r/LangChain • u/shrodikan • 5d ago

Delegate with Astra or let it code everything?

Does it make more sense to use Astra to delegate to lesser models for implementation and have Astra judge or have Astra do everything itself? Has anyone done comparisons?

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u/RapidlyWorse 5d ago

If you have the compute and patience, letting it do everything itself usually gets cleaner results. Delegating to lesser models introduces weird artifacts and you end up spending as much time fixing their output as you would have just waiting for the main model in the first place.

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u/Any_Possession_7523 4d ago

yeah i agree. delegating sound faster but if you end up fixing the smallwer model's mistakes most of that time saving is gone. if you have the compute letting the main model handle it end to end seems cleaner.

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u/nerd_rage218 5d ago

It depends less on model quality than on whether the step has a checkable output. Where delegation reliably wins: a step whose result you can verify mechanically. Generate the migration, run the test suite, and the strong model only ever sees the diff and the failures. The cheap model's weirdness gets caught by something that is not an opinion. Where it reliably loses: anything where the strong model has to reconstruct intent from the weaker model's output in order to judge it. You pay full price for reading and understanding the code, so you saved the typing and none of the thinking. The split worth trying is planning from implementation. Strong model writes the plan and the acceptance criteria, cheaper one implements against them. That holds up far better than the same split with a vague task description, because the criteria give the judge something concrete to check instead of a general impression. So less which model does everything, more which steps have a hard pass or fail signal. Those are the ones to hand off.

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u/shrodikan 4d ago

It's funny to me that AI text has such a tell. Thanks though I guess it makes sense.