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LessonsMarch 5, 202618 min read
Why Most AI Systems Fail in Production
Five recurring failure modes that show up when promising AI demos meet compliance, cost, latency, and messy real-world data.
ProductionFailure ModesLessons
This post is part of the Learning Log archive. The architecture and key decisions from this piece are summarized in the header above.
The core theme is practical: production AI systems are defined by operational discipline — observability, fallback behavior, cost controls, and the interfaces between components — not isolated model quality.
The full write-up is being migrated into the new publishing flow. Check back soon.