Apple researchers question how much harness strong MLE agents need
Apple researchers published work examining how much scaffolding autonomous machine learning engineering agents require. They note that modern MLE agents increasingly rely on elaborate machinery such as multi-agent orchestrators and dedicated retrieval subagents, while more primitive but improved coding agents with direct read, write, and bash access to the execution environment have received little attention in the field.
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