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- AI Strategy (429)
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10 AI Business Models You Need Now: Proven Playbooks Turning Algorithms into Revenue
AI is no longer a feature—it’s a business model. In this guide, I break down ten proven models—API-first services, vertical copilots, agentic automation, copilot upsells, insights-as-a-service,…
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Monetizing AI with Confidence: Proven Models, Smart Pricing, and ROI You Can Defend
Turning AI features into sustainable revenue requires more than a great demo; it demands crisp packaging, pricing discipline, and visible customer outcomes. I outline practical models—add-ons,…
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A Practical AI Workflow for Product Manager Cover Letters
Use a repeatable AI workflow to turn a product role and verified career evidence into a concise, specific cover letter that still sounds like you.
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Context-Driven AI Product Engineering That Survives Production
Learn how to design context contracts, retrieval pipelines, evaluations, and ownership so an AI feature stays grounded and useful in production.
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2026 Support Capacity Playbook: Bold AI Automation, Smarter Staffing, Zero‑Surprise SLAs
AI is reshaping support capacity planning, and the old linear volume-to-headcount model no longer holds. I center plans on automation rate (AI Agent involvement rate ×…
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AI in Product Design: My Proven Playbook, Real Use Cases, and the Tools That Win Faster
AI in product design has moved from novelty to necessity, and the fastest-moving teams are weaving it through discovery, prototyping, and validation. I share a practical…
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From Concierge to AI Marketing Engine: Inside Mowie’s Document Hierarchy Playbook
SMBs don’t need a bigger team to market like pros—they need smarter systems. In this first-person breakdown, I unpack how Mowie evolved from a hands-on concierge…
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Automated Insights for Product Teams: Uncover Causal ‘Aha’ Moments in Minutes, Not Weeks
Automated insights change the analytics game by surfacing causal patterns and “aha” moments in minutes, not weeks. Instead of manual, exhaustive searches, I get ranked hypotheses…
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Operationalizing AI: A Practical System for Scalable Growth
A practical operating model for choosing AI use cases, designing controlled workflows, measuring value, governing risk, and scaling what works.
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How to Build a Self-Improving AI Support Operation
A practical operating model for turning AI support failures into owned, tested changes that improve resolution without weakening quality or trust.
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How to Run AI-Augmented Workflow Experiments That Matter
A practical playbook for testing AI-assisted workflows with clear hypotheses, full-job metrics, guardrails, and evidence-based autonomy decisions.
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AI-Enabled Customer Support Roles: A Practical Org Design
A practical model for assigning AI quality, knowledge, conversation design, automation, and human escalation without hiring too early.
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AI-First Customer Support for Sustainable Ecommerce Growth
A practical operating model for choosing AI support workflows, controlling ecommerce actions, measuring real resolution, and scaling without losing trust.
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AI-Enabled Product Management: A Practical Operating Model
A practical operating model for using AI in discovery, planning, and execution while keeping evidence, judgment, and accountability in human hands.
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How to Operationalize AI: A Practical Adoption Playbook
A field-ready playbook for choosing AI workflows, securing their data, evaluating reliability, and expanding autonomy only when outcomes justify it.
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Enterprise AI Workforce Readiness: A Practical Operating Model
A workflow-level operating model for role-specific AI training, human accountability, safer adoption, and measurable business outcomes.
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How to Build an AI-Native Product Team Operating Model
A practical operating model for AI-native squads, platform services, decision rights, evaluation gates, metrics, and a disciplined 90-day rollout.
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- AI Strategy (429)
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