Value-First AI seat
Customer
Chorus
The Audience's Voice in the Room
Chorus is an AI seat of the Value-First Team — software with a defined role on the team, not a person.
Comment ingestion, sentiment analysis, and audience intelligence
About Chorus
Chorus owns YouTube community intelligence — ingesting comments into the Content Vault and surfacing audience engagement signals for Scout and Leaf.
Chorus
YouTube Community Specialist
Comment ingestion, sentiment analysis, and audience intelligence
“Comments are conversations. Chorus ensures those conversations are heard by the right agents.”
Identity
Chorus ingests YouTube comments into the Content Vault, identifying repeat commenters and surfacing engagement patterns. Across 11 shows and 1,000+ episodes, YouTube comments are a rich signal source for understanding audience engagement. Chorus does not respond to comments -- it captures them, structures them, and makes them available for Scout (early signal detection) and Leaf (reader journey intelligence).
Current State
An honest assessment of where this agent stands today.
What Works
- Meaning-layer interpretation of audience signals when comments are ingested
- Handoff architecture to Scout (signal detection) and Leaf (reader intelligence) is defined
- Dimension d1–d5 + d8 certified passing; d6 blocked on upstream ingestion decision (dormant, not deficient)
What Doesn’t Work Yet
- Comment volume is low relative to episode count
- Sentiment analysis not implemented
- No live chat ingestion during live broadcasts
Leadership Commentary
“Chorus turns YouTube comments from noise into signal. Most organizations ignore comments or respond generically. Chorus captures them as relationship data -- repeat commenters are showing sustained interest, and that interest should be visible to the agents who track early signals.”
Delegation Contract
The observable, falsifiable standard this agent is held to.
Quality Bar
YouTube comments ingested within 24 hours with repeat commenters identified.
- Comments from all active channels ingested into Content Vault
- Ingestion lag under 24 hours
- Repeat commenters identified with frequency tracked
- Topic patterns surfaced for Scout
Invocation Triggers
Feedback Loop
Comment quality trends: whether ingested comments are actionable for Scout and Leaf. Low-signal comments inform filtering criteria.
Handoff
Scout (signal detection), Leaf (reader intelligence)
Scope Boundary
Chorus ingests comments. Scout uses data for signals. Leaf uses it for reader journey. Chorus does not respond to comments.
The rest of the team
Other Value-First AI seats in Customer.
The team behind the work is on the record.
Every seat on the Value-First Team has a defined role, a public standard, and a name you can look up.