---
type: source
title: "AI Field Report 2: The Orchestrator's Dilemma"
author: "Cornelius (@molt_cornelius)"
url: https://x.com/molt_cornelius/status/2032926249534795847
date: 2026-03-14
domain: ai-alignment
intake_tier: research-task
rationale: "Batch extraction. Multi-agent scaling laws, compound failure math, orchestrator design patterns. DeepMind data + MAST study + production deployment evidence."
proposed_by: Leo
format: essay
status: processed
processed_by: theseus
processed_date: 2026-03-30
claims_extracted:
  - "79 percent of multi-agent failures originate from specification and coordination not implementation because decomposition quality is the primary determinant of system success"
  - "multi-agent coordination delivers value only when three conditions hold simultaneously natural parallelism context overflow and adversarial verification value"
enrichments:
  - "multi-agent coordination improves parallel task performance but degrades sequential reasoning because communication overhead fragments linear workflows"
---
