A practical guide to building reliable text-to-SQL systems: architectures, prompts, schema linking, safety, evaluation, and production tips.
Practical techniques to cut AI model serving latency: from quantization and batching to network, GPU, and scheduler tuning, with checklists and examples.
Design and operate a low-latency AI anomaly detection API for streaming data—architecture, models, thresholds, evaluation, and operations.
A practical guide to Reinforcement Learning from AI Feedback (RLAIF): how it works, key algorithms, design choices, pitfalls, and evaluation.
A practical guide to designing an AI churn prediction API—architecture, data/modeling choices, endpoints, MLOps, metrics, and code examples.
Learn how Constitutional AI aligns models using explicit principles, self-critique, and AI feedback, with recipes, code, and evaluation tips.
