Problem
S4 personas are persona_0 through persona_99 with no identity. The LLM invents a different persona each call with no consistency. 100 calls to the same model produce votes that correlate too highly — consensus, not diversity.
Suggested Improvements
- Define 5-10 named persona archetypes with demographics, preferences, and viewing habits
- e.g., "college student who watches during commute, saves practical tips, shares humor"
- e.g., "millennial parent, watches after kids sleep, engages with relatable parenting content"
- Give each persona a content preference history ("liked videos about X, skipped Y")
- Vary voting prompt per persona type — different evaluation criteria
- Consider different temperature settings per persona for vote diversity
- Once feedback data exists, calibrate persona preferences against actual performance
Context
See design/pipeline-quality-review.md
Depends on
Problem
S4 personas are
persona_0throughpersona_99with no identity. The LLM invents a different persona each call with no consistency. 100 calls to the same model produce votes that correlate too highly — consensus, not diversity.Suggested Improvements
Context
See
design/pipeline-quality-review.mdDepends on