The text discusses a feature in New Relic's Applied Intelligence product called "suggested responders" that helps resolve production issues faster by identifying the most relevant team members to help resolve incidents in real-time. This feature uses machine learning (ML) to analyze past interactions and predict the most likely responders for new violations. The suggested responders model consists of three phases: supervised pattern recognition, label spreading, and a recommender engine. It provides a list of users who are most likely to resolve a certain violation, along with their likelihood scores. This feature can be used to route incident notifications to specific channels based on predicted suggested responders, ensuring that the right people are notified for the right incidents. The text also highlights how to get started with suggested responders and its benefits in increasing response efficiency and resolving production issues faster.