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  <title>Carthi P</title>
  <id>https://carthi-portfolio.pages.dev/</id>
  <updated>2026-08-31T18:29:19.281273+00:00</updated>
  <entry>
    <title>Shrinking a PyTorch Model&#x27;s Memory Footprint with ONNX</title>
    <link href="https://carthi-portfolio.pages.dev/articles/onnx-inference-footprint/"/>
    <id>https://carthi-portfolio.pages.dev/articles/onnx-inference-footprint/</id>
    <updated>2026-08-31T00:00:00+00:00</updated>
    <summary>A walkthrough of exporting PyTorch models to ONNX for deployment — what actually gets smaller, what doesn&#x27;t, and the export gotchas worth knowing before you ship.</summary>
  </entry>
  <entry>
    <title>What Actually Breaks in a Production RAG Pipeline</title>
    <link href="https://carthi-portfolio.pages.dev/articles/production-rag-lessons/"/>
    <id>https://carthi-portfolio.pages.dev/articles/production-rag-lessons/</id>
    <updated>2026-03-22T00:00:00+00:00</updated>
    <summary>Retrieval quality, not generation quality, is where enterprise RAG systems fail. Notes from building ingestion, embedding and vector search for enterprise document corpora.</summary>
  </entry>
  <entry>
    <title>Designing a PySpark Pipeline That Survives Schema Drift</title>
    <link href="https://carthi-portfolio.pages.dev/articles/pyspark-schema-drift/"/>
    <id>https://carthi-portfolio.pages.dev/articles/pyspark-schema-drift/</id>
    <updated>2025-11-18T00:00:00+00:00</updated>
    <summary>Third-party data changes shape without telling you. Notes on building ingestion that fails loudly at the boundary instead of silently three tables downstream.</summary>
  </entry>
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