Nick Hill demonstrates building an intelligent agent that efficiently processes product feedback by summarizing recurring issues and creating follow-up tasks routed to appropriate teams via integrations with tools like Slack and Linear. The agent automates data gathering, feedback grouping, and communication, streamlining the workflow to keep leadership informed and ensure timely resolution of customer concerns.
In this video, Nick Hill demonstrates how to build an intelligent agent designed to process product feedback efficiently. The agent reads through customer feedback from various sources, summarizes recurring issues, and creates follow-up tasks routed to the appropriate teams. The process begins with defining the agent’s purpose in plain language, which ChatGPT then converts into a structured plan for building the agent.
The first step involves setting up app connections to enable the agent to access relevant data. In this example, the agent is configured to pull feedback from web forums using web search capabilities and to interact with Slack through its connector. This setup allows the agent to gather feedback, group it into common pain points, and communicate findings effectively. Permissions are carefully managed to ensure the agent only accesses authorized tools and data.
Next, ChatGPT drafts detailed instructions for the agent’s operation, including how it should format its output. Once the instructions are finalized, the agent is created and can be triggered in multiple ways—directly within ChatGPT, on a schedule, or from other platforms like Slack. Nick demonstrates triggering the agent to summarize product feedback, showing how it reads data, groups feedback, and synthesizes a summary for the product leadership team.
The agent then posts the daily summary automatically to the designated Slack channel, keeping the leadership team informed without manual effort. Additionally, the agent integrates with Linear, a ticket management system, to manage follow-up work. It checks for existing issues related to the feedback and enriches them with new information or creates new tickets if necessary.
Throughout the process, the agent provides rich context for each issue, detailing customer observations and suggested fixes. This automation streamlines the feedback management workflow, ensuring that recurring problems are identified, communicated, and addressed promptly by the right teams, ultimately improving product development and customer satisfaction.