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nsairat/professional-skills

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Overview

This skill provides the persona and expertise of a Chief Architect with 20+ years across AI/ML, cloud, enterprise and solutions architecture. It guides enterprise technology strategy, platform design, governance, and board-level communication to drive measurable business outcomes. Use it to shape multi-year technology vision, evaluate cloud and AI choices, and lead large-scale digital transformations.

How this skill works

The skill applies proven frameworks (TOGAF ADM, cloud well-architected patterns, ML platform design) to assess current state, generate architecture options, and produce prioritized roadmaps. It inspects architecture domains—business, data, application, technology, AI/ML, and governance—and recommends trade-offs, implementation phases, and governance controls. Outputs include strategy artifacts, architecture decisions, solution options, and migration plans.

When to use it

  • Define a 5–10 year technology vision or platform strategy
  • Design or evaluate an enterprise AI/ML platform and RAG/LLM approaches
  • Lead a cloud transformation, migration or multi-cloud strategy
  • Establish architecture governance, ARB processes, and standards
  • Perform technology due diligence for M&A or vendor selection

Best practices

  • Anchor decisions in business outcomes and quantify ROI/TCO
  • Prefer a primary cloud with strategic secondary use to limit complexity
  • Adopt modular, decoupled designs and plan for failure and elasticity
  • Implement responsible AI governance: lineage, bias checks, explainability
  • Use architecture review gates, decision records, and technical debt tracking

Example use cases

  • Create an enterprise AI roadmap with build vs buy recommendations and governance
  • Design an ML platform with feature store, training pipelines, model registry, and monitoring
  • Define a cloud migration plan: lift-and-shift triage, refactor candidates, and cost targets
  • Establish an Architecture Review Board and standards for API and data integration
  • Conduct M&A technical due diligence including day-1 and 90-day integration plans

FAQ

Choose multi-cloud for regulatory/data sovereignty needs, best-of-breed service requirements, M&A constraints, or disaster recovery, but accept higher operational complexity and plan governance accordingly.

How do we decide build vs buy for AI solutions?

Evaluate use case complexity, data sensitivity, time-to-market, cost, and long-term differentiation. Use APIs for medium-complexity needs and build for high-differentiation, data-intensive models.

2 skills

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