🧠 LLM & AI Agents

Understand what LLMs and AI agents are, how they are trained, and how a QA tester builds a simple test agent with the OpenAI API, with hands-on labs.

You learned how to USE AI for testing on the Claude AI page — this page opens the hood. What is an LLM really doing, how is it trained, what turns it into an agent, and can a tester build and even fine-tune one alone with the OpenAI API? Everything here is hands-on and simulation-backed: you will predict tokens like a model does before you ever call one.

What you can learn on this page

  • 🎯 Intro: The AI, ML & LLM Map — AI, ML, Deep Learning and LLM are not four competing things — they are one map at four zoom levels, and the zoom axis is exact: each level is defined by HOW the software acquires its behavior. Rule-based software is told what to do line by line; ML learns beha
  • 🧱 What Is an LLM: Tokens & Prediction — An LLM is your phone keyboard's next-word suggestion grown to planetary scale — and the mechanism matches one-to-one, not loosely: your keyboard learned "what word usually follows" from your own typing history; an LLM learned "what token usually
  • 🎓 How LLMs Are Trained: Pretraining — Pretraining a model is like a photography student who studies millions of photographs without ever being told explicitly "this composition is good, this one is bad" — the mechanism is exact: instead the student is given ONE recurring drill, "giv
  • 🎯 Fine-tuning & RLHF — A pretrained base model fresh out of pretraining is like a brilliant new hire who has read every book in the company library but has never once been shown what a GOOD answer to a customer actually looks like — the mechanism is exact: pretraining only teaches &
  • 🧠 Context Window & the Root of Hallucination — The context window is like a whiteboard that gets erased the moment a meeting ends — the mechanism is exact: everything the model "knows" about your specific conversation lives ONLY in the text currently inside that window, and the instant the conver
  • 🤖 What Is an Agent: LLM + Tools + Loop — A chatbot is a brilliant consultant sitting behind a glass wall in a room full of tools; an agent is that SAME consultant handed a key to walk through the glass and actually use the tools — the mechanism is exact: the consultant's expertise (the LLM) doesn't c
  • 🔧 Function Calling: The Agent's Hands — Function calling is like a call center operator who can only fill out a request form ("please transfer $50 from account X to account Y") and hand it to a human teller — the operator NEVER touches the vault themselves, no matter how confidently they w
  • 🐍 OpenAI API: A Tester's First Call — Calling the OpenAI API for the first time is like ordering from a restaurant menu over the phone instead of walking into the kitchen yourself — the mechanism is exact: you don't need to know how the kitchen (the model's internals) works; you send a structured