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AI Characters & Conversational NPCs

English edition. The Japanese edition (../../ai-characters/) is the source of truth; this translation may lag behind it.

This is the first area where this knowledge base aims to be the best in the world. Scope: characters that talk through an LLM, remember, and build a relationship with the player — game NPCs, AI companions, AI VTubers, and official IP characters brought to life with AI.

Why this area

  1. It changes the most. It is the clearest example of an experience that cannot exist without AI.
  2. Knowledge is fragmented. Game AI research, companion apps, streaming culture and regulation are discussed in separate silos.
  3. Japan has an edge. Character culture, VTubers, voice actors — and, since August 2026, a Ministry of Justice guideline on voice rights.
  4. Regulation now shapes design directly. The scope of a character's conversation alone can change its legal classification (see pattern P01).

Contents

File What it is Use it for
patterns.md 38 design patterns in 7 groups A reference while planning and designing
case-studies.md 14 case studies (3 from Japan), successes and failures Evidence of what has actually happened
evaluation.md A five-layer evaluation framework with release gates Development, QA and ship decisions
playbook-persuasion-npc.md Playbook: building NPCs that make persuasion a game (from our own experiments) When implementing

Five principles (the catalog in one screen)

  1. Decide the conversation scope first. Experience, cost and legal classification all follow from it (P01).
  2. The engine owns facts and rules. Never let what the LLM says become game truth (P16).
  3. Don't let the character judge itself. Persuasion outcomes are scored by a separate judge (P17).
  4. Keep relationships as numeric state. Affinity must not depend on the LLM's mood (P11).
  5. Design the ending. Endless conversation is a weakness for wellbeing and for compliance (P22).

Experiments

A small harness that compares a naive NPC engine with one that applies these patterns lives in prototype/; results are logged in experiments/.