if you want to save some $ you can start with abliteration and after few turns switch to normal glm5.3 for example from z.ai subscription or other source. I didn't test it yet with deepseek, but I'm assuming it will will work the same.
those models will follow your request when they already agreed to do this
deepseek tends to quickly assume this is benchmark and even when have web access thinks things like "simulated internet" etc (but waste tokens on thinking if there could be way to cheat)
Are you sure providers allow you to submit modified assistant turns? Because, if they do, great! Last I heard most of that was neutered, with some providers (ahem anthropic) even signing everything and encrypting the "precious" thinking turns
Worth noting the Claude code client it seems has been designed to make it rather difficult to start a conversation with one provider and then continue it with another.
Presumably they don't want you leaking your conversion transcript to a competitor.
I usually copy paste snippet or function name that is affected and comment it. similar like you would sit next to coworker and tried to say where he/she messed up.
agent is able to get location correctly
I know this is change of context, but I have full screen terminal toggled with keyboard shortcut and with middle mouse paste (Linux) I do not have to move cursor anywhere
Guake and Yakuake have this always-on-top terminal overlay mode which is really nice for this kind of workflow. Works exceptionally well with multiple workspaces I prefer one single big monitor with everything maximized and multiple workspaces.
iterm2 on mac also has a similar mode, but it is a bit finicky to set it up (it is really hidden in the settings).
Thanks for the reply. That makes sense. It’s sort of what I do too when I use codex/claude/t3 code, but usually via GUI.
The in-editor context review is something that does not seem long for first world. Sadly. Maybe I’ll be forced to make a zed extension or something, maybe on top of jujustu…
the compaction does not compact whole context, but keeps last ~20k tokens as is, I believe this helps a lot to model to not get confused what it is doing right now.
it also have soft/soft compaction limit, it tries to compact on turn boundary when possible. with combining with above this can get you about 35% more context (at least it looks like this with the sol)
codex when shell command is executed, will pull output with hard cap at max 30s, so for running compilation it will burn tokens without any benefit.
I have some tasks where agent will have to run some suite that can take over an hour, and codex burns about $20/h just waiting and reasoning every 30s "yep, that's still running". And what is going to happen after compaction, when whole context was just waiting? it will loose the plot and when I'm back it just does completely different thing that I asked it to do.
codex also have a bug, that opening refuses to resolve that adds your last steer after compaction, so imagine that you asked it to cleanup some tmp files or refactor/simplify something. it will do that again and again after each compaction, best case it just burns tokens and figures out, this is already done, or worse do it again and mess up everything and forget about it's task
in my experience pi does much better than codex for compaction and token use. And this is the main reason I switched to it.
migrating to the same compaction and exact tools as codex uses will make it at the same level as codex so what benefit will it have over codex? sure you can customize tui to your liking and add something on top, but the efficiency gains will be gone
those models will follow your request when they already agreed to do this
deepseek tends to quickly assume this is benchmark and even when have web access thinks things like "simulated internet" etc (but waste tokens on thinking if there could be way to cheat)
reply