Deep explanation
Anthropic trade-offs for a document intelligence pipeline
Junior trade-off question: compare a rules-plus-small-Claude-model fallback with a full Claude PDF extraction rebuild for invoices and contracts, using accuracy, cost, latency, and risk, then propose a two-quarter plan.
Quick answer
The quick fix is cheap and low-risk because rules still handle the easy fields and Claude only fills the gaps, but it keeps brittle rules and struggles with layouts the OCR breaks. The rebuild lets Claude read the whole PDF and return structured fields with the source text it used, which handles messy contracts better but costs more per document and needs a solid evaluation set. I would ship the quick fix this quarter, build the evaluation set at the same time, and move document types to the new pipeline only when they beat the old one on accuracy and cost.
The interview question
Your document intelligence pipeline extracts fields from invoices and contracts. One option is a quick fix: keep the current OCR plus rules and call a small Claude model only for fields the rules miss. The other is a bigger rebuild: send whole PDFs to Claude with schema-based extraction, citations, and batch processing. Compare the trade-offs and recommend a plan for the next two quarters.
Deep explanation
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