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Why your RAG returns garbage (and it's not the model)

Your RAG bot just gave a confident, detailed answer. And it's completely wrong . Here's the part that'll annoy you: the model did nothing wrong. It answered perfectly — using the text you handed it.

  • Chunking: Incorrect fixed-length cuts split sentences or questions from their answers
  • Embedding: Retrieval model may not produce similar vectors for related information
  • Ranking: Re-ranker can prioritize most relevant chunks for accurate answers

Blog Pipeline Fence Corruption: How a Naive Sed Rule Swallowed Markdown Code Blocks

A draft came out of my blog generation pipeline with the frontmatter intact, the title correct, the word count in range, and roughly 1,400 words of prose rendered inside a single syntax-highlighted…

  • Sed rule corrupted Markdown code blocks by removing closing fences, causing unclosed code blocks.
  • Fix involved changing sed rule to match whole-document wrapper instead of substitution.

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