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The paper fills a documented gap by writing down, for the first time in a consolidated form, the end-to-end practice for building production custom AI agents — knowledge the authors note has previously existed only in informal sources like podcasts, blogs, and leaked system prompts.
Practitioners using LLMs to extract structured signals from open-ended text should invest in understanding input data quality first — prompt tuning and model upgrades offer only marginal, bounded gains when the key information is absent from the source text.