Prompt Engineering Fundamentals
Master the art of writing effective prompts that get consistently great results from any AI model. This lesson teaches the core principles of prompt engineering with practical examples for legal professionals.
Step 1: Why Prompting Matters
The difference between a useless AI response and a brilliant one often comes down to HOW you ask. A vague prompt like 'Write about car accidents' gives generic content. A specific prompt like 'Draft a demand letter introduction for a rear-end collision case where my client suffered a herniated disc at L4-L5, the defendant ran a red light, and there are two witnesses' produces highly targeted, actionable output. Prompt engineering is the skill of communicating precisely with AI to get the results you need.
Step 2: The CRAFT Framework
Use the CRAFT framework for consistent results: Context (set the scene — 'You are a personal injury attorney in California'), Role (define who the AI should be — 'Act as an expert demand letter writer'), Action (what to do — 'Draft a liability analysis section'), Format (how to structure output — 'Use numbered paragraphs with legal citations'), and Tone (communication style — 'Formal and persuasive, suitable for insurance adjusters'). Applying all five elements dramatically improves output quality.
Step 3: Being Specific and Structured
Vague inputs produce vague outputs. Always include: specific facts and details relevant to your task, clear constraints ('Keep it under 500 words', 'Focus only on liability'), desired output structure ('Create a table with columns for...', 'List in order of importance'), and examples of what good output looks like. For legal work, include case details, jurisdiction, applicable statutes, and the specific legal standard you're working with. The more context you provide, the less the AI needs to guess.
Step 4: Iterative Refinement
Great prompts rarely happen on the first try. Use iterative refinement: start with your best prompt, review the output critically, identify what's missing or wrong, and modify your prompt to address those gaps. Common refinements include: 'Be more specific about damages calculations', 'Include case law citations from the last 5 years', 'Make the tone more aggressive', or 'Add a section about comparative negligence'. Think of each iteration as coaching the AI to do better.
Step 5: Building a Prompt Library
Create reusable prompt templates for common tasks: demand letter sections, discovery response drafts, deposition question lists, case summaries, client communication templates, and settlement analysis frameworks. Store these in a shared document or tool like Notion. Include placeholders for case-specific details [CLIENT_NAME], [INCIDENT_DATE], [INJURIES]. A good prompt library saves hours and ensures consistent quality across your practice.
Key Takeaways
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Video Resources
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