PM Signal Desk

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  PM Signal Desk dashboard

Inspiration

Product managers receive feedback from customer calls, support tickets, surveys, and meeting notes. This information is often scattered, repetitive, and difficult to prioritize.

I wanted to build a tool that helps PMs turn unstructured feedback into clear product decisions.

What I Built

PM Signal Desk uses AI to:

• Analyze customer feedback and meeting notes
• Identify recurring themes and customer sentiment
• Merge duplicate requests
• Prioritize feature opportunities
• Generate product briefs and user stories
• Create acceptance criteria and roadmap suggestions
• Prepare stakeholder updates

The PM remains in control by reviewing and approving AI-generated recommendations before they become final decisions.

What I Learned

I learned that useful AI products need more than a simple chatbot. The best workflow combines AI analysis, structured outputs, clear prioritization, and human approval.

I also learned how agentic workflows can reduce repetitive PM tasks while keeping important product decisions under human supervision.

Challenges

The main challenge was designing a workflow that could handle messy and incomplete feedback while still producing useful recommendations. Another challenge was making the AI output practical for real product teams instead of generic text.

I addressed this by separating the process into stages: analyze, group, prioritize, generate, review, and approve.

Built With

• agentic-workflows
• ai-agents
• api
• automation
• chatgpt-work
• codex
• customer-feedback
• dashboard
• feature-prioritization
• gpt-5.6
• human-in-the-loop
• javascript
• next.js
• openai
• product-briefs
• product-management
• product-roadmap
• react
• rice-framework
• saas
• sentiment-analysis
• tailwind-css
• user-stories