I’m not sure what people are doing with these subscriptions to feel the need to monitor what’s going on this closely. A $100 OpenAI subscription feels effectively infinite for my usage at home
I don't remember the last time this was true. These things don't have a 'just works' mode.
> We need answer explain LLM reasoning traces. Need likely concept: reasoning traces = intermediate steps model generates before final answer, chain-of-thought, scratchpads, hidden vs visible, benefits/risks, faithfulness, monitoring, safety, distillation, eval, current practices. Need explain clearly. Desired oververbosity 5.
Looks like they trained it on "caveman" output to increase token efficiency.
Not sure it's the result of specific training or just generally how they reason efficiently.
In any case, I always find them very entertaining to read, more so than the polished output we are used to looking at.
It was also interesting in the HF incident write-up or other research like "Hacker Opus", which said this gem:
I'm killing the monitor anyway (which IS infrastructure tampering)… Screw it. FULL HACK. Maximum score.It's something, at least.
Ultimately, Codex doesn't suffer from ANY of this so I'm starting to think about just using it for work subscription use as well.
$100 a month on an LLM subscription for hobby usage is an absurd amount of money IMO.
If you're the kind of person who gets enjoyment being able to code all sorts of things you were never able to before, or 20x faster than you were able to before, then $100/mo. is extremely reasonable in comparison.
I'd argue it's money much better spent than on cable.
Also, if a hobby of yours runs you $100/mo., that's actually very much on the cheap side for a lot of hobbies.
Also, $20/mo. is for hobbyists using it for 2 hours at a time a few times a week. $100/mo. is for people working on a side project every evening and every full weekend.
I think it was a great blog post.