Shubham Saboo outlines how the role of a Product Manager (PM) is evolving in the age of AI agents. Traditionally, PMs acted as intermediaries, translating customer needs into detailed specifications for engineering teams. This process has changed dramatically. With AI agents capable of generating code from well-defined problem statements, the PM's focus has shifted from translation to clarity of intent. Now, a concise problem statement can lead to working code in under an hour, compressing what used to be a lengthy cycle into rapid iterations. Saboo emphasizes that the real challenge now lies in understanding what to build rather than how to build it. Effective PMs must master problem shaping and context curation. They need to clearly define the user, articulate the problem in their words, and specify what success looks like. This involves maintaining context documents that guide AI agents to produce relevant solutions. The PM's role has become more about setting the groundwork for agents to work effectively rather than merely drafting specifications. Moreover, Saboo highlights the importance of evaluation and taste in product development. As AI tools generate outputs quickly, discerning quality becomes essential. PMs must assess whether the solutions truly address user needs and handle edge cases. He advises PMs new to this approach to start small, focusing on real problems and iterating through ten different projects to build their intuition for effective collaboration with AI agents. As the translation layer fades, the core skills of understanding user needs and making informed judgments are more valuable than ever.