Practical Use Cases
Prompting theory is one thing — knowing WHEN to use AI is the real skill. The highest-value use cases: drafting and editing text, analysing documents, extracting data, brainstorming, code writing, and research synthesis.
Drafting emails and documents: give the AI the key points and tone, let it draft, then edit. Faster than starting from blank.
Data extraction: paste a document and ask for specific information in a table format. AI is excellent at structured extraction from unstructured text.
Research synthesis: feed multiple sources and ask for a summary highlighting agreements, disagreements, and gaps.
Code: describe what you want the code to DO, not how to write it. Include the language, framework, and any constraints.
WRITING: 'Draft a [type] about [topic] for [audience] in [tone]. Key points: [list]. Length: [target]'
ANALYSIS: 'Read this [document] and extract [specific information]. Present as a [table/list/summary]'
BRAINSTORMING: 'Generate 10 ideas for [objective]. Each should be [criteria]. Rank by [metric]'
EDITING: 'Review this text for [clarity/grammar/tone]. Suggest specific improvements with reasoning'
CODE: 'Write a [language] function that [does X]. Input: [type]. Output: [type]. Handle edge cases: [list]'
RESEARCH: 'Summarise the key arguments for and against [topic]. Cite specific evidence where possible'
DECISION SUPPORT: 'Compare [options] across these criteria: [list]. Present as a comparison table with a recommendation'
Build prompt templates for your most common tasks and refine them over time