Staying current on fast-moving AI developments as a PM, and acting on what matters

AI moves quickly. How do you stay up to date with what is happening in the field? ```hint Show a system, not a reading list Naming sources is the easy part. Explain how you decide which developments matter for a product built on AI agents, and how something you learned changed what you did. ``` ### Clarifying Questions - Are you asking about my personal habits, or also about how I would keep a product team current? - Should I focus on developments that matter for agents that talk to customers (model quality, cost, latency, safety), or on the field as a whole? - How technical should I go: research papers and benchmarks, or product launches and market moves? ### What a Strong Answer Covers - A deliberate mix of sources (primary releases and research, practitioner writing, hands-on use, customer and market signals) and why each earns its place - A cadence and a filter that separate hype from changes that affect what an agent product can do, what it costs or what risks it carries - Testing new models or features against real tasks instead of trusting announcements or leaderboards - A concrete example of a development that changed a decision, plan or opinion - How the candidate shares what they learn with their team ### Follow-up Questions - Which recent AI development do you think matters most for companies deploying customer-service agents, and why? - Tell me about a widely hyped development you chose not to act on. How did you decide? - A new model posts better benchmark scores than the one your product uses. How would you decide whether to switch?