Posts where AI plays a role in enhancing product management tasks like documentation, feature prioritization, and sprint planning.
AI
The Hidden Consequence of a Post-Work World We talk a lot these days about a world without white-collar workers. AI is writing code, reviewing contracts, generating marketing copy, even giving financial advice. There is even talk of embodied AI encroaching on the realm of manual labor at some point in
AI
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'
AI
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
AI
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”
AI
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’
AI
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
AI
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
Innovation & Ideation
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:
AI
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
AI
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
Product Leadership
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
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