Insights
Perspectives on engineering intelligent systems — from technical architectures to governance frameworks.
Engineering AI Observability
Modern AI systems require new approaches to monitoring that go beyond traditional metrics. We examine the architectural patterns and tooling needed for production-grade observability.
Latest Perspectives
Optimizing GPU Cloud Costs
Practical strategies for reducing cloud GPU spend while maintaining performance for AI workloads.
Read MoreAI Procurement Best Practices
How government agencies can structure AI acquisitions to ensure technical and ethical requirements are met.
Read MoreRed Teaming AI Systems
Our framework for adversarial testing of production AI systems to uncover vulnerabilities.
Read MoreTechnical Debt in AI Systems
Identifying and addressing technical debt patterns unique to machine learning systems.
Read MoreKubernetes for AI Workloads
Architecture patterns and operational considerations for running GPU workloads at scale.
Read MoreAI Governance Frameworks
Comparing technical implementations of emerging AI governance requirements.
Read MoreStay Informed
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