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Field notes on AI strategy, engineering leadership, platform architecture, and shipping practical systems.

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AI strategy How to separate prediction, generation, and business value. AI infrastructure Architecture choices for retrieval, context, and model workflows. Leadership Current role notes and engineering leadership context. Developer workflow Practical field reports from local models and agent tooling.

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21 published posts

3 min read

AI Infrastructure Decisions in a Growing Compute Economy

As enterprises increasingly adopt AI, the infrastructure needed—spanning compute, storage, networking and energy—has become a central concern. This covers everything from data centres and chip selection to cooling and energy sourcing. Unlike conventional IT stacks, an AI strategy cannot be uniformly deployed; each function within a business may require tailored approaches. AI has become a business-wide decision, not confined to technology departments.