AgentforceAdvancedfeedbacklearningquality
Design feedback loop from human agent corrections to agent improvement
Real World Scenario
Supervisors correct wrong agent answers in Case comments but corrections never reach agent training pipeline; same mistakes repeat.
Expected Answer
• Structured dispositions: agent wrong, knowledge gap, policy change
• Workflow creating knowledge article or topic utterance from repeated corrections
• Weekly review queue of low-CSAT transcripts assigned to content owners
• Track correction themes metrics not anecdotal fixes
• Close loop notification when fix deployed to agent version
• Avoid auto-training on uncorrected noisy feedback
• Governance council prioritizes fix backlog
Follow-Up Questions & Answers
Click to expand — each follow-up includes a direct, interview-ready answer
Direct answer: Structured dispositions: agent wrong, knowledge gap, policy change Also consider: Workflow creating knowledge article or topic utterance from repeated corrections In practice: Weekly review queue of low-CSAT transcripts assigned to content owners Optimize for scale and operational observability.
Architect Perspective
Agents improve only with closed-loop ops — corrections in Case comments are wasted unless piped to owners.