Cursor for Product Managers

Key Takeaways

Over the last few years, we've seen an explosion of AI tools for writing code. Cursor and Cloud Code are great at helping teams build software once [music] it's clear what needs to be built. But writing code is only part of building a product people want. The most important part is figuring out what to build in the first place. [music] Every successful product requires product management, talking to users, understanding markets, synthesizing feedback, and deciding what problems are worth solving and how the product should work. Whether this process is done by founders, engineers or product [music] managers, the activity is the same. Historically, the output has been product requirements docs, Figma mocks and Jira tickets, artifacts designed to communicate intent to human engineers. Today, teams use AI in isolated parts of this [music] process, but there's no system that supports the full loop of product discovery. Imagine a tool where you upload customer interviews and product usage data, ask, "What should we build next?" and get the outline of a new feature, complete with an explanation based on customer feedback as to why this is a change worth making. The tool would also propose specific changes to your [music] product's UI, data model, and workflows and would break down the development tasks so that they could be handled by your favorite coding agent. We think there's an opportunity to build a cursor for product management, an AI native system focused on helping teams figure out what to build, not just how to build it. As agents increasingly take the first pass at implementation, the way we define and communicate what to build needs to change. If you're building in this space, we'd love to hear from