incident management
- AI Strategy (429)
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- Leadership (81)
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China AI Governance: An Operating Plan for Product Leaders
A practical plan for adapting AI products to China’s focus on deployment risk, agent safety, human override, incident response, and auditability.
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How to Run AI Support Quality as a Continuous Operation
A practical operating model for measuring AI support quality, gating releases, shaping conversations, and turning live failures into controlled improvements.
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AI-Enhanced Threat Intelligence: From Feeds to Decisions
A practical operating model for turning threat intelligence and internal exposure data into faster, evidence-backed security decisions with controlled AI autonomy.
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AI Safety Governance for Autonomous Systems That Can Act
A practical operating model for autonomous AI, covering action boundaries, least-privilege access, human approvals, audit trails, kill switches, and release gates.
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Frontier AI Pacing: An Enterprise Safety Assurance Playbook
A practical framework for turning frontier-model evidence into deployment gates, vendor requirements, and coordinated incident controls for AI agents.
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How to Evaluate and Control Enterprise AI Agents at Runtime
A practical operating model for evaluating agent quality, gating risky actions, preserving identity across queues, and proving your kill switch works.
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Production AI Reliability: How to Earn User Trust
A practical operating model for setting AI autonomy, testing full workflows, exposing accountability, and recovering before failures erode trust.
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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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Governing AI Security Beyond the Open-Weights Debate
A practical operating model for product leaders to govern jailbreak disclosure, open-weight releases, agent containment, and incident-response readiness.
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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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From Customer Signals to Reliable Product Operations
A practical framework for routing support, behavioral, research, and reliability signals into faster response and stronger product decisions.
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Built for Your Biggest Days: How We Engineer Fair, Reliable Scale Without Downtime
Enterprise teams ask sharper questions about scale—and they should. I share how we handle 150k+ requests/sec, shard our source-of-truth data with Vitess and PlanetScale, and reshape…
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Stop Blurring the Lines: Clear Product–Engineering Boundaries to Boost Quality and Prevent Burnout
Blurry lines between product and engineering lead to burnout, slow delivery, and quality problems. I share a practical model that restores clarity: product trios own the…
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Reliable AI Infrastructure: A Product Leader’s Playbook
A practical framework for exposing silent AI failures, hardening runtime paths, controlling releases, and turning SLOs into product decisions.
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The Safety of Speed: 180 Deploys a Day, 12‑Minute Releases, 99.8%+ Availability
Speed and safety are not opposites—they reinforce each other when you ship in small, frequent batches. By automating our pipeline end-to-end, we move from merge to…
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How to Build AI-Enabled Cybersecurity Operations Safely
A practical 90-day model for using AI in threat detection and incident response with clear authority limits, metrics, and governance.
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Inside the Engine Room: How I Drive Scalable Analytics APIs, Reliability, and Performance
I share how I focus on the middleware and compute systems that power analytics at scale so teams can trust their data. I detail how overseeing…
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Agentic AI for Incident Response: A Practical Operating Model
A practical operating model for scoping, governing, evaluating, and rolling out incident-response agents without surrendering human control.
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