Prism - From Chats to Structured Product Work

Modern product teams constantly discuss bugs, features, ideas, and feedback inside chat platforms like WhatsApp, Slack, Discord, and internal threads. However, these high-value product signals get buried in noise, making manual triage slow, repetitive, and error-prone. Prism is a production-minded AI Product Signal Agent built on Complete.dev that continuously ingests messy team conversations and transforms them into structured, actionable outputs. Instead of simple summarization, Prism uses a product knowledge base and contextual understanding of the codebase to intelligently classify messages into Issues, Features, Ideas, and Marketing signals while filtering irrelevant chatter. The system orchestrates multiple AI agents in sequence: a classifier agent detects relevance and priority, an interpreter agent structures requirements and acceptance criteria, and a planning agent generates execution-ready artifacts like implementation plans, testing checklists, and documentation. A human-in-the-loop checkpoint ensures quality and control before final outputs. During the hackathon, we built a fully working pipeline that supports multi-format chat ingestion (Discord exports, text, and structured logs), real-time signal classification, a workspace board for structured triage, and an issue builder that converts raw conversations into downloadable technical plans. Prism’s core innovation is context-aware signal intelligence — it doesn’t just read messages, it understands them in relation to the product itself. The long-term vision is to integrate live WhatsApp, Slack, and Discord bots that act as always-on product observers, ensuring no critical signal is ever lost in chat history again.