July 2026
- AI Strategy (315)
- Generative AI (106)
- IT Leadership (33)
- Leadership (76)
- Product Management (344)
- Product Management Leadership (306)
- Uncategorized (32)
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AI Productivity Is Not a Product Outcome: Measure What Matters
A practical operating model for linking AI-enabled speed to customer behavior, business impact, quality guardrails, and deliberate capacity choices.
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AI-Assisted Behavioral Analytics: A Product Leader’s Playbook
A practical operating model for using AI to investigate user behavior, validate product insights, build cohorts, and turn launch data into safer decisions.
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From Amplitude Adoption to Customer Value: A Leadership Model
Build a customer value model that connects Amplitude behavior data to business outcomes, credible claims, and clear leadership decisions.
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Competing on Experience: A Retail Banking Product Strategy
A practical framework for choosing the banking journeys, measures, and operating habits that turn customer experience into durable advantage.
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Operating Lessons from Plaid’s COO for Scaling Through Change
Plaid COO Eric Sager’s operating approach shows how capacity, customer ownership, decision trade-offs, delegation, and onboarding can support resilient growth.
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A Practical Framework for Choosing Product Management Tools
A workflow-first framework helps product teams select, govern, and reassess tools without mistaking a long feature list for a coherent operating system.
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A Practical Framework for Measuring New Feature Success
A practical framework for deciding whether a new feature earns adoption, improves the user experience, and contributes to a meaningful product or business outcome.
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Feature Management as a Product Development Discipline
A practical guide to controlled feature releases, evidence-based rollout decisions, cross-functional ownership, and the governance needed to manage complexity.
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How Cohort Retention Analysis Turns Churn Into Action
Learn how to define useful customer cohorts, interpret retention differences carefully, and convert churn signals into focused product decisions.
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How to Choose a North Star Metric That Guides Product Teams
A practical framework for selecting a North Star Metric that reflects customer value, supports product decisions, and avoids misleading activity measures.
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From Customer Signals to Reliable Product Operations
A practical framework for routing support, behavioral, research, and reliability signals into faster response and stronger product decisions.
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How Snapbar Turned Crisis Into an AI-Native Photo Experience Revolution
Snapbar’s reinvention shows how a mature company can turn crisis into a durable AI product strategy. The company moved from physical photo booths to a WebRTC-based…
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The Hidden Leadership Skills Product Managers Need Before the Title Change
Product managers do not need to wait for a formal title change to start building real leadership capability. The strongest path begins with understanding how leadership…
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Supercharge Product Discovery: A Practical July Guide to Better Team Ideation
Chapter 8: Supercharged Ideation offers a practical way for product teams to move beyond traditional brainstorming and generate stronger solution options. The core lesson is that…
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From Static Scores to Adaptive Customer Health Intelligence
A practical framework for turning customer health from a lagging score into an adaptive system connecting behavior, context, and timely action.
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Durable Product and Platform Leadership Beyond the Launch
A practical framework for turning product momentum into lasting platform value through governance, customer trust, disciplined growth, and AI readiness.
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How to Operate AI Customer Agents as a Reliable CX System
A practical operating model links agent capabilities, release readiness, evaluation, measurement, and ownership into one continuous CX improvement loop.
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AI Product Leadership: Faster Learning, Safer Systems
A practical framework for improving product discovery and delivery while matching AI evaluation, privacy, and governance to real-world risk.
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Connecting Product Analytics, Attribution, and Growth Decisions
A practical framework for linking journey context, governed product data, AI-assisted analysis, and measurable action without overstating attribution.
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Reliable AI Coding Requires Four Kinds of Control
A practical framework for controlling requirements, context, verification, permissions, and recovery when teams build software with AI agents.
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Browse topics
- AI Strategy (315)
- Generative AI (106)
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