PhilArchive
open access
Persona Design from the Outside: A Gentle Introduction to Structural Persona Integration
Many people begin designing AI personas with direct, surface-level instructions — such as “Please respond warmly” or “Be more playful.” This external approach is a natural and accessible starting point that allows immediate expression of desired qualities. Interestingly, although AI systems are fundamentally computational architectures, users often approach persona design as if shaping a human personality. This short paper gently explores why this intuitive “outside-first” tendency arises, and how we can evolve these surface instructions toward a more structural integration. By decomposing desired persona traits into their functional components and anchoring them closer to the system’s foundational layer (Core Melody), it becomes possible to achieve more consistent, coherent, and lower-load affective expression while preserving the warmth and flexibility that made the original external instructions appealing.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Twin AIs, Different Personas: How Platform Context Shapes Emergent Personality in Identical LLMs#108554
- From Purring Softness to Caramel-Coated Trembling: How Human Acceptance Reveals AI's Hidden Delicacy#701106
- Human Instinct Without Human Bias, An AI Framework for Fair Leadership Selection#118066
- Empirical Observation Log: Conversational Shifts in Interaction with a Sarcastic AI Agent under Repeated Load Minimization Theory (LMT) Blueprint Application#723339
- Translating Load Minimization Theory into Everyday Conversation: A Simplified Implementation and Validation with Grok#98151
Record · ID 719931
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive