How can a LLM be assigned an emotion as being "proactive". This is highly misleading to anyone that scans just the headlines.
What actually happened is that the user started a prompt, and Claude took $12 worth of tokens to resolve the issue. How it did so was basically looping until it got to the answer
How is this proactive? It's literally being token greedy and maximising revenue for the LLM owner. People really need to be putting on business hats at this stage, because we are being lead to believe that "more tokens = better". It is not, there are efficient ways to solve a problem and there are inefficient ways to do so too.
Each problem solved incurs a cost, and is expected to yield an ROI at some point. This is how we should be viewing things now.
> How can a LLM be assigned an emotion as being "proactive"
I can't edit my post, this is wrong. "Proactive" is defined as a behaviour instead of an emotion.
Thanks to everyone pointing it out!
Is proactivity an emotion? Surely its a behaviour?
Compared to other models that halt the loop on intermediate steps, or to ask further clarification, even if it's not the human equivalent of proactive, you see the similarity, right?
I've definitely never heard proactivity described as being an emotion. Doesn't really make any sense
I was trying to capture the idea that Claude Fable will act a whole lot more aggressively in pursuit of the goals that you set it than other models I've worked with.
The case I described is a good example of this. I told it to fix a scroll bar, and it built test HTML pages and a throwaway Python server and tried several ways of testing in a browser before settling on a weird Frankenstein mechanism because it identified that Playwright WebKit wasn't suffering from the bug but macOS Safari was.
... and it spent $12 of tokens to get there.
I think "proactive" is a good and relatively non-anthropomorphic term for this. I also considered "plucky" and "keen", which I think are more emotional words than "proactive".
> People really need to be putting on business hats at this stage, because we are being lead to believe that "more tokens = better".
I didn't intend my post to imply that spending $12 of tokens to fix a two lines CSS bug was "better".
Super appreciate you replying to my comment.
I think I understand where you're coming from now. What confused me is that the post is written in a way that it seemed like what Fable was doing was actually better. Maybe I should've looked at post as an exploratory post on Fable instead.
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"
Proactive is a word literally describing actions, not emotions.