blue/.blue/docs/dialogues/rfc-0017-dynamic-context-activation.dialogue.recorded.md

Alignment Dialogue: RFC 0017 Dynamic Context Activation

Date	2026-01-25
Experts	12
Rounds	2
Convergence	95%
Status	Complete

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Summary

Deliberation on Phase 3 features for RFC 0016 Context Injection Architecture: refresh triggers, relevance graph computation, and staleness detection.

Panel

Expert	Domain	Key Contribution
Systems Architect	Architecture	Event-sourced design via audit log; hybrid lazy evaluation
Performance Engineer	Efficiency	Content-addressed cache; mtime-first staleness; token budget enforcement
UX Designer	Experience	Context breadcrumbs; predictable refresh moments; progressive disclosure
Data Scientist	Algorithms	PageRank relevance; co-access matrix; Bayesian staleness
Security Engineer	Security	Cryptographic hashes; rate limiting; plugin sandboxing
Distributed Systems	Consistency	Version vectors; bounded staleness; materialized relevance view
Cognitive Scientist	Cognition	Hysteresis for refresh; reasoning continuity; tier-appropriate thresholds
Product Manager	Prioritization	MVP = on_rfc_change only; defer ML; success metrics first
Database Engineer	Data Model	relevance_edges table; staleness indexes; efficient queries
ML Engineer	Learning	Graceful degradation ladder; bandit trigger learning; cold start mitigation
DevOps Engineer	Operations	Structured audit logging; refresh metrics; circuit breakers
Philosophy/Ethics	Ethics	Transparency imperative; user agency; coherence constraints

Round 1: Perspectives

Strong Convergence (7+ experts)

1. Event-sourced staleness - Use content hash comparison from audit log, not calendar time
2. on_rfc_change as MVP trigger - Ship simplest valuable trigger first
3. Materialized relevance graph - Compute on write, cache aggressively
4. Tiered staleness thresholds - ADRs stable (session-start only), RFCs volatile (every state change)
5. Rate limiting - Circuit breakers to prevent refresh storms
6. Transparent context changes - Announce what context updated and why
7. Version vectors - Efficient O(1) staleness checks per document

Tensions Identified

ID	Tension	Positions
T1	ML Complexity	Data Scientist wants full ML stack vs Product Manager wants explicit links only
T2	User Control	Philosophy wants advisory defaults vs UX wants automation that "just works"
T3	Session Identity	Security wants crypto random vs Systems needs persistence across restarts

Round 2: Synthesis

T1 Resolution: Phased Relevance (ML as optimization, not feature)

Phase 0: Explicit links only (declared relationships) Phase 1: Weighted explicit (recency decay, access frequency) Phase 2: Keyword expansion (TF-IDF suggestions) Phase 3: ML gate review - proceed only if:

• Explicit links have >80% precision but <50% recall

• 1000 co-access events logged

• Keyword suggestions clicked >15% Phase 4: Full ML (if gated)

T2 Resolution: Predictability is agency

Tier	Control Model	Notification
1-2	Automatic	Silent (user action is the notification)
3	Advisory	Inline subtle ("Reading related tests...")
4	Explicit consent	Prompt as capability ("I can scan...want me to?")

Honor Test: If user asks "what context do you have?", answer should match intuition.

T3 Resolution: Composite session identity

Session ID: {repo}-{realm}-{random12}
Example: blue-default-a7f3c9e2d1b4

• Stable prefix enables log correlation via SQL LIKE queries
• Random suffix ensures global uniqueness and unpredictability
• No schema changes for MVP; optional parent_session_id for v2

Scoreboard

Expert	W	C	T	R	Total
Systems Architect	9	9	8	9	35
Cognitive Scientist	9	8	9	9	35
Database Engineer	9	8	9	9	35
Philosophy/Ethics	9	8	9	9	35
Distributed Systems	9	9	8	8	34
DevOps Engineer	8	9	9	8	34
Performance Engineer	8	8	9	8	33
UX Designer	8	9	8	8	33
Data Scientist	9	7	8	9	33
Security Engineer	8	8	9	8	33
Product Manager	8	9	9	7	33
ML Engineer	8	7	8	8	31

Recommendations for RFC 0017

1. MVP Scope: Implement on_rfc_change trigger with content-hash staleness
2. Architecture: Event-sourced from context_injections; pluggable relevance scorer
3. Session Identity: Composite {repo}-{realm}-{random12} format
4. Notification Model: Tier-based (automatic → advisory → consent)
5. Relevance Graph: Start with explicit links; gate ML on usage metrics
6. Staleness: Per-document-type thresholds; hash-based, not time-based
7. Safety: Rate limiting (max 1 refresh per 30s); circuit breakers

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Dialogue orchestrated by 💙 Judge with 12 domain experts across 2 rounds.