Agent Analytics
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Measuring Enterprise AI Value: A Practical Adoption System
A practical system for connecting enterprise AI usage to repeat behavior, workflow outcomes, quality guardrails, and defensible financial impact.
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A Practical Privacy Control Model for AI Agent Trace Analytics
A practical control model for collecting useful AI agent traces while limiting exposure across capture, redaction, access, exports, and retention.
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How to Measure Enterprise AI Agent Performance and ROI
A practical framework for routing agent work, setting hard budgets, measuring accepted outcomes, and proving enterprise AI ROI against a credible baseline.
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AI Agent Data Privacy: A Product Leader’s Launch Playbook
A launch-ready framework for mapping AI agent data flows, minimizing collection, redacting traces, setting retention, and testing every control.
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How to Build AI Agent Infrastructure That Proves Value
A practical operating model for tracing agent runs, diagnosing failures, controlling routing costs, and connecting performance to business outcomes.
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How to Roadmap AI Agents, Robotics and Dedicated Hardware
A practical framework for sequencing agent autonomy, robotics, and dedicated hardware without letting compelling demos outrun product evidence.
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Enterprise AI Spend Is Concentrating. Manage It as a Portfolio
A practical operating model for separating AI activity from value, attributing costs correctly, and scaling proven workflows without rewarding waste.
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Production AI Agent Operations: A Practical Operating Model
A practical operating model for reliable AI agents, covering orchestration, safe retries, evaluations, controlled releases, monitoring, and incidents.
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Reliable Agentic AI Architectures: A Production Blueprint
A production blueprint for agentic AI covering bounded graphs, independent verification, safe tool execution, durable state, and eval-driven rollout.
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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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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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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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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 Use Novus, the First Product Agent, to Turn Rapid Releases into Measurable Wins
Rapid releases don’t have to blur what’s working. I use Novus to connect code velocity to customer outcomes with eval-driven development, observability, and continuous discovery—without drowning…
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AI Agent Product Development: From Workflow to Autonomy
A practical framework for developing AI agents through focused workflows, bounded capabilities, measurable outcomes, and evidence-based autonomy.
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Why We Made Fin the Most Open Agent: Instant HubSpot & Freshdesk Support With 76% Resolutions
Fin now runs as a Service Agent on top of HubSpot and Freshworks, so you can deploy world-class automation without leaving your helpdesk. Setup takes less…
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Reusable AI Agent Workflows Need Evaluation Contracts
A practical model for packaging agent skills with traces, test fixtures, guardrails, and product metrics so reuse does not weaken accountability.
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Supercharge Insights with Amplitude Agent Connectors: Connect Notion, Slack, Linear & More
When insights and actions live in different tools, teams lose speed and clarity. Amplitude’s Agent Connectors help by uniting Notion, Atlassian, Slack, Linear, and more with…
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How to Design a Dependable CLI Agent Users Can Trust
A practical framework for building CLI agents with narrow contracts, safe permissions, predictable execution, and measurable reliability.
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Speed-to-Lead Is Dead: How AI Agents End the Wait and Rebuild a High-Velocity Sales Org
Prospects shouldn’t wait after they click “contact sales.” AI Agents engage buyers instantly at the peak of intent, collapsing qualification, discovery, and even an initial demo…
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Browse topics
- AI Strategy (315)
- Generative AI (106)
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- Leadership (76)
- Product Management (344)
- Product Management Leadership (306)
- Uncategorized (32)
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