Agentic_ai_evaluation_guide
Agentic AI Evaluation: From Development to Production A Practitioner’s Guide for Engineers and Technical Leaders Grounded in: EquipmentIQ — a production multi-agent RAG system for CNC machinery predictive...
Writing
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.
MCP vs Tool Calling vs Skills — And Where RAG Fits In
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...
Building a Conversational Voice Agent for IMDB Data with LangGraph, FAISS, and Streamlit
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...
Retrieval-Augmented Generation: A Comprehensive Technical Guide
A deep dive into RAG architecture, embeddings, chunking strategies, retrieval patterns, and production best practices for building grounded, hallucination-resistant AI systems.
Why Most Agentic AI Systems Fail in Production (And How to Fix That)
Agentic AI demos look great. Production deployments rarely do. Here's the engineering discipline that bridges the gap.
RAG Retrieval Metrics You Should Actually Be Tracking
Hit Rate@K, MRR, NDCG — what they measure, when each one matters, and how to implement them for your RAG system.
MLOps Monitoring: The Tools Actually Worth Using in 2026
A practitioner's comparison of Evidently, Arize Phoenix, Azure ML Monitor, and LangSmith for production ML and LLM monitoring — based on real deployments.
The Human Side of AI: What the Data Reveals — and What Businesses Are Getting Wrong
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...