— Techniques
Prompt Engineering
The craft of designing inputs to LLMs to get reliable, high-quality outputs.
Also known as: Prompt Design · Prompting
What is Prompt Engineering?
Prompt engineering is the practice of writing structured AI inputs — including role assignments, output formats, examples, and constraints — to consistently get the desired behaviour from an LLM. Good prompt engineering is the difference between a 60%-quality output and a 95%-quality one. ONROL spends Day 1 of the Generalist track entirely on prompt patterns: structured prompts, chain-of-thought, few-shot examples, output formatting, and hallucination reduction.
— Related
Terms connected to Prompt Engineering
Models
LLM (Large Language Model)
An AI model trained on huge amounts of text that can understand and generate human language.
Open →Techniques
Chain-of-Thought (CoT)
A prompting technique where you ask the AI to think step-by-step before answering.
Open →Techniques
Few-Shot Prompting
Showing the AI 2-5 examples of the desired output before asking for a new one.
Open →Techniques
System Prompt
The hidden instruction that shapes an AI's persona, rules, and behaviour.
Open →Concepts
Tokens
The chunks of text LLMs process — roughly 0.75 words each.
Open →— Apply this
From definitions to deployed projects.
Knowing what a term means is step one. ONROL's AI Generalist track gets you shipping projects that use it.
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