[ Level 02 ]
Practice
Hands-on prompt craft, structured output, workflows, data preparation, and managing prompts as an asset.
Getting to a good prompt: structure, role, example, and output format
Turn a well-written prompt into a reusable prompt template with clear placeholders, and use a test cycle with acceptance criteria to make quality repeatable.
Updated 2026-10-05
Structured output: lists, tables, and JSON
Why free text fails downstream systems, when to use lists, tables, or JSON, and how to demand, repair, and validate a machine-readable model output.
Updated 2026-10-05
Basic workflows: steps and conditions
Build AI workflows step by step — each step's input, action, and output — and decide where conditions, branches, loops, and human approval steps belong.
Updated 2026-10-05
Inputs and data preparation
What separates good input data from bad: cleaning the five typical problems, formatting with clear labels, sizing data to the context window, and privacy early.
Updated 2026-10-05
Your first end-to-end automated workflow
A complete guide to building one automated workflow: goal and exclusions, the seven system parts, no-code build steps, pre-launch testing, and first-week metrics.
Updated 2026-10-05
Prompt management as an asset
Treat prompts as company assets: a shared prompt bank with six core fields, version history of what changed, why, and who approved, and safe template reuse.
Updated 2026-10-05