Ai Product Management

In a previous article, we covered key theoretical concepts that underpin — which involves probabilistic weighting of uncertain outcomes — and focused on the relevance to AI product management. , we are going...

, having spent my profession working across a big selection of industries, from small startups to global corporations, from AI-first tech corporations to heavily regulated banks. Over time, I’ve seen many AI and ML...

under uncertainty is a central concern for product teams. Decisions large and small often must be made under time pressure, despite incomplete — and potentially inaccurate — information concerning the problem and solution...

, clients and stakeholders don’t want surprises. What they expect is clarity, consistent communication, and transparency. They need results, but additionally they want you to remain grounded and aligned with the project’s goals as a...

that the majority AI pilot projects fail — not due to technical shortcomings, but attributable to challenges in aligning recent technology with existing organizational structures. While implementing AI models could seem straightforward, the true obstacles...

how our job will evolve and even exist than now with the emergence of AI Agents. But let me be upfront that AI tools don’t change the elemental job of the PM, which...

constructing with AI, complexity adds up — there’s more uncertainty, more unknowns, and more moving parts across teams, tools, and expectations. That’s why having a solid discovery process is much more vital than when you're...

of Contents Introduction The AI space is an enormous and sophisticated landscape. Matt Turck famously does his Machine Learning, AI, and Data (MAD) landscape yearly, and it all the time seems to get crazier and crazier....