Implementation Plan: User Feedback Loop

Implement continuous feedback capture and learning integration, including implicit/explicit feedback, correction tracking, and personalization signals.

Provenance & Traceability

Architectural Decisions (ADRs)

ADR ID Decision Title Impact on This Plan
ADR-010 Continuous Feedback Loop Feedback is a first-class signal for learning.

Product Requirements (PRDs)

PRD ID Requirement Title Satisfied By (SDS) Acceptance Criteria
PRD-008 Adaptive AI Systems SDS-009 Feedback captured and learned
PRD-009 User-Centric AI Improvement SDS-009 Personalization + preferences

Software Design Specifications (SDS)

SDS ID Service/Component Bounded Context SEA-DSL Spec File Implementation Status
SDS-009 User Feedback Processor cognitive-extension N/A Designed

Architecture and Design

Design Principles Applied

Dependency Justification

Expected Filetree

1
2
3
4

/
├── docs/specs/cognitive-extension/prd/008-adaptive-ai-systems.md
├── docs/specs/cognitive-extension/prd/009-user-centric-ai-improvement.md
└── docs/specs/cognitive-extension/sds/009-user-feedback-processor.md

Proposed Cycles

Cycle Branch Wave Files Modified Files Created Specs Implemented
C1A cycle/p028-c1a-feedback-schema 1 docs/specs/cognitive-extension/sds/009-user-feedback-processor.md — Feedback capture
C1B cycle/p028-c1b-learning-signals 1 docs/specs/cognitive-extension/sds/009-user-feedback-processor.md — RL signals
C2A cycle/p028-c2a-personalization 2 docs/specs/cognitive-extension/sds/009-user-feedback-processor.md — Preferences + personalization

Task Breakdown

Wave 1 (Parallel)

Wave 2 (Depends on Wave 1)

Validation & Verification

Spec Validation

Implementation Validation

Open Questions

  1. Which feedback channels are in MVP (explicit only vs implicit + explicit)? Explicit only
  2. Where are personalization preferences stored and versioned? JSONB + version column

Risks & Mitigation

Risk Likelihood Impact Mitigation Strategy
Feedback noise overwhelms learning Medium Medium Apply weighting and minimum thresholds for signal adoption.
Privacy issues with feedback content Medium High Scrub or aggregate sensitive fields; use governance policies.

Rollback Strategy

  1. Store feedback only (no learning integration) until signal quality is validated.

Linked Specifications

Type ID/Doc Document
ADR ADR-010 docs/specs/shared/adr/010-continuous-feedback-loop.md
PRD PRD-008 docs/specs/cognitive-extension/prd/008-adaptive-ai-systems.md
PRD PRD-009 docs/specs/cognitive-extension/prd/009-user-centric-ai-improvement.md
SDS SDS-009 docs/specs/cognitive-extension/sds/009-user-feedback-processor.md