Cursor is an AI-powered code editor built for software engineers – not product managers. Yet over the past few months, it has become my primary AI tool for product management work. Here’s why I made the switch, and how it’s helping me get more done. A Case Study (and Some Use Cases) Here’s a recent example of how I used Cursor end-to-end to investigate and document an analytics issue: Exploring our analytics. I can chat directly with PostHog (our analytics tool) through Cursor. It writes and executes SQL queries, then presents the results to me in plain English. Identifying the root cause of issues. I noticed something unusual in our analytics data. When I asked Cursor to investigate, it autonomously created multiple diagnostic queries, pinpointed the exact date the bug began, and identified the most likely causes. Drafting markdown documentation. Cursor summarised the issue in a markdown file. Like most LLM outputs, it was verbose. I ended up deleting about half the content. But it gave me a solid starting point. Publishing to Notion. Once I refined the writeup, Cursor posted it to Notion and automatically applied the relevant tags – something most people don’t do consistently! I manually added an “AI generated content” tag-transparency about AI involvement matters to me. Creating a Linear ticket. Cursor created the ticket with a concise description, and assigned it to the correct team and owner. This end-to-end workflow took minutes to go from investigation to documentation to ticket creation. If I was doing this all myself it would have taken hours. More importantly, it all happened without me leaving Cursor. ...