Articles
Preparing the article archive.
When the Idea Answers Back
Jul 30, 2026
Language compresses a product idea. AI gives high-agency product people more power to build enough of it to explore, learn from its behavior, and discover what the original words left out.
The A/B Test That Lies
Jul 28, 2026
A/B tests can establish causal movement, but teams still need a metric hierarchy that distinguishes local engagement from durable product trust.
Your Team Needs Fewer Dashboards and More Dials
Jul 23, 2026
Metrics become management only when teams connect signals to authorized controls, decision rights, guardrails, and a memory of what happened next.
Your AI Coworker Should Know Which Doors It Can Open
Jul 21, 2026
A product manager should understand the business consequence of an action. They should not have to become a systems administrator before asking an AI tool to help with their work.
AI Agents Need Breakpoints
Jul 18, 2026
Codex can order queued turns, but it cannot yet express a durable approval gate between them or constrain the current turn to the phase the user intended.
What Should an AI Be Allowed to Know?
Jul 18, 2026
An AI AMA earns trust by separating general expertise from personal claims, screening every runtime surface, and treating privacy failures as release blockers.
The Art of Making Algorithms Understandable
Jul 14, 2026
AI product managers need faithful explanatory artifacts that turn complex recommendation systems into reviewable behavior, not just static requirements.
One Task, Multiple Agents, One Continuous Loop
Jul 13, 2026
Trustworthy multi-agent systems emerge from evidence contracts, interruption rights, recovery paths, and human feedback—not from parallelism alone.
I Knew What AI Could Do. I Forgot to Think That Way.
Jul 12, 2026
AI-forward thinking begins by questioning inherited architecture: let models interpret raw evidence, deterministic systems constrain and test it, and humans own the decision boundary.
The Best AI Will Not Ask You to Choose a Model
Jul 10, 2026
AI products will earn broader adoption when they translate user intent into the right capability, instead of making people configure the machinery.
Don’t Inherit the Tool. Inherit the System.
Jul 8, 2026
AI-assisted work becomes portable when teams preserve runnable systems, clear decisions, tests, and documentation beyond any one tool.
The Discovery Brain: Where LLMs Can Strengthen Streaming Recommendations
Jul 7, 2026
LLM-native discovery can unify streaming recommendations when grounded catalog truth, governed memory, validation, and feedback protect user trust.
The Camera Is Becoming Software
Jul 6, 2026
Software is turning cameras into adaptive capture systems, pushing dedicated gear toward high-intent work while phones own everyday memory.
Fit for Purpose: Choosing the Right Quality Bar
Jul 3, 2026
Teams move faster when precision serves the user experience, not internal certainty, and good enough means fit for purpose.
Modernizing Discovery and Promotion in Personalized Products
Jul 1, 2026
Modern discovery systems balance personal relevance, popularity, momentum, and strategic intent without letting promotion overwhelm user value.