OFIA · CASE STUDY
Product Listener Agent
AI agent that monitors Slack channels for product feedback, classifies bugs / features / ideas, and creates triaged Linear tickets via MCP.
The problem
Product insights were buried in Slack. Bug reports appeared in #engineering and #support-escalations. Feature requests surfaced in #customer-success and #product-feedback. Ideas showed up everywhere. The PM spent 6+ hours per week manually reading channels, triaging requests, creating tickets, and following up. Things still slipped through. High-frequency requests weren't being tracked. There was no systematic synthesis of what customers and teammates actually wanted.
Our approach
An internal listener that monitors all product-related Slack channels, classifies every message as a bug, feature request, idea, or noise, synthesizes conversations into structured output, and triages directly into Linear via MCP — with weekly summaries delivered to the PM.
How it works
- Monitors #product-feedback, #engineering, #customer-success, and #support-escalations continuously.
- Classifies each message and extracts structured details (bug, feature request, idea).
- Groups similar items by theme and tracks request frequency over time.
- Auto-creates Linear bugs with inferred severity (P1 regression / P2 broken / P3 minor) and likely owner.
- Links feature requests to existing epics when matches are found.
- Sends a weekly synthesized Slack pulse to the PM: bugs triaged, requests by frequency, ideas added, trending signals.
What we shipped
- Multi-channel Slack listener
- Message classifier and theme grouper
- Linear MCP integration with severity inference
- Frequency tracker
- Weekly PM pulse via Slack DM
Impact
- No feature request or bug report goes unnoticed.
- PM triage time: 6+ hours/week → quick review of pre-triaged output.
- Frequency tracking enables data-driven prioritization.
Frequently asked questions
How can product teams capture all customer feedback from Slack automatically?
Product teams can capture all customer feedback from Slack automatically by deploying a listener agent that monitors product-related channels continuously, classifies every message, groups duplicates, and triages into Linear — ensuring nothing is missed.
What is the best way to triage product feedback from multiple Slack channels?
The best way to triage product feedback across multiple Slack channels is to use an AI agent that classifies messages in real time, tracks feature request frequency, auto-creates Linear bugs with proper severity, and delivers a weekly structured summary to the PM.
How much PM time can automated product feedback triage save?
Automated product feedback triage saves 6+ hours per week of manual Slack-reading and ticket-creation, freeing the PM to focus on prioritization decisions rather than discovery and data entry.
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