A practical guide to building robust multi-step AI pipelines with prompt chaining, orchestration patterns, state, testing, guardrails, and cost control.
Design, build, and scale an API-driven data labeling pipeline with quality gates, active learning, and strong governance.
Build a production-ready predictive analytics API with Python and FastAPI—training, serving, security, testing, and MLOps in one tutorial.
A practical blueprint for deploying autonomous AI agents to production—architecture, safety, reliability, evals, cost control, and ops patterns.
A practical guide to advanced chunking in RAG: semantic and structure-aware methods, parent–child indexing, query-driven expansion, and evaluation tips.
