Is it worth learning to code?

Key Concepts

• Product Management in the Age of AI: The evolving role of product managers with the advent of AI tools.
• Judgment vs. Output: The increasing importance of critical thinking and discernment over sheer speed or volume of work.
• Skillset Optimization: Prioritizing the development of “good judgment” over technical skills like coding.
• Taste & Quality: The value of aesthetic sensibility and high standards in AI-driven product development.
• Building as Learning: The necessity of practical application to refine judgment.

The Shifting Landscape of Product Management

The speaker argues that current AI tools are effectively “supercharging” the capabilities of product managers, enabling them to create documentation like Product Requirements Documents (PRDs) with unprecedented ease. However, this increased efficiency doesn’t translate to increased value for the product manager themselves. Compensation isn’t tied to the quantity or quality of PRDs produced, but rather to the quality of judgment exercised in directing product development. The core point is that AI handles the “doing” – the execution of tasks – while the product manager must focus on the “thinking” – deciding what to do.

The Devaluation of Raw Output & the Rise of Judgment

The speaker explicitly discourages individuals from learning to code, particularly if they haven’t already. This isn’t a dismissal of coding as a skill, but a statement about prioritization. In a world where AI can generate code and other outputs rapidly, the ability to produce raw output is becoming less valuable. Instead, the speaker emphasizes that future rewards will be given to those who demonstrate “better judgment.” This judgment encompasses understanding what will be genuinely useful and tasteful for users. The speaker frames this as a fundamental shift in the skills needed to succeed.

Prioritizing Clarity, Quality, and Taste

The speaker states they are dedicating 100% of their time to cultivating “good judgment, clarity, quality, and taste.” These qualities are presented as the differentiating factors in an AI-driven environment. “Taste” is particularly noteworthy; it implies an aesthetic sensibility and an understanding of user experience beyond mere functionality. This suggests a move towards products that are not just capable, but also delightful and well-designed.

The Importance of Practical Application – “Building”

While advocating for a focus on judgment, the speaker doesn’t suggest abandoning practical work. They explicitly state, “That doesn’t mean you shouldn’t build.” Instead, building – creating and iterating on products – is presented as the method for improving judgment. Experience gained through practical application is crucial for developing the nuanced understanding necessary to make sound decisions. The act of building provides the feedback loop needed to refine one’s sense of what works and what doesn’t.

Notable Quote

“We won’t be rewarded in the word of AI for faster raw output. We will be rewarded for better judgment.” – The speaker, highlighting the core argument of the discussion.

Synthesis

The central takeaway is a call to re-evaluate skill development priorities in the age of AI. The speaker argues that the ability to generate output is becoming commoditized, while the ability to exercise sound judgment, prioritize quality, and understand user needs is becoming increasingly valuable. Product managers, and potentially anyone involved in creative or strategic work, should focus on honing these “soft” skills through practical experience and deliberate practice, rather than solely pursuing technical proficiency.