AI Strategy
- AI Strategy (430)
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- Leadership (81)
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- Product Management Leadership (374)
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Product Experimentation for AI Systems: A Practical Playbook
A practical playbook for testing prompts, retrieval, and policy changes with decision-ready metrics, safe rollouts, and reliable instrumentation.
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Apex Arrives: Vertical AI That Beats GPT-5.4 on Customer Service Speed, Accuracy, and Cost
Apex is a new vertical model for Fin that outperforms GPT-5.4 and Opus 4.5 on speed, accuracy, and cost—now powering ~100% of English chat and email…
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Inside My Product Marketing Playbook: Amplitude Analytics Tactics That Drive PLG Wins
This collection distills my most practical product marketing lessons into actionable steps you can apply right away. I show how to use Amplitude Analytics and behavioral…
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How to Scale AI Customer Experience Without Losing Quality
Build an AI CX quality system that combines risk-based monitoring, explicit scorecards, human review, and a closed product improvement loop.
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How to Ship Responsible AI Products in Regulated Healthcare
A practical delivery model that turns healthcare AI data boundaries, evaluation, staged rollout, and production monitoring into release decisions.
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Stop Flying Blind with AI Agents: Put Users at the Center with Pendo Agent Analytics
AI agents often launch fast but learn slowly because teams track deployments instead of outcomes. Enterprises are spending 93% of their AI budget building agents and…
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Bad Advice from Your AI Clone? Ethics, IP, and How Product Leaders Protect Quality
AI “clones” can sound like you while giving advice you’d never give. In this analysis, I unpack the ethics, IP risks, and product-quality pitfalls of building…
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Meet Amplitude’s Always‑On AI Analysts: Instant Answers Without Dashboards or Reports
Manual dashboards, ad hoc reports, and replay review have long slowed decision-making for product, growth, and data teams. Always-on analysis changes that dynamic by turning questions…
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How to Build Scalable, AI-Ready Product Documentation
A practical operating model for creating reliable, versioned product knowledge that serves customers, support teams, and AI assistants.
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How to Build a Continuous Improvement Loop for AI Support
A practical operating model for measuring AI support outcomes, learning from failures, testing fixes, and shipping improvements without regressions.
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A Practical Strategy for Foundational AI Platforms and Analytics
A practical framework for choosing platform capabilities, closing governance gaps, linking AI evaluation to analytics, and scaling adoption.
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Agentic AI for Clinical Trial Operations: A Practical Playbook
A practical framework for choosing, designing, validating, and governing clinical trial agents while keeping accountability and audit evidence intact.
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Agentic Architecture Demystified: How Modern AI Systems Plan, Learn, and Execute at Scale
Modern AI isn’t just a model; it’s an agentic system that plans, retrieves, acts, and evaluates in a tight loop. In this piece, I break down…
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How We Automated 81% of Customer Support with AI—While Uplifting CX, Speed, and ROI
Automating 81% of support with AI didn’t happen by accident—it required an AI-first strategy, tight knowledge management, and rigorous conversation design. By deploying Fin across our…
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From Resolutions to Outcomes: How We Price AI Agents Fairly and Amplify Customer Value
AI pricing should align with real, measurable value. Resolutions were a great starting point, but as Fin now handles complex, multi-step, and human-in-the-loop workflows, success is…
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AI-Native Product Development with Amplitude: A Practical Loop
Build an AI-native product loop that turns Amplitude behavior data into focused hypotheses, safer experiments, and evidence-backed roadmap decisions.
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How I Used Claude Code to Run a Full Content Audit in Hours—and Uncovered Big SEO Wins
I put Claude Code to work on a full SEO content audit and was surprised by how quickly it produced credible, data-backed insights. By loading my…
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February Fin Breakthroughs: Master complex workflows, natural voice, 2-minute Shopify, smarter ops
This February, we removed four major constraints holding AI agents back: complexity in automation, voice quality under pressure, Shopify setup friction, and helpdesk overhead. Procedures and…
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Ship MVPs in Days, Not Months: My Proven Prompt Prototyping Playbook for Product Teams
Most MVPs fail because teams validate too slowly and ship on assumptions. I use a prototyping prompts playbook to turn ideas into briefs, flows, and test…
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Behavioral Analytics That Crush Fraud: Spot Anomalies, Prioritize Risk, Act with Confidence
Fraud teams don’t need more alerts—they need clarity, speed, and confidence. Behavioral analytics delivers that by surfacing true anomalies, prioritizing risk by impact, and enabling fast,…
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Browse topics
- AI Strategy (430)
- Generative AI (113)
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- Leadership (81)
- Product Management (394)
- Product Management Leadership (374)
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