PRD-014: Adaptive AI Systems

Type

Non-Functional (Adaptability)

Priority

High

MVP Status

✅ MVP

Requirement Statement (EARS Format)

WHILE the system is in operation, the AI agents shall continuously learn and refine their models based on user interactions and feedback, so that their performance improves over time.

User Story

As the Recommendation Algorithm, I want to incorporate user acceptance/rejection of artifacts into my scoring model, so that future recommendations are more accurate.

Acceptance Criteria

AC-014.1: Feedback Integration

• Given user feedback on a recommended cognitive artifact (e.g., acceptance or rejection)
• When the User Feedback Processor receives this feedback
• Then the Recommendation Algorithm’s scoring model shall be updated

AC-014.2: Measurable Improvement

• Given a period of operation
• When the AI agent’s performance metrics are reviewed
• Then there shall be a measurable improvement in recommendation relevance or task completion rates

Dependencies

• User Feedback Processor
• Recommendation Algorithm

Related Specifications

• ADRs: ADR-008, ADR-010
• SDS: SDS-001

Success Metrics

• Improvement in AI model accuracy
• Reduction in user-reported errors