Hacker News Reader

Comment by furyofantares | Hacker News Reader

I'd been on Codex for a while and with Codex 5.2 I:

1) No longer found the dumb zone

2) No longer feared compaction

Switching to Opus for stupid political reasons, I still have not had the dumb zone - but I'm back to disliking compaction events and so the smaller context window it has, has really hurt.

I hope they copy OpenAI's compaction magic soon, but I am also very excited to try the longer context window.

View on HN

If you use OpenCode (open source Claude Code implementation), you can configure compaction yourself : https://opencode.ai/docs/en/config/#compaction

Not sure if it's a common knowledge but I've learned not that long ago that you can do "/compact your instructions here", if you just say what you are working on or what to keep explicitly it's much less painful.

In general LLMs for some reason are really bad at designing prompts for themselves. I tested it heavily on some data where there was a clear optimization function and ability to evaluate the results, and I easily beat opus every time with my chaotic full of typos prompts vs its methodological ones when it is writing instructions for itself or for other LLMs.

You can also put guidance for when to compact and with what instructions into Claude.md. The model itself can run /compact, and while I try to remember to use it manually, I find it useful to have “If I ask for a totally different task and the current context won’t be useful, run /compact with a short summary of the new focus”

I ofter wonder if I'm missing something, but shouldn't we be able to edit the context manually???

In that way we could erase prompts and responses that didn't yield anything useful or derailed the model.

Why can't we do that?

so you have to garbage collect manually for the AI?

also, i don't want to make a full parent post

1M tokens sounds real expensive if you're constantly at that threshold. There's codebases larger in LOC; i read somewhere that Carmack has "given to humanity" over 1 million lines of his code. Perhaps something to dwell on

OpenAI has some magic they do on their standalone endpoint (/responses/compact) just for compaction, where they keep all the user messages and replace the agent messages or reasoning with embeddings.

> This list includes a special type=compaction item with an opaque encrypted_content item that preserves the model’s latent understanding of the original conversation.

Some prior discussion here https://news.ycombinator.com/item?id=46737630#46739209 regarding an article here https://openai.com/index/unrolling-the-codex-agent-loop/

This is true.

When I am using codex, compaction isn’t something I fear, it feels like you save your gaming progress and move on.

For Claude Code compaction feels disastrous, also much longer

1m context in OpenAI and Gemini is just marketing. Opus is the only model to provide real usable bug context.

Source? I ask because I use 500k+ context on these on a daily basis.

Big refactorings guided by automated tests eat context window for breakfast.

i find gemini gets real real bad when you get far into the context - gets into loops, forgets how to call tools, etc

I find gemini does that normally, personally. Noticeably worse in my usage than either Claude or Codex.

I find Gemini to be real bad. Are you just using it for price reasons, or?

yeah gemini is dumb when you tell it to do stuff - but the things it finds (and critically confirms, including doing tool calls while validating hypotheses) in reviews absolutely destroy both gpt and opus.

if you're a one-model shop you're losing out on quality of software you deliver, today. I predict we'll all have at least two harness+model subscriptions as a matter of course in 6-12 months since every model's jagged frontier is different at the margins, and the margins are very fractal.

How many big refactorings are you doing? And why?

How is that relevant? we are talking about models, now what you do with them.

Codex high reasoning has been a legitimately excellent tool for generating feedback on every plan Claude opus thinking has created for me.

I'm directly conveying my actual experience to you. I have tasks that fill up Opus context very quickly (at the 200k context) and which took MUCH longer to fill up Codex since 5.2 (which I think had 400k context at the time).

This is direct comparison. I spent months subscribed to both of their $200/mo plans. I would try both and Opus always filled up fast while Codex continued working great. It's also direct experience that Codex continues working great post-compaction since 5.2.

I don't know about Gemini but you're just wrong about Codex. And I say this as someone who hates reporting these facts because I'd like people to stop giving OpenAI money.

This has been my experience too.

Have any of you heard of map reduce

I agree even though I used to be a die hard Claude fan I recently switched back to ChatGPT and codex to try it out again and they’ve clearly pulled into the lead for consistency, context length and management as well as speed. Claude Code instilled a dread in me about keeping an eye on context but I’m slowly learning to let that go with codex.

Surely compaction is down to the agent rather than the model, so are you comparing Claude Code to Codex CLI?

It's both.

Using Codex more for now, and there is definitely some compaction magic. I’m keeping the same conversation going and going for days, some at almost 1B tokens (per the codex cli counters), with seemingly no coherency loss

Hmm I’ve felt the dumb zone on codex

From what I've seen, it means whatever he's doing is very statistically significant.

Reply on news.ycombinator.com