Developer loses 79% of extracted data after AI model treats '<TAB>' as literal text

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A developer building an AI-powered data extraction pipeline lost 246 of 310 records because the language model output the literal string '<TAB>' instead of an actual tab character, exactly as instructed. The bug was compounded because the pipeline's rejection counter lumped together parsing failures and hallucinated content under a single field, making a catastrophic format error look like the integrity checker working correctly. The fix involved replacing the ambiguous separator name with a concrete worked example using a pipe character, after confirming the corpus contained none across nearly eight million characters. A secondary lesson emerged when the worked example used real source text, causing the model to copy it verbatim and extract nothing else — requiring a fictional placeholder name to prevent imitation. The developer also added a fast single-fragment probe flag, cutting the time to detect prompt contract failures from a full pipeline run down to roughly seven seconds.

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ProgrammingDEV Community ·

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