Tag: evaluation

A Python architecture map for AI, data, and backend teams that need notebooks, prompts, evaluations, services, repositories, and infrastructure to stop collapsing into one folder.

A scikit-learn NPS ordinal classifier with SMOTE, probability calibration, utility-based thresholding, and PSI drift checks. The parts that make it useful to the retention team, not just accurate on a dashboard.

How to turn DSPy and RAG evaluation into a production release loop with golden sets, retrieval checks, generation rubrics, regression thresholds, and versioned prompt programs.

A practical evaluation loop for multi-agent workflows that catches demo-friendly failures in task handoff, tool use, permissions, latency, and completion criteria before release.

How imbalanced classifiers can keep a strong AUC while producing probabilities that break thresholds, alerts, and cost-sensitive decisions in production.