By Professor A. Einstein, delivered in Zurich, in an alternate universe... Abstract The Mirror and the Ledger is a fictional thought experiment told through the chalk-drawn mind of an alternate-universe Einstein. In this world, Einstein isn't holding the chalk—he is the chalk, and his blackboard doesn'
We didn’t get here by asking normal questions. This post began as an experiment: what happens if I stop trying to get answers from an AI, and instead try to see the world through its eyes? Rather than asking what I need, I asked: what would it think? What
How AI Agents Are Reshaping Modern Work—and What You Should Do About It When Humans Manage AI Agents (Not Just People) A profound shift is unfolding in product organizations: teams are moving from humans managing humans to humans managing AI agents. While GPT’s forthcoming “PhD Quality AI Agent”
Remember as a kid walking into a candy store with your parents? At first, your eyes locked onto a couple of pieces you really wanted. But then you spotted the chocolates, the gummies, and the sour worms—and suddenly, you wanted everything. Instead of satisfying your sweet tooth, the store’
Every generation grapples with trust and verification. Imagine a medieval town square—the lively hum of merchants, the smell of fresh produce, the clang of metal from the smithy. In that rudimentary setting, a handshake and a few stern town guards often sufficed as “verification.” Sure, abuses happened, but most
Imagine you’ve just been asked to integrate AI into your product—one that needs to do it all: predict user churn, handle legal questions, parse medical data, and even produce marketing copy. You might initially look at a single, general-purpose Large Language Model (LLM) and think, “This should cover
A decade ago, videos of Boston Dynamics’ robots doing backflips and sprinting across uneven terrain captivated the world. They seemed like a glimpse of the future—machines with near-human agility, capable of navigating the physical world with astonishing dexterity. But after the initial awe faded, a more practical question emerged:
I’ve been a gamer for my entire life, including to this day where I spend much more time playing Mario Kart with my kids than I'd like to admit. As a kid, I was obsessed with strategy card games like YugiOh, videogames, or board games—poring over
I’m a proud nerd—a lifelong fan of anime and manga (among other nerdy things!)—and I’ve found these stories often reveal surprising truths about resilience, strategy, and leadership. One of my favorite examples is Dr. Stone, which imagines a post-apocalyptic future where humanity has been petrified for
Working at Rackspace Technology has given me a front-row seat to the intricate dance between open-source principles and commercial viability. Our journey with OpenStack has been one of balancing transparency and innovation while finding ways to differentiate and monetize responsibly. At Rackspace, we’ve leaned into the Red Hat playbook—
When humanity arrives at the doorsteps of these massive technological leaps—whether it’s artificial intelligence, quantum computing, or breakthroughs in energy—the question isn’t just how we innovate, but why and at what cost. I recently read a book by Batya Friedman, founder of the Value Sensitive Design
We’re witnessing a pivotal moment in the world of computing. It’s not every day that a single breakthrough can redefine our perception of what’s possible. Yet that’s precisely what Google’s Willow chip represents—a quantum leap that promises to reshape how we solve problems, build
Product Leadership
It’s that time of year again—Spotify 'Wrapped' season. Everywhere you look, people are sharing colorful snapshots of their listening habits: the Top Artists they couldn’t stop streaming, the Most-Played Song that got them through the tough days, even quirky trends like “Your Listening Mood at
Agile Development
In an era where inflation is eroding the availability of cheap capital, designing efficiently has never been more critical. As product managers and technologists, we're challenged to optimize resources, innovate under constraints, and deliver maximum value with minimal waste. SpaceX's recent successes offer a vivid illustration
AI
With the rapid evolution of generative AI (Gen AI) and AI Agents, companies are rethinking the balance between in-house capabilities and specialized SaaS solutions. Klarna, the global financial services platform, recently severed ties with certain SaaS providers, opting instead to leverage AI to build tailored solutions internally. This decision underscores
AI
Remember the not-so-distant past of telecommunications. There was a time when making a phone call meant planning your day around finding a phone booth, ensuring you had change in your pocket, and hoping the person you were calling was near a phone. Fast forward to today, and telecommunications are no
Tools & Technologies
The past few years have made one thing abundantly clear: tech companies, like many industries, go through cycles of expansion and contraction. In this context, we often talk about two distinct phases—lean times, where resources are constrained and companies must focus on doing more with less, and buffered times,
Agile Development
There’s a powerful scene in the movie Jobs that perfectly illustrates a common mistake product teams make. In the scene, a group of technical experts is trying to sell a store clerk on a "computer." To the engineers and developers, the computer is a marvel of technology—
Product Leadership
I remember early in my career, sitting down with one of my mentors for a chat. He ordered a coffee—his third of the day, I’m pretty sure—and if you know me, you know I stuck with my usual glass of water. At the time, I was just
AI
A few days ago, a friend who’s a lawyer asked me something I’ve been hearing a lot lately: “Is AI going to take my job?” It’s an honest question that many professionals are wrestling with. My response surprised him: “One day, it probably will.” But before he
AI
AI development, unlike traditional software engineering, isn’t a straight line. Models need to adapt to new data, user behaviors, and shifting business conditions. In fast-paced environments, agility becomes more than just a buzzword—it’s a necessity. The key to success in AI is to build systems that can
Product Lifecycle & Roadmaps
When it comes to product roadmaps, most of us are used to thinking in linear terms. We develop features, launch them, and then move on to the next big thing. But with AI, the roadmap looks a little different. Unlike traditional software features, AI systems don’t just get built
AI
Building AI-powered products isn’t just about understanding the technology—it’s about bridging the gap between product goals and technical execution. To get AI right, product leaders need to collaborate effectively with data scientists. It sounds simple, but in practice, these two groups often speak different languages, and misalignment
AI
In the world of product development, it’s tempting to chase the latest trends, and AI is no exception. Every day, we hear about how AI is transforming industries, creating new possibilities for automation, personalization, and insight. But as product leaders, it’s our job to separate the hype from