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If You Can Survive a Toddler, You Can Ship LLMs in Production

A few years back I was running a time-series pipeline that scored incoming product reviews on a 1-10 scale. The scorer was an LLM. Reviews rolled in continuously, ratings flowed into a dashboard the product team checked every Monday morning. Everything ran clean for months. Then one Monday the chart had a step in it. Reviews from the prior week averaged 6.4. The current week averaged 7.6. Same product. Same customers. The reviews themselves, when I went back to read them, looked indistinguishable from what we had been getting all year. The model had changed. The provider had pushed a quiet update to the weights, and the LLM that gave us 6.4-equivalent scores last week was now giving 7.6-equivalent scores for the same content. Every historical comparison in that dashboard was silently invalid. The cleanup took a week. The harder conversation was about how much of our reporting had been real in the first place. That kind of failure is the default behavior of LLMs in production. Trying
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Fashion Kavitha

30d ago
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