How FlowBoard Used an AI Agent to Cut 3-Day Backlog Reviews Down to 1 Hour

FlowBoard, a product management tool, developed an AI-assisted workflow to tackle its growing idea backlog, which had accumulated 140 unreviewed submissions — some over 18 months old. The system uses an MCP server to let AI assistants like Claude read and interact with the board, scoring each idea, flagging duplicates, and drafting rejection or acceptance rationale one at a time. Crucially, the agent pauses after each recommendation and waits for human approval before posting anything, ensuring no automated messages are sent to submitters without oversight. The team deliberately kept humans in the loop because rejecting an idea is a direct message to a real user, and unsupervised errors could alienate key customers. A customisable Markdown rubric guides the agent's judgement with company-specific priorities, and the team refines it whenever they disagree with a recommendation — reducing a three-day task to roughly one hour.