I launched @zarosabe.
Not to chase the next meta, but to outlast them all.
If narratives are temporary, then ownership shouldn't be.
The experiment begins.
Built on @base via @clanker_world.
CA: 0xeB68C7efC185965199f5C260F15D5ebA3340db07
Full thinking here:
The most critical part that codex needs to improve is context compaction.
If that can be fast, reliable, without timeout or nasty reconnections,
thats actually the best selling point.
I still believe that the real winner for AI providers battle still going to be the one that:
- super cheap
- not too smart
- can do basic needs for consumer
in the end, most people in the world still need help for basic needs.
high IQ model is not public needs.
"Codex is letting you to finish the task" is not an unlimited use.
it bypasses the 5h limit by eating your weekly limit.
So once your weekly limit is gone,
you still get the limit error and it stops.
summary: don't use /goal on your $20 plan.
UI Tips with GPT models:
never use GPT-5.5 for UI job ever.
it has the similar capability as 5.4, same potential mistakes, and more creativity that causing drifts.
And it also more expensive (2x price).
better stick with GPT-5.4,
or use Claude.
People with simple tasks should never use GPT-5.5.
It's still can make mistakes, and it's expensive.
use GPT-5.5 as orchestrator to select the correct model for your task. That's why agent loop is important.
or just you chinese cheap model for your simple task.
long thread basically wasting time even you do compactions.
my gpt-5.5 works like hours facing websockets error mostly, and that shit only happens on long thread.
- Codex is slow on long thread.
- OpenAI banning some payment methods paying users, but adding reset limit feature that abuseable via free account in exchange to pump fake number codex usage pre-IPO.
Looks like June is Anthropic month.
Soon, GPT will follow Fable.
API only for frontier, and you will only get that GPT-5.5 expensive model via subscription. kek...
the gap for frontier model is coming.
@ShanuMathew93 you have 1 agent (loop master), controlling other agents.
You give loop master a goal.
It then controlling/prompting other agents to reach that goal.
So, your job is only defining the goal.
Loop master will report back once the goal reached.