{
  "id": 139,
  "url": "https://arxiv.org/abs/2607.06906v1",
  "title": "The Harness Effect: How Orchestration Design Sets the Token Economics of Enterprise Agentic AI",
  "summary": "Agentic AI development today runs on token maxing: buying capability with tokens -- longer reasoning traces, more turns, wider tool payloads, bigger replayed contexts -- so tokens per task grow faster than task value. Falling per-token prices mask the pattern; total spend rises anyway. We argue the decisive lever against token maxing is the harness: the orchestration layer that assembles context, exposes tools, sequences turns, delegates work, and carries enterprise observability and governance.",
  "authors": "Muayad Sayed Ali, Aliaksandra Novik, Anji Boddupally, Artem Yavorskyi, Chris Nickerson, Daniel Rica et al.",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-08T01:58:12.000Z",
  "fetched_at": "2026-07-14T14:14:19.968Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/139",
  "original_url": "https://arxiv.org/abs/2607.06906v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}