It's not being aggressive, it's just trying throwing shit at problems until it sticks... or doesn't.
That doesn't make it smart or aggressive, if anything it's just been turned to crank tokens until something happens, which doesn't make it a good model.
Why are you positively anthropomorphizing this? It's an LLM, it's been tuned via RL, and it's been tuned by engineers at Anthropic to use a metric fuck-load of sub-agents and tokens to presumably pump their pre-IPO revenue!
A co-worker managed to get Fable to spin up 50 (!!!) sub-agents for a problem which codex worked on with 3 sub-agents. What the hell is going on here? It certainly doesn't mean Fable is "smarter" than Codex.
I've tested it extensively and I'm still using GPT 5.5 High Fast as my primary engineering model. It's far more steerable, writes less, higher quality code, and consistently finds issues and edge cases which are not found by Fable or Opus 4.7.
I don't think calling a model "relentlessly proactive" is positive anthropomorphism.
Spinning up 50 unnecessary subagents is exactly what I'd expect from a "relentlessly proactive" model.
> It's not being aggressive, it's just trying throwing shit at problems until it sticks... or doesn't.
The vast majority of the work the agent did was to reproduce the issue using the limited tooling it had access to. I don't see how that qualifies as "just trying throwing shit at problems until it sticks"