Product Management

I heard Satya Nadella describe this week on the All-In podcast how LinkedIn has been collapsing product management, UX, and engineering roles into a single “full-stack builder” role. The framing was optimistic: AI reduces construction costs and speeds up delivery. At a surface level, this makes sense. AI dramatically accelerates prototyping, implementation, and iteration. In many environments, the traditional separation between PM, design, and engineering really does introduce friction that slows learning and execution. ...

A Small Number, a Real Moment CV Match has been out in the world for a few months now. I almost didn’t notice when it crossed 100 installations. That number, by itself, is not impressive. It is small. Almost trivial. What made me stop was not the number, but the realization that this thing actually existed in the hands of people I did not know. Real users, not personas. Real decisions, not demos. ...

The Full Stack PM I have always believed in the idea of the full stack product manager. Not because one person should do everyone’s job, but because product work does not respect org charts. Products fail and succeed in the gaps between roles, and when those gaps exist, someone has to step in and own them. Many organizations like clear distinctions: technical PMs, product owners, delivery PMs, growth PMs. On paper, it looks clean. In practice, it often creates waste. Handoffs. Waiting. Endless alignment meetings. Everyone does their part, but nobody owns the outcome. ...

Early in my career, coming from industrial engineering, I learned a simple rule that has shaped the way I think about software development ever since. Software may look abstract, creative, fluid. But underneath, it behaves like a production system. The best articulation of this idea appears in The Goal by Eliyahu M. Goldratt, one of the most influential books I have ever read. In production, every system revolves around three outputs you can influence: ...

The Answer Is Still Cookies A few days ago, I saw a Cookie Monster quote that made me stop: “Me don’t know da question, but me know da answer is cookies.” It is funny. It is childish. And it is exactly how companies behave when they insist their problems are special. Every company believes it is fundamentally different. Different industry. Different technology. Different customers. Different speed. Therefore, their problems must be new, unprecedented, uniquely complex. ...

From CLS to Agentic AI I was born in 1977, right at the intersection of two worlds. Old enough to remember analog. Young enough to grow with digital. My first program was written on a Dragon 32, a home computer with 32 kilobytes of RAM and a keyboard that felt like it came from a typewriter factory. My oldest brother brought it home one afternoon, and it was the first computer I ever saw in real life. ...

A Fool with a Tool Long ago, I met a senior executive from NBC who liked to say: “A fool with a tool is still a fool.” It was true then, when the “tools” were spreadsheets, automation scripts, or a shiny new CRM. It’s even truer today, when the tools in question are large language models and autonomous agents. Over the past year, AI has moved from novelty to necessity. The experiments are over; the adoption curve has turned vertical. ...

From Hand-Waving to Hands-On Leadership Some leaders speak with absolute confidence but offer very little clarity. They communicate in slogans, headlines, and big statements, not because the work is strategic, but because this is their default mode. It doesn’t matter whether the topic is AI strategy, a roadmap shift, a bug fix, or a simple user flow. The pattern is the same: big words, big confidence, and no details. And the moment you ask how, the answers dissolve into vague gestures and confident phrases that sound important but say nothing. ...

Why the Best Leaders Keep Asking Why Early in my career, I learned about the Five Whys, a simple yet powerful problem-solving method developed by Sakichi Toyoda at Toyota in the 1930s. The idea is straightforward: when you face a problem, ask why it happened. Then ask why again about that answer, and continue until you reach the root cause, usually after about five rounds. It sounds simple, yet most people don’t do it consistently. ...

Metadata Then & Now: A Decade of Machine Understanding Ten years ago, I wrote a blog post for Dalet about metadata and online video advertising. In 2015, digital video was accelerating fast, budgets were moving from TV to online, ad-blocking was spiking, and programmatic was scaling, so we focused on the unglamorous layer that made it all work: metadata. Back then, my main argument was that metadata shouldn’t be entirely human or entirely automatic. Machines could process at scale, but humans understood nuance. That idea sounds self-evident now, but in 2015 it bordered on heresy. ...