Evaluating GenAI Systems (Why 'It Feels Good' Isn't Enough)
GenAI systems need real evaluation — accuracy, relevance, safety — just like any other engineering system, not vibes-based judgment.
Beginners
AI Agents 101: From Chatbot to Agent
The shift from a model that answers questions to one that takes real actions using tools — the plan, act, observe, repeat loop.
Hallucinations: Why They Happen and How to Reduce Them
The honest explanation for why LLMs make things up, and practical ways to reduce it — grounding, citations, and a few other levers.
Embeddings and Vector Similarity
How text gets turned into numbers that capture meaning, and why ‘similar meaning = nearby numbers’ is the foundation of search, recommendations, and RAG.
Prompting Fundamentals
Why specificity beats cleverness, and how to talk to a model that takes everything you say literally.
Tokens, Context Windows, and Why They Matter
What a token actually is, why every model has a memory limit, and why this quietly affects cost, speed, and what you can even ask a model to do.
How LLMs Actually Work (Next-Token Prediction, Simply Explained)
No math-heavy transformer internals, just the core idea: an LLM is a very sophisticated autocomplete engine trained on huge amounts of text.
What Is Generative AI (and What It Isn't)
The simple difference between predictive AI and generative AI, explained without the jargon.