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Data

    AI Privacy Is a Plumbing Problem, Not a Policy Problem Privacy in AI systems fails in the details: what gets logged, who can replay prompts, how long artifacts linger. Treat it as infrastructure, not a checkbox. privacy ai data Your AI Pipeline Is Just ETL With Extra Steps (And That's Fine) AI data pipelines are ETL with a retrieval layer bolted on. The discipline is the same as always: detect change, chunk intelligently, keep indexes fresh. data ai infrastructure Video Understanding AI: What Actually Works I pointed a video understanding pipeline at 200 hours of meeting recordings. The results taught me more about pipeline design than about meetings. llm ai data Data Engineering Patterns: Batch vs. CDC vs. Streaming A comparison of data ingestion patterns from building the fintech startup's financial data pipelines, plus when each one actually makes sense. data metrics architecture Most Teams Are Not Ready for MLOps MLOps is real, but most teams buying MLOps tooling cannot even version their training data. Fix the basics first. ai devops data Data Mesh Is an Org Chart Fix, Not a Tech One Most data problems are ownership problems. Data mesh gets that right. But adopting it as an architecture diagram exercise misses the point entirely. data architecture engineering GDPR for Engineers: What We Actually Built at a Fintech Startup Eleven days before the GDPR deadline: the technical work we did at a fintech startup — data mapping, consent storage, erasure pipelines, and the backup problem. compliance privacy business How I Build Data Pipelines That Actually Survive Production Every pipeline I've built at the fintech startup broke at some point. Here's the design approach that made them recoverable instead of catastrophic. data reliability architecture