As the cost of writing code continues to decrease, the scarcity of individuals who decide what to build is on the rise, posits AI luminary Andrew Ng. With AI driving down the cost of coding, the demand for idea generators is intensifying. This perspective has sparked a lively debate, with some arguing that cheaper development costs lower the barrier to experimentation, while others worry about the impact on product quality.
In the realm of product development, the ratio of engineers to product managers may shift due to AI. While AI tools are lowering entry barriers, they are not simplifying the role of product managers, who now need a deeper understanding of the underlying technology.
Future AI product managers will need to possess a suite of skills, including a grasp of AI’s foundational logic, the ability to iterate quickly and learn from failures, the capacity to interpret data, the skill to find direction amidst uncertainty, and the speed to keep pace with AI’s advancements. The challenge lies in finding talent that is both technically proficient and adept at management.
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Build Faster, Think Deeper
Engineers are now more focused on what to build rather than just how to build it. As technical barriers lower, the demand for product insight increases. Andrew Ng asserts, “This is an unparalleled era of creation!” Below are the core takeaways for the future AI product manager:
– Comprehend the underlying logic of AI technology.
– Iterate quickly and learn from mistakes.
– Interpret data effectively.
– Navigate through ambiguity to find direction.
– Keep learning at a pace that matches the speed of AI advancements.
The evolving landscape of AI does not simplify the role of a product manager; it deepens it. As we dive into this transformative era, the call to action is clear: Build faster, think deeper.
