{
  "id": 16104,
  "url": "https://arxiv.org/abs/2608.02345v1",
  "title": "Can AI Agents Simulate A/B Test Outcomes? A Validation Framework for Agentic Experimentation",
  "summary": "A/B testing remains the standard for rolling out new features in the technology industry. Each experiment, however, consumes real traffic, engineering effort, and weeks of wall-clock time. Can AI agents---conditioned on behavioral profiles and contextual descriptions of the intervention---simulate outcomes accurately enough to vet candidate treatments before committing live traffic? We formalize this question as a \\emph{Simulated Randomized Controlled Trial} (S-RCT) and derive a two-layer error",
  "authors": "Stefan Hut, Lorenzo Masoero",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-03T14:58:06.000Z",
  "fetched_at": "2026-08-04T05:10:21.797Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/16104",
  "original_url": "https://arxiv.org/abs/2608.02345v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}