Building Privacy Aware Infrastructure in the AI-Native Era
summary
An AI-native asset classifier combines a hybrid deterministic rules + LLM fallback that cuts the set of nodes needing LLM review from a 100,000-node example down dramatically so millions of assets scale. It builds ranked evidence briefs, uses a three-LLM judge panel with Cohen’s Kappa and a human review gate to freeze trustworthy ground truth, runs shadow mode and promotes stable patterns into rules.yaml distillation, yielding millisecond deterministic decisions, far lower cost, and auditable replay.
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chapters (11)
- 0:00Privacy-aware infrastructure intro
- 1:28What is privacy-aware infrastructure
- 3:56Asset classification importance
- 5:22Designing classification pipeline
- 7:09Handling noisy signals challenge
- 8:57Managing drift and variability
- 11:02Scaling with LLMs challenge
- 13:30Lessons from failed approaches
- 15:59Three key principles
- 17:01Future directions
- 18:04Closing and call to action
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