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The curiosity is inefficient though. So many times I have to stop the agent and tell it to just fucking write the code and try compiling it. Otherwise it will fill its entire context tracing through the program logic to derive from the code itself whether the thing it is about to do would work. It completely fails to notice it can just… try.
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Everything about LLMs is inefficient. They have their benefits but watching them reason over things that are painfully obvious, that they've literally investigated before (before a memory compaction), never take a step back aand be like 'this is going too slow let me look for a better way', etc. is painful.
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It's tuned for the kinds of tasks where "just try" doesn't get good results.

A major complaint with AI code was that AIs struggle with complex codebases, don't respect existing conventions, reinvent functionality multiple times over, etc. So, newer high end AIs are tuned with the "explore/exploit" dial turned towards "explore".

You could probably get it to do things "quick and dirty" with prompting, but that, of course, requires prompting for it.

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Perhaps what is missing is a better memory/caching layer to avoid doing the same for explorations over and over again.
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Fable and sub agents are two different things. There are many situations for which Fable is great, but Fable doesn't have to run in a sub agent. You can use it for your main agent and that works fine.

Or are you saying my sub agents burned so many tokens because they were all using Fable, whereas my main agent could do the same job with a lesser model?

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I think the commenter (who is not me) is saying to use Fable as the main agent but then use lesser models for your subagents so that you get the advantages of Fable to plan but then the subagents don’t cost as much, and may be more focused because they lack Fable’s thinking modes.
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But how is that better than a single agent searching those "angles" sequentially?

Unless they are orthogonal they most likely require similar context anyway so multiple sub agent is just wasteful.

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doesnt intelligence involve knowing where to start and what to read and not just throwing everything in the bag.

im on local only AI and subagents are only valuable when they avoid polluting the context with extraneous file reads and parallel exploration when fixes are linear.

as OP is on about, subagents burn tokens because they arnt a deterministic intelligent gatherer but like pooluring water into a maze hoping the exit will illuminate.

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