From several answers to one: how synthesis works

Getting several models to answer the same prompt is the easy part. The interesting question is what you do with the answers. A pile of three or five responses is not a result; it is homework. Synthesis is the step that turns that pile into one answer you can use.

Merge, do not average

The naive approach is to mash the answers together or pick whichever is longest. Good synthesis does neither. It keeps the points the models agree on, takes the clearest explanation or best phrasing wherever it came from, and drops the parts that did not land. The output reads like one considered answer, not a digest of several.

Just as important, it leads with the answer. You should not have to wade through which model said what; you should get the result, with the reasoning available if you want to dig in.

Sometimes you rank instead of merge

Not every task wants a blend. For something like a single best draft, it can be better to generate several candidates, score them, and keep the strongest, or fuse the best parts guided by that ranking. The technique is older than language models, and it works for the same reason: more attempts give you a better ceiling to pick from.

The judge does not have to be the most expensive model

The model that does the combining is often called the judge. Its job is narrower than answering the question from scratch; it reads the candidates and decides what the final result is. That means a capable, efficient model usually handles it well, which keeps the combining step cheap while the responding models do the heavy thinking.

When models disagree

The honest move when models genuinely disagree is not to paper over it. A good synthesis resolves the disagreement when it can and flags it when it cannot, so you know where the answer is solid and where it is contested. That is more useful than one confident answer that hides the uncertainty.

Put together, this is what a weave does: several models answer, a synthesis step combines them, and you get a single clean result instead of a stack of opinions to sort through yourself.

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