<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Module 1: Inference &amp; Prompt Injection - AI 101 — Agents, MCP &amp; the Agentic Security Model</title><link>https://fortinetcloudcse.github.io/ai-101/02inference/index.html</link><description>This page covers the theory behind how LLMs work at the API level — tokens, context, message roles, sampling, and why the prompt injection attack in Lab 1 is not a bug that can be patched. It is also a reference you can return to during later modules when you need a reminder of how a specific piece works.&#10;By the end of this page you should be able to explain:</description><generator>Hugo</generator><language>en-US</language><atom:link href="https://fortinetcloudcse.github.io/ai-101/02inference/index.xml" rel="self" type="application/rss+xml"/><item><title>Lab 1 — Prompt Injection</title><link>https://fortinetcloudcse.github.io/ai-101/02inference/1_lab.html</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://fortinetcloudcse.github.io/ai-101/02inference/1_lab.html</guid><description>Ollama is already running from the setup step. You interact directly with the inference endpoint using two scripts in lab-app/scripts/ — but read through the prompts below first so you know exactly what the model is being asked to do.&#10;Your path: Docker ComposeKubernetes / Helm Locked in — every lab page follows this choice. ​ Docker Compose Kubernetes / Helm Docker Compose — every command on this page runs on your own machine.</description></item></channel></rss>