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[2602.14433] Synthetic Reader Panels: Tournament-Based Ideation with LLM Personas for Autonomous Publishing
Summary
The paper discusses a novel system for autonomous book ideation using synthetic reader panels composed of LLM personas to evaluate book concepts through structured tournaments.
Why It Matters
This research highlights the potential of AI in the publishing industry, offering a method to enhance the ideation process by replacing traditional focus groups with diverse, automated evaluations. It addresses the need for more effective content validation and market alignment in publishing.
Key Takeaways
- Synthetic reader panels can replace human focus groups in book ideation.
- Panels are tailored to reflect target demographics, ensuring diverse representation.
- Tournament-based evaluations enhance the quality of book concepts by filtering out low-quality ideas.
Computer Science > Computers and Society arXiv:2602.14433 (cs) [Submitted on 16 Feb 2026] Title:Synthetic Reader Panels: Tournament-Based Ideation with LLM Personas for Autonomous Publishing Authors:Fred Zimmerman View a PDF of the paper titled Synthetic Reader Panels: Tournament-Based Ideation with LLM Personas for Autonomous Publishing, by Fred Zimmerman View PDF HTML (experimental) Abstract:We present a system for autonomous book ideation that replaces human focus groups with synthetic reader panels -- diverse collections of LLM-instantiated reader personas that evaluate book concepts through structured tournament competitions. Each persona is defined by demographic attributes (age group, gender, income, education, reading level), behavioral patterns (books per year, genre preferences, discovery methods, price sensitivity), and consistency parameters. Panels are composed per imprint to reflect target demographics, with diversity constraints ensuring representation across age, reading level, and genre affinity. Book concepts compete in single-elimination, double-elimination, round-robin, or Swiss-system tournaments, judged against weighted criteria including market appeal, originality, and execution potential. To reject low-quality LLM evaluations, we implement five automated anti-slop checks (repetitive phrasing, generic framing, circular reasoning, score clustering, audience mismatch). We report results from deployment within a multi-imprint publishing operation managi...
