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How to Measure AI Product Quality and Prove Real ROI
A practical framework for linking AI evaluations to successful tasks, retained usage, business outcomes, and the full cost of delivering value.
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How to Govern AI Product Experiments Without Slowing Teams Down
A practical operating model for testing AI in stages, setting evidence gates, and turning legal, privacy, and safety concerns into product controls.
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AI Agents for Product Experimentation: A Practical System
A practical operating model for turning product signals into instrumented experiments with AI agents while preserving accountable product judgment.
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How Interactive Frontier Models Change AI Product Strategy
A practical framework for choosing, designing, evaluating, and safely shipping AI responses that become charts, forms, calculators, and actions.
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How to Build an AI-Assisted Holiday E-Commerce Creative System
A practical plan for turning product images into governed, testable holiday creative with AI while preserving brand and product accuracy.
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How to Build Proactive AI Customer Support That Earns Trust
A practical framework for selecting support triggers, setting AI autonomy, protecting trust, and measuring verified customer recovery rather than clicks.
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Amplitude SDK vs. Warehouse Ingestion: A Decision Guide
Use this framework to choose Amplitude’s SDK, warehouse ingestion, or a hybrid based on behavioral depth, data authority, and governance.
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How Product Leaders Should Govern Emerging AI Capabilities
A practical framework for governing retrieval poisoning, synthetic user forecasts, agent permissions, and the evidence needed before launch.
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Conversational AI Latency and the Mechanics of Turn-Taking
A practical framework to measure voice AI latency, tune endpoint detection and barge-in, and decide when the experience is ready to launch.
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How to Build Product Verification Loops for AI Software Factories
A practical operating model for linking factory tests and AI evals to post-ship evidence, product decisions, and compounding learning.
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Designing AI Products That Learn Without Losing User Trust
A practical framework for placing AI in the workflow, capturing meaningful feedback, governing adaptation, and turning usage into safer product learning.
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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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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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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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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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Behavioral Analytics for AI Agent Activation and Retention
A practical framework for measuring an AI agent’s first useful outcome, repeat value, and behavior-triggered interventions without mistaking activity for trust.
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How I Make AI Agents Speak Like Our Team: A Conversation Design Playbook That Lifts CSAT
Your AI Agent will sound like an LLM unless you intentionally design how it communicates. I share a practical conversation design playbook covering tone, response structure,…
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AI Inference Economics: Optimize for Value, Not Cost
A practical framework for balancing AI inference cost, latency, and quality against conversion, retention, support demand, and revenue.
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A Practical Model for Amplitude Behavioral Web Intelligence
A decision model for combining Amplitude analytics, zoning, heatmaps, replay, performance signals, and experiments without overstating the evidence.
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How Agentic Analytics Reshapes Product Development Roadmaps
A practical synthesis of how product agents connect behavioral analytics, controlled experiments, roadmap decisions, and accountable automation.
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