Prompt Engineering for Lawyers (On-Demand)

Course Description

This course offers a comprehensive introduction to the practical techniques and best practices for leveraging generative AI. Designed for attorneys and legal professionals, the course emphasizes the importance of treating AI as a junior associate—capable of producing valuable work product but requiring careful supervision and verification. Participants will explore the unique risks associated with AI, such as hallucinations and confidentiality concerns, and learn how to mitigate them through structured prompting strategies. The curriculum covers essential prompt engineering methods including role-based prompting (personas), chunking, iterative refinement, prompt chaining, few-shot prompting, and flipped interaction prompting. Through real-world legal scenarios, students will gain hands-on experience in designing effective prompts, managing AI outputs, and ensuring that generated content aligns with legal standards and client objectives. By the end of the course, participants will be equipped to integrate AI into their legal workflows, enhancing efficiency, accuracy, and risk management in drafting, negotiation, and document review.

Principles

• Effective AI Starts with Effective Prompting
  • The quality of AI-generated legal work depends largely on the quality of the instructions it receives.
  • Clear, specific, and well-structured prompts produce more accurate, useful, and efficient results than vague requests.
• Treat AI as a Junior Associate—Not a Final Decision-Maker
  • AI can accelerate drafting, research, negotiation, and document review, but its work requires attorney supervision and independent verification.
  • Lawyers remain responsible for the accuracy, legal sufficiency, and ethical use of AI-generated content.
• Managing AI Risk Is as Important as Improving Efficiency
  • Prompt engineering should incorporate safeguards against hallucinations, confidentiality breaches, and other AI-related risks.
  • Attorneys should use AI in ways that protect client information and comply with professional and ethical obligations.
• Structured Prompting Produces Better Legal Work Product
  • Techniques such as role-based prompting, chunking, iterative refinement, prompt chaining, and few-shot prompting enable lawyers to guide AI toward more reliable and context-appropriate outputs.
  • Mastering these methods helps integrate AI effectively into everyday legal workflows.

Syllabus

1. Why Prompt Engineering?
   • How AI is used in legal work
   • Treating AI like a junior associate
2. Key Risks
   • AI making things up (hallucinations)
   • Protecting confidential information
3. Prompting Basics
   • Giving clear instructions
   • Assigning roles (personas)
4. Core Techniques
   • Breaking big tasks into steps (chunking)
   • Improving drafts step-by-step (refinement)
   • Building on previous answers (chaining)
   • Showing examples to guide AI (few-shot)
   • Having AI ask clarifying questions first (flipped interaction)
5. Practical Legal Examples
   • Drafting and reviewing agreements
6. Best Practices
   • Always check AI’s work
   • Use your legal judgment