Intermediate Track

Few-Shot Prompting: Teaching AI by Example

Learn how to use few-shot prompting to dramatically improve AI output quality by showing the model exactly what you want through examples.

XML Tags & Delimiters: Structure Your Prompts Like a Pro

Learn how to use XML tags and delimiters to clearly separate instructions from data in your prompts — a technique that dramatically reduces errors on complex tasks.

Chain of Thought Prompting: Make AI Reason Step by Step

Chain of Thought (CoT) prompting forces AI to show its reasoning before answering — dramatically improving accuracy on logic, math, analysis, and multi-step tasks.

Avoiding Hallucinations: Keep AI Grounded in Facts

Learn what causes AI hallucinations and the specific prompting techniques that dramatically reduce fabricated facts, fake citations, and confidently wrong answers.

Constrained Generation: Force Structured Output

Learn how to make AI models reliably output JSON, XML, CSV, and other structured formats — essential for integrating AI into real applications and workflows.

System Prompts: Giving AI Standing Instructions

System prompts let you set persistent rules, persona, and context that apply to every message in a conversation. Learn how to write them effectively and when they change everything.

Prompting With Long Documents and Large Context

Pasting a 50-page document and asking 'what do you think?' rarely works. Learn how to structure prompts for long-form content, extract what matters, and work around context limits.

Multimodal Prompting: Working with Images, Files, and Mixed Content

Modern AI models can see, read files, and process multiple input types at once. Learn how to structure prompts that work with images, documents, data files, and mixed content effectively.