you why it did something. If you ask it why it didn't do X even though your prompt said so, it can come up with some plausible sounding explanation, which might even be correct, but there's a fundamental impedance mismatch between giving you the most plausible sounding answer and actually grounding that in knowledge of how it generated that answer.

TBF having a 60k personal style guide is also a bad idea, people get borderline AI-psychosed about how their special prompts are really steering the AI when in reality there is no way to evaluate this stuff. You invariably end up trying to define your style in terms of what it is and it isn't, it's like trying to define "red". "follow the style of my 5 most recent PRs" works pretty well.

quotemstr 1 day ago||
Codex is open source. You can build it yourself. You don't have to use upstream's parameter choices, compaction strategies, subagent heuristics, or whatever. Strange how people act like tweaks to these parameters are mandates when they're really just suggestions relayed to you via git.

For example: upstream recently changed the effort level hotkeys so M-. would stop at xhigh, not max. If you want max, upstream, you go to the /model menu. I didn't like this change, so I undid it locally. Easy peasy.

noname120 1 day ago|
Not true. Try to increase the context window and you will be greeted with an error when you reach the real limit enforced server-side.
searealist 1 day ago|||
The models themselves support up to 1M. You are just charged more for all context over 400k. The 272k limit is just a client limitation to ensure you can never go over 400k since the maximum output size of the model is 128k.
noname120 18 hours ago||
Not true. This is the case for the API, not for subscriptions: they are hard capped at 400k.
quotemstr 1 day ago|||
Perhaps not this for this parameter, but for others? Client side.
ashu1461 1 day ago||
I am wondering why the codex repo is open source ? Can they afford it to be open source in the longer run ?
simonw 1 day ago||
Not much point making it closed source at this point, coding agent harnesses are trivial to reverse-engineer.

Being open source was also a useful community lever they could pull when they were trying to catch up with Claude Code.

CamperBob2 1 day ago||
Not much point making anything closed source at this point, if the client has access to the binary.
Topfi 1 day ago||
What do you mean “afford”?
cmrdporcupine 1 day ago||
Codex compaction is really quite good. Smaller context doesn't really harm me.

I had a /goal running last night for 9.5 hours straight while I slept. When I woke up in the morning it was fully on task and focused.

Write up a detailed design doc. Build a decent AGENTS.md, and write up a good prompt or /goal.

Long context can be more of a curse than a benefit sometimes anyways.

maherbeg 20 hours ago|
Yeah, agreed. It makes everything else look pretty bad. I still like to manage my work in a more structured form, but Codex can just rip on a goal end to end in the same thread.
hendersoon 1 day ago||
This was done because they were charging the 100%/50% premium for long-context over 272k to Codex users, even though they set 372k as the default. It cost people a LOT of money.
monster_truck 1 day ago|
If ChatGPT 5.6 is so good why do they continue to have the same motherfucking cache and usage issues that they were struggling with when 5.2 is new? Could not pay me to use this shit. Enjoy your reset bingo
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