{
  "id": 427,
  "url": "https://arxiv.org/abs/2607.00049v1",
  "title": "Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study",
  "summary": "Large Language Models (LLMs) are increasingly used in Agile Software Development for documentation, coaching, and training. As practitioners adopt these tools to prepare for certifications such as Professional Scrum Master (PSM), a key question is whether LLMs can reliably reason about Scrum, a framework with normative, well-defined rules described in the Scrum Guide (2020). This paper examines how different prompt techniques affect the factual accuracy of LLM responses to Scrum certification-st",
  "authors": "Mirko Perkusich, Danyllo Albuquerque, João Paiva, Robson Vilar, Emanuel Dantas, Ademar França de Sousa Neto et al.",
  "category": "research",
  "topics": null,
  "orgs": "openai",
  "regions": null,
  "published_at": "2026-06-29T23:55:14.000Z",
  "fetched_at": "2026-07-14T14:14:32.646Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/427",
  "original_url": "https://arxiv.org/abs/2607.00049v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}