In the rush to add new features and capabilities, product teams often overlook a fundamental truth: how you build and deliver is as important as what you build and deliver.

As I logged into my favorite MMORPG last weekend, something struck me: while I haven’t touched Microsoft Word’s release notes in years (or ever), I was eagerly devouring every detail of this game’s latest update.

McKinsey’s recent article “The missing data link: Five practical lessons to scale your data products” has hit on something I’ve been advocating for years: treating data as a product rather than a project or resource. While I’m typically wary of consultancy research (aren’t we all?), this piece validates much of what we’ve observed in the field about the transformative power of data product thinking.

Technical complexity is the enemy of shared understanding. When presenting complex product concepts, data analyses, or system architectures, the gap between your expertise and your audience’s comprehension can quickly become a chasm.

We’ve all seen it—-companies rushing to slap “AI-powered” on their marketing materials while implementing little more than basic automation or, worse, glorified if/then statements. The current marketplace is brimming with products that tout AI capabilities but deliver minimal value beyond the initial novelty.

A decade ago, I challenged development teams to create “joy in 15 seconds.” Back then, it was revolutionary to expect enterprise software to deliver immediate satisfaction. Today, it’s table stakes. The modern user—conditioned by TikTok’s instant dopamine hits and Amazon’s one-click purchases—demands even faster gratification from every digital experience, including workplace tools.

In a world where both technical expertise and human development are critical for success, the most effective product leaders recognize that mentorship amplifies rather than replaces their technical capabilities.

Work Smarter, Not Harder

In technology and business, project and product management are two significant but often confused roles. Although the term “PM” can refer to either function, the goals behind both reflect drastically distinct ways to generate value - with significant effects on the performance of your company.

The era of “move fast and break things” is giving way to a more thoughtful approach to technology development—particularly when it comes to artificial intelligence. As AI systems become integrated into the critical aspects of our lives, the ethical implications of these technologies can no longer be treated as an afterthought or relegated to a long-forgotten compliance checklist.