---
id: "rlm_axiom_012"
category: "general"
date: "2026-02-23"
source_file: "rlm_axioms_2026_02_23.jsonl"
---

# rlm_axiom_012

**principle**: Map-Reduce over direct LLM attention for large corpora: never feed massive datasets directly into LLM context. Mount as external state, use root model to write Map-Reduce logic, run micro-chunk workers in parallel. O(n^2) → O(n).

**evidence**: DT19b architectural principle. genesis_memory_cortex.py and rlm_army.py both implement chunked processing. Research report batch ingestion uses 800-char chunks, not full document injection.

**strength**: high
