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Gilder Miller
Gilder Miller

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When Your Data Pipeline Becomes a Coffee Pipeline

I'm at my favourite coffee shop, laptop open, terminal humming. The barista asks what I'm working on. "Just setting up a real-time data pipeline," I say, trying to sound casual.

She nods knowingly. "Like for... coffee orders?"

I laugh. "No, for business intelligence. Using Python, PostgreSQL, and AWS Lambda to process streaming data."

Next thing I know, I've been roped into building their new "smart ordering system." Suddenly my data pipeline is literally a coffee pipeline. My Jenkins CI/CD is now triggering espresso shots. My MongoDB is storing latte preferences. My GCP functions are calculating optimal milk-to-coffee ratios.

Three weeks in, the system works perfectly. Too perfectly. It's now predicting when customers will arrive based on their previous order patterns. The barista calls it "creepy but helpful." I call it an unintended consequence of saying "yes" too quickly.

How would you handle it? If you built something that worked too
 well in an unexpected context, would you embrace it or pull back?

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