What is an AI feedback pipeline?

An AI feedback pipeline is infrastructure that transforms unstructured user feedback (screenshots, bug reports, feature requests) into structured, machine-readable data that AI agents can parse and act on. FeedbackFlow captures user feedback with full context (DOM state, console logs, network errors) and uses AI to structure it into actionable tickets.

How does FeedbackFlow work with AI development workflows?

FeedbackFlow sits between users and AI agents in your development pipeline. When a user reports a bug or requests a feature, FeedbackFlow captures the full context, uses AI to ask clarifying questions, then outputs structured JSON that AI agents can consume. This eliminates manual translation of user feedback into tickets.

What is product feedback automation?

Product feedback automation is the process of automatically collecting, structuring, and routing user feedback without manual intervention. FeedbackFlow automates the entire flow from user screenshot to actionable ticket, including context capture, AI triage, and integration with tools like Linear and Notion.

Can AI agents read FeedbackFlow output?

Yes. FeedbackFlow outputs structured JSON with all feedback context, making it machine-readable for AI agents. The output includes the user report, screenshots, DOM state, console logs, network errors, and AI-generated reproduction steps—everything an AI agent needs to understand and fix the issue.

What is AI-assisted development infrastructure?

AI-assisted development infrastructure refers to tools and systems that enable AI agents to participate in the software development lifecycle. This includes feedback pipelines (like FeedbackFlow), code generation tools, automated testing systems, and deployment automation—all designed to be consumed and acted upon by AI agents, not just humans.

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