Recently, I found myself immersed in Morgan Housel’s brilliant Same as Ever, and it sparked an intriguing reflection on product management in our AI-driven world. Artificial intelligence is starting to reshape how we work. However, some fundamentals of product management remain steadfast, much like the human behaviors Housel describes in his book.
This truth became strikingly clear during the development of our Driving Product Growth training course. Despite AI’s sophisticated market analysis and data processing capabilities, our most valuable insights came from two distinctly human sources: candid customer conversations revealing frustrations and unmet needs, and dynamic idea exchanges between product managers and their cross-functional colleagues.
The Power of Human Connection
During our training pilot sessions, we witnessed something that AI could never replicate—the spark of understanding when product managers, marketers, sales and customer success teams came together to tackle shared challenges. These weren’t just structured discussions; they were organic conversations that often veered into unexpected territory, unveiling insights that no algorithm could have predicted.
In one session, a seasoned team grappled with defining their North Star metric. What initially seemed straightforward—selecting a single measure of success—evolved into a deeper examination of their product’s fundamentals. The team worked through exercises that revealed how their customers’ problems, product value proposition, and adoption drivers were more nuanced than expected.
The breakthrough came through cross-team dialogue. Marketing illuminated how customers perceived and valued different product elements, while Customer Success brought forward specific adoption barriers they’d encountered in the field. The team’s combined perspectives and experiences led them to a North Star that truly reflected their product’s impact—an insight that emerged not from data alone, but from collaborative human understanding and shared customer empathy.
Learning Through Iteration
Our course development process itself exemplified another timeless principle of product management—the power of iteration based on human feedback. We continuously refined our training materials and exercises, responding to participants’ reactions, engagement levels, and learning patterns. This wasn’t just about adjusting content; it was about reading body language, sensing confusion or excitement, and adapting in real-time—nuances that AI systems, however sophisticated, cannot fully grasp.
The Enduring Elements
Through this experience, several timeless aspects of product management became evident:
- Deep Customer Understanding: While AI can analyze patterns and trends, the ability to truly empathize with customer pain points comes from human connection and conversation.
- Cross-functional Collaboration: The magic of spontaneous ideation and problem-solving that happens when diverse teams come together cannot be replicated by algorithms.
- Adaptive Learning: The capacity to read subtle cues, adjust approaches on the fly, and create meaningful learning experiences requires human intuition and emotional intelligence.
These elements remind us that while AI will undoubtedly enhance our capabilities in product management, it won’t replace the fundamental human skills that make product managers effective. As Housel might say, the tools and technologies will continue to evolve, but our need to understand, connect with, and solve problems for other humans remains constant.
Looking Forward
As we navigate the AI revolution in product management, perhaps our focus shouldn’t be on what’s changing, but on what endures. The most successful product managers of the future will be those who embrace AI’s capabilities while continuing to develop their uniquely human skills—empathy, judgment, and the ability to build genuine connections with customers and colleagues.
Our training course experience stands as a testament to this truth: in product management, some of the most valuable insights and growth opportunities come not from algorithms or data analysis, but from human interaction, observation, and iteration. As we move forward, let’s remember that while AI may change how we work, it won’t change why we work—to create products that meaningfully improve people’s lives.
Eddie Pratt, Managing Director – Product Focus
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