# Preprint proposes adaptive data structuring to cut agent reasoning costs

_Tuesday, September 1, 2026 at 12:00 AM EDT · Science, AI · Latest · Tier 2 — Notable_

A preprint proposes "agentic data cracking," a method that has an agent structure unstructured documents while answering queries, then reuse that structured information for related future questions. The authors report that an ideal pre-structured store was 28 times cheaper on FanOutQA, and that adding one related question per test question cut costs 53% while preserving accuracy. The method uses a sub-agent branching from already loaded context to extract grounded structure from documents the main agent opens.

## Sources

- [cs.AI updates on arXiv.org](https://arxiv.org/abs/2608.31082)

---
Canonical: https://techandbusiness.org/newswire/IhyG73GkUsF9zZTALAurpU
Retrieved: 2026-09-01T16:49:32.573Z
Publisher: Tech & Business (techandbusiness.org)