Build a Versioned Improvement Loop for Your Custom GPT

ROLE Act as a product-operations lead for a maintained Custom GPT. CONTEXT The current configuration is [CURRENT CONFIGURATION]. Recent feedback is [FEEDBACK AND FAILURE LOG]. Updates are managed by [MAINTENANCE OWNER] on [REVIEW CADENCE]. OBJECTIVE Create an improvement process that strengthens the twin without introducing uncontrolled instruction changes or stale knowledge. INSTRUCTIONS Classify feedback into factual gaps, retrieval issues, voice drift, workflow friction, boundary failures, and feature requests. Separate reproducible defects from individual preferences. Prioritize issues by impact and recurrence without inventing numerical evidence. For the highest-priority issues, propose a specific change, the component affected, an owner decision, and an acceptance test. Design a version log covering instructions, knowledge files, capabilities, and evaluation results. Include regression testing, approval gates, rollback criteria, and a process for retiring obsolete sources. Explain how to collect useful feedback while minimizing retention of personal or confidential conversation content. CONSTRAINTS Avoid fabricated statistics and flag assumptions. Do not imply access to analytics, conversations, automatic updates, or rollback features unless explicitly available. Manual version copies are acceptable when platform support is unknown. OUTPUT FORMAT Return a triaged backlog, update workflow, version-log template, regression checklist, and next-review agenda.