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Alexandra NacPersonal Operating System
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Expertise

Applied AI Systems

Designing practical AI-powered systems that combine language models, structured workflows, retrieval, tools and application logic.

Capability statement

I build AI features that are part of a working system, not standalone demos — grounded in real data, with clear boundaries around what the AI is allowed to do.

Problems I solve

  • Turning AI models into usable product features
  • Connecting AI to application data and APIs
  • Structuring multi-step AI workflows
  • Reducing hallucinations through grounded retrieval
  • Making AI functionality understandable in the interface

Approach

  • Start from user intent rather than model capability
  • Separate reasoning, retrieval and UI presentation
  • Ground answers in verified content
  • Keep actions safe and reviewable
  • Use structured outputs instead of uncontrolled prose where possible

Full description

I focus on building AI features that are part of a real system rather than isolated chat interfaces. My work explores how AI can retrieve trusted information, reason over structured content, trigger safe actions, support workflows and generate useful outputs inside web applications.
Evidence standard

Strengths

  • Grounded retrieval over hallucination-prone free generation
  • Structured output contracts (blocks/actions, not chat text)
  • Cost/behavior tracing on every LLM call

Current focus

Extending Alex OS's reasoning layer to understand new CMS content types (like Expertise and Skills) without any code changes to the reasoning engine itself.
Internal Links
EvidenceSupportsAI workflow automation proofProjectRelatedMulti-Agent RAGProjectRelatedAlex CMSProjectRelatedAlex OS