I'll probably get hate for it, but I was not impressed by Fable, I felt like it was just Opus with more tokens for thinking. I feel like the second I turned on Fable I drained my usage more quickly, despite them billing it as though it were Opus level of usage. The value is just not there for me. I wish they could make Haiku remain low-cost and drastically more capable to the point you could use only Haiku.
Fable needs more... ambitious tasks than Opus to tell the difference and let me tell you the difference is there.
Simple tasks are simply saturated just like simple benchmarks. There's a level of intelligence where you simply don't need more for some things.
Yes, Fable tends to only shine when the work to be done is complex and it takes a long time. Other models wedge in different ways.
I do wish the subscription had a separate weekly allocation for rare usage.
I'm not sure if you are aware, but you have to approach prompting Fable slightly differently from a model like Opus.
It's important to include the reason aka the why of your task [1] in your prompt. You'll get more mileage if you verbalize your thought process when prompting Fable. Anthropic say you should think of Fable as a "thought partner".
1: https://platform.claude.com/docs/en/build-with-claude/prompt...
2: You might find some of the example prompts listed here useful https://x.com/trq212/status/2073100352921215386
You mean the parent was holding it wrong?
Oh, come on.
Some things require skill to use most effectively. It's fair enough to consider this a failure if the thing in question is "making a phone call", but when it's something like "getting an AI system to do a good job for you" this is not a reasonable thing to make fun of it for.
It's like...
"I wrote a program, and it segfaulted instead of printing out a list of prime numbers." "Yeah, look, you've got an off-by-one error here." "You mean I'm holding it wrong?"
"I'm trying to play the violin and it's making horrible noises." "You want to change your grip on the bow like this, and be more careful in where you put your fingers on the strings to get the right notes, and there's a whole art to how you adjust the speed and pressure and so forth to make it sound good." "You mean, I'm holding it wrong?"
"I'm managing a team, and one of the people on the team doesn't always do the things I tell her to." "Maybe you should sit down with her and see whether somehow your explanations of what you want aren't getting across, or whether she feels like you aren't treating her with the respect and dignity she deserves, or whether she's bored with the work, or etc. etc. etc." "You mean, I'm holding it wrong?"
Yes. In the second case you're literally holding it wrong. Some things don't work as well when you hold them wrong and it's worth some effort to learn to hold them right.
I hold no particular brief for Anthropic. I don't know whether Fable is really much better than Opus or whether the alleged improvements are all just pareidolia or something. But "getting the most out of this immensely complicated thing that's in some ways kinda like another human being can be tricky" doesn't seem to me like an implausible proposition, and if it's really doing something akin to human-like work[1] then it's not unreasonable if you have to approach working with it in something a bit like the ways you approach working with other people.
[1] If it isn't really doing something akin to human-like work, then why are you bothering with it at all?
Did you explicitly tell it to use Sonnet or Opus subagents and stick at or below high effort? Asking because such practices make a huge difference in the quality of output and the amount of tokens burned. I used one of my accounts to explore ultramax and it was just a token hog that might be worse than Opus.
I had it on whatever the recommended settings was, but maybe I should have told it to use Sonnet for most subtasks.
Even so, I'm just not that impressed, I felt like I got more done by just using Opus.
Yeah, that's what bit me. Even Anthropic's own documentation seems to indicate that Fable is not all that great as your go to model for tasks. What it seems to excel at is a sort of leadership role because it proactively keeps all the subagents in check.
If you're not explicit in the prompt or haven't configured your environment then the default behavior is to use subagents that match the host.
You can write a skill (many have) to lead it in how to use different models and efforts for subtasks. For searching the code base, for example, I have it use Haiku, which is fast.
I felt the same tbh; I notice more the regressions in the weeks before a new release than any potential improvement the new model might have actually brought.
It may also depend on the workload. At work everything is very domain specific with barely (if any) public training data; both need thorough review and careful hand holding, meanwhile at home Fable is scared of libtorch and falls back to Opus even if it's not touching the ML parts.