TL;DR Artificial intelligence can generate alternatives, investigate hypotheses, and optimize selected objectives at a speed that changes the economics of enterprise analysis. But the value of that capability depends on

Continue ReadingThe Question Bottleneck: Defining Objectives Before AI Explores Solutions

Animation: Workloads can remain available while management capabilities require recovery and verification before return to service. TL;DR I am releasing a new technical whitepaper, Beyond High Availability: Designing and Validating

Continue ReadingBeyond High Availability: Proving VCF 9.1.x Management-Plane Recovery

TL;DR Enterprise organizations have spent generations building operating models around a practical constraint: sophisticated expertise is expensive to develop, difficult to distribute, and limited in availability. Artificial intelligence is changing

Continue ReadingThe Intelligence Abundance Problem: When Answers Outrun Decisions

TL;DR AI-driven discovery becomes valuable when an unconventional solution survives independent verification. But a mathematically valid algorithm, a successful simulation, or an improved benchmark score does not automatically justify production

Continue ReadingFrom AI Discovery to Production: Proof, Governance, and Engineering Trust

TL;DR Most enterprise network architectures begin with established design patterns. Engineers choose proven topologies, routing protocols, redundancy models, and traffic-engineering methods because those approaches have understandable failure behavior and operational

Continue ReadingCan AI Discover Better Network Architectures? Designing a Controlled Experiment

TL;DR Artificial intelligence can generate unconventional engineering ideas, but generating ideas is not the same as discovering valid solutions. A credible AI discovery engine needs an architecture that separates candidate

Continue ReadingThe AI Discovery Engine: Generators, Evaluators, and Verification

TL;DR Much of artificial intelligence is evaluated against human performance. We ask whether a model can pass examinations, write convincing explanations, produce expert-level code, solve mathematical problems, or reason through

Continue ReadingBeyond Human Benchmarks: Why AI’s Greatest Value May Be Discovery, Not Imitation