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Amplitude Browser SDK: Turn Web Vitals Into Product Decisions
A practical model for sending Web Vitals through Amplitude, protecting page performance, and tying LCP, INP, and CLS to product growth.
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Trustworthy AI Product Engineering: From Demo to Daily Use
A practical operating system for making AI outputs traceable, uncertainty actionable, failures bounded, and quality measurable in customer workflows.
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Beyond Accuracy: The Trust-First Evaluation Metrics I Use to Scale High-Impact AI Products
Trust—not accuracy—determines whether AI features earn adoption, retention, and long-term impact. In this piece, I share the layered metrics I use to evaluate model quality and…
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AI-Ready Data Governance: A Practical Trust Framework
A practical operating model to trace AI inputs, enforce access, automate quality controls, and prove trust without slowing delivery.
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How to Build Self-Service Analytics Teams Actually Trust
A practical operating model for giving product teams faster answers without sacrificing metric consistency, data quality, privacy, or analyst leverage.
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Dormant User Win-Back Strategy: A Practical Playbook
A practical framework for segmenting dormant users, rebuilding their path to value, orchestrating outreach, and measuring durable reactivation.
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Mastering Data Governance in the AI Era: Move Fast, Reduce Risk, and Unlock Trusted Insights
AI is changing the rules of data governance, and the winners will combine speed with trust. In this piece, I share a practical blueprint for building…
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High-Quality Data, High-Velocity AI: My Product Playbook for Governance, Trust, and Scale
High-quality data is the fastest path to real AI impact. I outline how data contracts, privacy-by-design, and a unified analytics platform create the foundation for trustworthy,…
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A Quality System for Trustworthy AI-Assisted UX Research
Learn how to use AI for UX synthesis without weakening evidence, participant coverage, privacy, or the product decisions the work supports.
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Win AI Search: Proven Playbook to Get Your Startup Recommended by ChatGPT & Perplexity
AI search is becoming the new homepage for startups, and the brands that win are the ones models can clearly identify, verify, and cite. In this…
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Prototypes vs Products: How I De-risk Ideas Fast and Ship Reliable Value at Scale
Too many teams confuse prototypes with products—and pay for it later. I use prototypes to learn fast and reduce risk, and I treat products as promises…
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AI at Home, Impact at Work: Experiments That Supercharged My Product Leadership
I reflect on a standout All Things Product conversation that reinforced how low-stakes AI experiments at home can dramatically improve how we build AI-powered products at…
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Global Product Manager Playbook: Build Borderless Products, Align Teams, Win Every Market
Building products without borders isn’t a launch plan—it’s a system. In this playbook, I share how a Global Product Manager aligns product strategy, localization, pricing, and…
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Recruitment Impersonation Scams: A Playbook for Leaders
A practical playbook to help leaders make real jobs verifiable, triage impersonation reports, and guide candidates after data or money is exposed.
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How to Build an AI-Powered SaaS Customer Lifecycle
A practical model for using AI across SaaS onboarding, support, retention, and expansion without fragmenting data, ownership, or trust.
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Enterprise AI Foundations: An Operating Model That Scales
A practical blueprint for data, governance, evaluation, and decision rights that turns scattered AI pilots into a scalable enterprise capability.
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How Product Leaders Can Prevent Recruitment Impersonation Fraud
A practical control system for verifying recruiters, limiting candidate data exposure, triaging scam reports, and protecting brand trust.
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AI Risk Governance: An Operating Model for Cyber Defense
A practical operating model for classifying AI workflows, matching autonomy to risk, instrumenting defenses, and scaling safely in 90 days.
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How to Prove AI Agent ROI Without Sacrificing Privacy
A practical framework for measuring AI agent value, total cost, and risk without turning product analytics into a privacy liability.
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AI-Personalized Activation: A Practical Path to Retention
A practical system for personalizing the path to first value, proving downstream cohort lift, and scaling AI activation without eroding user trust.
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