Mira: The Cursor for Product Management

Inspiration

We’ve seen AI revolutionize how we build with tools like Cursor and Claude Code, but the "last mile" of software remains the hardest: figuring out what to build. We wanted to move beyond static PRDs and Jira tickets to create an AI-native engine for product discovery that bridges the gap between customer pain and shipping code.

What it does

Mira is an AI-native system designed for the full loop of product discovery. You upload customer interviews and usage data, and Mira synthesizes them into a roadmap. It doesn't just suggest ideas; it proposes specific UI and workflows, then breaks them into structured tasks ready for your favorite coding agent to execute.

How we built it

We built Mira using a multi-agent orchestration layer. We leveraged LLMs to parse unstructured transcript data, mapped those insights to a vector database for RAG-based evidence, and used a structured output engine to generate technical specs that integrate directly with modern IDEs and task managers.

Challenges we ran into

The biggest hurdle was "signal vs. noise." Customer interviews are messy and often contradictory. We had to develop a weighted synthesis algorithm to ensure Mira prioritizes high-impact problems over "vocal minority" feature requests while maintaining a coherent, vision-driven product direction.

Accomplishments that we're proud of

We successfully closed the loop between raw feedback and executable code. Our "aha" moment was seeing Mira take a rambling 30-minute Zoom transcript and autonomously generate a perfectly formatted set of sub-tasks that a coding agent could immediately start implementing.

What we learned

We learned that as AI takes over implementation (the how), the value of a team shifts almost entirely to definition (the what). The language of product management is shifting from human-readable documents to machine-understandable intent.

What's next for Mira

We’re looking to integrate Mira directly into live feedback loops—imagine a system that updates your product backlog in real-time as users interact with your app. Our goal is to make the distance between a customer’s problem and a deployed solution as short as possible.