July 2026
- AI Strategy (315)
- Generative AI (106)
- IT Leadership (33)
- Leadership (76)
- Product Management (344)
- Product Management Leadership (306)
- Uncategorized (32)
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The July 2026 AI Evaluation Lab Leak: A Leader’s Playbook
A practical governance and containment playbook for testing dangerous model capabilities without turning an internal evaluation into a real-world incident.
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Visual Search for Messy B2B Catalogs: An Intent-First Playbook
A practical framework for turning ambiguous product images into intent-aware retrieval, trustworthy ranking, and measurable B2B sourcing outcomes.
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How to Evaluate AI Risks That Emerge After Deployment
A practical framework for testing stateful AI across long user trajectories, monitoring drift after launch, and resisting misleading satisfaction metrics.
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Persistent AI Agent Memory: A Knowledge Graph Blueprint
A practical blueprint for modeling, governing, retrieving, and evaluating knowledge graph memory that an AI agent can safely use over time.
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How to Build Persistent Business Memory with AI Knowledge Graphs
Learn how to design a time-aware, evidence-linked knowledge graph that lets AI recover current decisions, their history, and provenance.
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Codex Token Cost Optimization Without Losing Useful Context
A practical model for trimming Codex context, preserving decisions, and proving token savings without creating more retries or review work.
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A Practical Guide to Metaphors for Understanding Language Models
A practical framework for choosing AI metaphors, exposing their hidden assumptions, and translating human-sounding behavior into testable product claims.
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How to Lead When AI Expands Roles Before Titles Change
A practical operating model for using AI across functional boundaries without blurring accountability, review, or specialist ownership.
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How to Benchmark AI Humanizers Without Gaming the Test
A practical framework for testing AI humanizers across detector disagreement, content fidelity, writing quality, latency, and workflow fit.
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Enterprise AI Ownership: What Your Company Must Control
A practical framework for deciding which AI assets, learning loops, contracts, and platform layers your enterprise must control as models change.
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China AI Safety Governance at WAIC 2026: A Product Playbook
A practical playbook for turning China’s WAIC 2026 signals on loss of control, agent boundaries, and cyber risk into product decisions.
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AI Video Generation Advances: A Product Leader’s Playbook
A practical framework for turning gains in video coherence, control, and open-source access into workflows, evaluations, and sound product bets.
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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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How to Run Customer-Facing AI Implementations That Scale
A practical operating model for turning vague customer AI requests into safe production deployments without creating a permanent custom-work queue.
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How to Scale AI Pilots Into Everyday Operating Work
A practical operating model for choosing the right workflow, setting AI boundaries, measuring value, and scaling with auditable controls.
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Cost-Aware AI Model Selection: Pay for Accepted Work
A practical framework to compare AI models by accepted-result cost, test quality, choose hosting, and route production work with safe fallbacks.
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How to Design Production AI Guardrails for Sensitive Workflows
A practical control-plane design for routing sensitive data, constraining agent actions, enforcing approvals, testing failures, and preserving auditability.
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Claude Code for Non-Technical Professionals: A Safe Start
A practical, low-risk way to use Claude Code for file-based product work, with a bounded first project, review gates, and reusable prompts.
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Gamma’s AI Pivot: Why the Blank Page Mattered More Than AI
Gamma’s pivot shows how to find an AI-native wedge, prove activation, price real value, and absorb enterprise demand without losing focus.
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How to Build Trustworthy AI Diagnostics for Women’s Health
A practical framework for defining clinical scope, communicating uncertainty, preventing automation bias and governing sensitive health data.
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Browse topics
- AI Strategy (315)
- Generative AI (106)
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- Product Management Leadership (306)
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