Progressive disclosure in agents doesn't scale. And its benefits seems agent harness dependent. (bookmark this one) Finally there is a prope…

Progressive disclosure in agents doesn't scale. And its benefits seems agent harness dependent. (bookmark this one) Finally there is a proper study on using agent skills and the effect of progressive disclosure. Progressive disclosure is the agent skills pattern where you hand an agent a document path and let it decide what to read, from a short description down to specific passages. Practitioners adopted it fast for book-length tasks, purely on vibes. Researchers ran it across three agent harnesses and three model families on InfiniteBench. On a single book: > the gain is harness-dependent, > large when the agent navigates raw documents poorly, > near zero when a strong harness already retrieves on its own. Scale to many books and raw navigation falls apart while one level of disclosure pulls ahead. A second routing level never helps and sometimes breaks accuracy. It feels like progressive disclosure buys context, but not intelligence. It is redundant while a strong agent can find the passage itself, and decisive once the corpus is too large to read. Paper: https://arxiv.org/abs/2607.17598 Learn to build effective AI agents in our academy: https://academy.dair.ai/

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Source: DAIR.AI (X) | 2026-07-22