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Python Development Workflow for AI era

AI made coding faster. But faster code without a fast feedback loop is just faster chaos. If we can code faster, we need everything around it to keep up: pipelines, testing, deployments, and monitoring. In this article, we break down a Python development workflow designed for shipping reliably in the AI era. Four pipelines. Three environments. Small MRs, you're willing to throw away. Deployments that are non-events. This is the first in a series where we'll dig into each step - from automated pipelines to feature flags to monitoring that catches issues before your customers do.