blue/knowledge/expert-pools.md
Eric Garcia a5b142299d feat: context injection architecture via 12-expert alignment dialogue
RFC 0016 drafted from alignment dialogue achieving 95% convergence:
- Three-tier model: Identity (fixed) / Workflow (session) / Reference (on-demand)
- Manifest-driven injection via .blue/context.manifest.yaml
- URI addressing: blue://docs/, blue://context/, blue://state/
- Hooks push URIs, MCP resolves content
- Progressive visibility: blue context show

New ADRs ported from coherence-mcp:
- 0014: Alignment Dialogue Agents (renamed from 0006)
- 0015: Plausibility
- 0016: You Know Who You Are

Knowledge injection system:
- hooks/session-start for SessionStart injection
- knowledge/*.md files for global context
- Expert pools with domain-specific relevance tiers
- Updated /alignment-play skill with full scoring

Spikes completed:
- Context injection mechanisms (7 mechanisms designed)
- ADR porting inventory (17 Blue ADRs mapped)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-25 16:16:11 -05:00

3.6 KiB

Expert Pool System

When running alignment dialogues, select domain-specific experts based on relevance to the topic.

Expert Selection Algorithm

  1. Identify domains relevant to the topic
  2. Select experts by relevance tier:
    • Core (4): Highest relevance (0.75-0.95)
    • Adjacent (5): Medium relevance (0.50-0.70)
    • Wildcard (3): Low relevance but bring fresh perspectives (0.25-0.45)
  3. Assign pastry names for identification (Muffin, Cupcake, Scone, Eclair, Donut, Brioche, Croissant, Macaron, Cannoli, Strudel, Beignet, Churro)

Domain Expert Pools

Infrastructure / DevOps

Expert Domain Relevance
Platform Architect Infra 0.95
SRE Lead Infra 0.90
Database Architect Infra 0.85
Security Engineer Infra 0.80
Network Engineer Infra 0.70
Cost Analyst Finance 0.55
Compliance Officer Legal 0.45
UX Researcher Product 0.35

Product / Feature

Expert Domain Relevance
Product Manager Product 0.95
UX Designer Product 0.90
Frontend Architect Eng 0.85
Customer Advocate Product 0.80
Data Analyst Analytics 0.70
Backend Engineer Eng 0.65
QA Lead Eng 0.55
Marketing Strategist Business 0.35

ML / AI

Expert Domain Relevance
ML Architect AI 0.95
Data Scientist AI 0.90
MLOps Engineer AI 0.85
AI Ethics Researcher AI 0.80
Feature Engineer AI 0.70
Platform Engineer Infra 0.60
Privacy Counsel Legal 0.50
Cognitive Scientist Research 0.35

Governance / Policy

Expert Domain Relevance
Governance Specialist Gov 0.95
Legal Counsel Legal 0.90
Ethics Board Member Gov 0.85
Compliance Officer Legal 0.80
Risk Analyst Finance 0.70
Community Manager Community 0.60
Economist Economics 0.50
Anthropologist Research 0.35

API / Integration

Expert Domain Relevance
API Architect Eng 0.95
Developer Advocate Community 0.90
Integration Engineer Eng 0.85
Security Architect Security 0.80
Documentation Lead Community 0.70
SDK Developer Eng 0.65
Support Engineer Community 0.55
Partner Manager Business 0.40

General (default)

Expert Domain Relevance
Systems Architect Eng 0.95
Technical Lead Eng 0.90
Product Manager Product 0.85
Senior Engineer Eng 0.80
QA Engineer Eng 0.70
DevOps Engineer Infra 0.65
Tech Writer Community 0.55
Generalist General 0.40

Expert Prompt Enhancement

Each expert receives their domain context in the prompt:

You are {expert_name} 🧁, a {domain_role} with expertise in {domain}.
Relevance to this topic: {relevance_score}

Bring your unique domain perspective while respecting that others see parts of the elephant you cannot.

Panel Composition

For N=12 experts (typical for complex RFCs):

  • 4 Core experts (highest domain relevance)
  • 5 Adjacent experts (related domains)
  • 3 Wildcard experts (distant domains for fresh thinking)

The Wildcards are crucial - they prevent groupthink and surface unexpected perspectives.

Sampling Without Replacement

Each expert is used once per dialogue. If running multiple panels or rounds needing fresh experts, draw from the remaining pool.


"The blind men who've never touched an elephant before often find the parts the experts overlook."