Arnica, an early-stage company, aims to build Minimum Lovable Products (MLPs) by deeply understanding their users. They conducted experimentation on HackerNews to determine what content and topics resonated most with their audience. The research involved querying a portion of the platform's records into a Graph database, which was then analyzed for user and post popularity trends. Key findings include optimal days and times for posting stories, the impact of user karma on story scores, and the role of links in increasing story popularity. Overall, good content is crucial to gaining traction on HackerNews, but understanding user preferences can help improve engagement and visibility.