I have spent thirty-five years watching data tools get declared obsolete and replaced, six times over. The pattern that survives every cycle is the one worth betting on -- and it tells you exactly how to read the current pressure to rebuild everything for AI.
Read moreA single mis-priced transaction can cost a firm millions; the maker-checker pattern gives you a reliable second opinion for AI-driven pipelines. We show how pairing deterministic code with an LLM auditor catches errors that each alone would miss.
Read moreWhen deterministic ETL pipelines start to crumble under ambiguous data and regulatory pressure, agentic workflows can restore reliability without a full rewrite.
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