Temperature and top-p control LLM output consistency. Learn exactly what each does, when to use each setting, and the specific configurations for extraction, chat, and creative tasks.
Templates transform prompts from one-off scripts into reusable infrastructure. Learn the structure that works at scale, when to extract a template, and how to manage them without overhead.
AI is pattern recognition at scale. This guide explains how frontier models like Claude and GPT-4 actually work, which models exist today, what they're genuinely good at, and a real Python example you can run right now.
Three architecture patterns for AI agents, from simple tool routing to agentic loops. Learn how to structure tool calling, set memory limits, and avoid the most common failure modes—with working code.
Large language models predict one word at a time based on statistical patterns learned during training. Understanding how this works explains their strengths, limitations, and why they fail in specific ways—and helps you use them effectively.
