Technical articles and insights on AI, MLOps, and production machine learning.
Technical deep dives and practical guides on agentic AI, RAG evaluation, LangGraph, MLOps, and deploying AI systems in healthcare and industrial settings.
A comprehensive guide on measuring, gating, and monitoring multi-agent and RAG systems using frameworks like LangSmith and RAGAS, grounded in a CNC predictive maintenance case study (EquipmentIQ).
The Human Side of AI explores the critical gap between skyrocketing AI awareness and low actual adoption, using data from the 2025 AI Impact Report. Written from the...
The three ways to extend an LLM aren't interchangeable — each solves a different problem at a different layer. Here's the mental model, with RAG as a fourth...
A deep dive into the architecture and design decisions behind a GenAI-powered movie assistant that combines structured pandas queries, semantic vector search, and LLM reasoning into a single...
A deep dive into RAG architecture, embeddings, chunking strategies, retrieval patterns, and production best practices for building grounded, hallucination-resistant AI systems.
Agentic AI demos look great. Production deployments rarely do. Here's the engineering discipline that bridges the gap.
Hit Rate@K, MRR, NDCG — what they measure, when each one matters, and how to implement them for your RAG system.
A practitioner's comparison of Evidently, Arize Phoenix, Azure ML Monitor, and LangSmith for production ML and LLM monitoring — based on real deployments.