Practical Prompt Engineering Masterclass: Hands-On [2026]

Define the audience persona to tailor large language model outputs, guiding the model with act as instructions to write in the reader's voice.

Explore the flipped interaction pattern in prompt engineering by letting ChatGPT ask you questions, gather information, and tailor outputs such as a fitness regime or quizzes, boosting interactivity and efficiency.

Learn to evaluate and maintain prompts through collaborative peer review and automated grading, using large language models to grade outputs and refine prompt catalogs over time.

Engage with the game prompting pattern, where a language model acts as game master to craft rules and scenarios for interactive prompt engineering.

Combine multiple prompt patterns to build sophisticated prompts by using input and alternatives together. Learn a pattern roadmap to solve problems and minimize unknowns.

Large language models learn from vast text and code to predict the next word, using prompts and a stop token, and capture context and word patterns.

Explore few-shot prompts and intermediate steps to guide a large language model through complex tasks, using patterns and examples to reveal step-by-step processes for achieving outcomes.

Analyze common mistakes in few-shot prompts, and learn to design clear input-output prefixes, provide sufficient context, and balance descriptive examples to improve prompt accuracy.

Explore the outline expansion pattern to simplify generating and expanding outlines, fill in content with prompts, and assemble pieces into cohesive content for projects.

Apply the fact check list pattern to verify facts in model outputs, take ownership of generated information, and use prompts to ensure accuracy and avoid convincing but incorrect text.

Apply the tale generation pattern to maintain rules and task focus in long conversations, then blend input patterns and alternative approaches to generate prompts for specific tasks and reminders.

Apply the semantic filter pattern to remove or preserve information by meaning, practice rewriting text for privacy, and build prompt-based tools for daily tasks.

Apply creative prompt engineering with large language models by practicing, experimenting, and collaborating, while staying ethical and up-to-date with research and sharing ideas.