Agent Analytics
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- Leadership (76)
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- Product Management Leadership (306)
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Prompt Engineering for Amplitude Global Agent That Holds Up
A practical framework for prompting Amplitude Global Agent to produce grounded, reviewable analysis that supports real product decisions.
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Beyond Accuracy: How I Evaluate AI Customer Service Agents That Delight and Scale
Most teams judge AI agents by accuracy and resolution rates—but that’s only half the story. In my POCs, I mirror real-world messiness, stress-test multi-turn and multilingual…
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Supercharge Core Web Vitals with Amplitude’s Global Agent: Faster Rankings, Happier Users
Core Web Vitals are a direct lever on user experience and SEO, so I use Amplitude’s Global Agent and Amplitude AI Agents to measure and improve…
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How to Prove the ROI of an AI Product Before You Scale It
A practical system for tying AI product behavior to incremental revenue, real cost savings, and risk-adjusted launch, scale, or rollback decisions.
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No More Accidental Agents: How We Engineered Global Agent’s Helpful, Curious Personality
Most AI agents inherit accidental personalities from prompts and defaults. We took a different path, treating personality as a measurable product surface and optimizing it with…
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Knowledge Management for AI Sales Agents: A Practical System
A practical operating model for turning product facts, sales policy, and conversation failures into accurate AI qualification and routing.
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From Internal FinOps Agents to Customer-Embedded Optimization
Learn how to turn internal FinOps agents into governed, customer-embedded workflows that improve cloud cost-to-value and product learning.
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4 Costly Agent Analytics Myths—And the Data-Backed Metrics I Rely on Instead
Agent Analytics can mislead when we over-index on speed, containment, or early green dashboards. I share four common myths I see in human and AI agent…
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How to Link AI Evals to Retention Without Chasing Proxies
A practical playbook for finding early AI quality signals that predict retention, validating causality, and turning them into product decisions.
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5 Proven Agent Skills I Use to Automate Weekly Product Reviews with Claude, Cursor, and Codex
Weekly product reviews can be fast, focused, and high-signal when agentic AI does the prep work. I use five repeatable agent skills—backlog triage, PRD synthesis, experiment…
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Supercharge Claude and Cursor with Amplitude Plug and Play: Your AI Analytics Expert in One Install
I’m introducing Amplitude Plug and Play, a new AI plugin for the Claude and Cursor marketplaces. With a single-install, it turns your favorite AI client into…
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Amplitude AI Product Analytics: A Practical Agent Playbook
Use this practical framework to instrument, evaluate, experiment with, and scale Amplitude Agents around product outcomes rather than AI activity.
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How to Build Agentic AI for Product Analytics and Support
A practical model for connecting behavioral data, safe agent actions, and outcome measurement so product support resolves issues without losing control.
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How We Taught Agentic AI to Speak Product Analytics—and Unlocked Actionable Insights
I describe how we taught agentic AI to understand the nuanced language of product analytics and deliver trustworthy answers grounded in our metric catalog and event…
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Stop Drowning in Tasks: How AI Marketing Agents Restore Focus and Maximize Impact
Marketers don’t have a volume problem—they have a focus problem. AI multiplies effort, but without outcome clarity it only accelerates busywork. I outline a practical playbook:…
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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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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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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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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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Browse topics
- AI Strategy (315)
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