Series · 7 of 7 parts · Intermediate
Prompt Engineering That Works
Past the tips-and-tricks noise: the small set of techniques that measurably change model output, and how to know they worked.
What you’ll understand
By the end you write prompts that behave consistently, produce structured output, and survive contact with real users.
Episodes
01Why Your Prompts Fail (and the Anatomy That Works)Role, task, constraints, format: the skeleton under every prompt that behaves.10 min→02Few-Shot: Examples Beat InstructionsOne good example outperforms three paragraphs of description. Here's why, and how to pick them.10 min→03Chain of Thought: When Thinking Out Loud HelpsStep-by-step reasoning improves hard tasks and wastes tokens on easy ones. Know the difference.11 min→04Structured Outputs: JSON You Can Actually ParseSchemas, validation, and retries: making model output machine-readable every single time.11 min→05System Prompts for Agents: The Job DescriptionConstraints, tool guidance, and uncertainty handling for prompts that run unattended.11 min→06Evaluating Prompts: Beyond 'Looks Good to Me'Test sets, A/B comparisons, and regression checks for prompt changes.10 min→07Dynamic Prompts: Context Injected at RuntimePrompts that adapt to the user, the history, and the task, assembled on the fly.11 min→