Course Content
Module 1: Introduction to Large Language Models (LLMs) in Law
What LLMs Are (and Aren’t): A Lawyer‑Friendly Mental Model Legal Use Cases & Risk Tiers
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Module 2: Fundamentals of Effective Prompt Design for Legal Tasks
The ICI Framework: Intent + Context + Instruction Advanced Prompt Techniques for Legal Work Prompt Debugging: Lost Middle, Ambiguity, and Token Hygiene
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Module 3: Verifying and Validating AI-Generated Legal Content
Validation Mindset: Why Verification Is Non‑Negotiable Hallucinations in Legal Content: Red Flags & Fixes Bias, Relevance, and Fit: Quality Control Beyond Accuracy
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Module 4: Ethical Considerations and Responsible AI Use in Law
Confidentiality & Data Handling: What You Can Paste Into AI Competence, Supervision, and Accountability with AI Build Your Firm AI Policy Template
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Module 5: Building a Personal Prompt Library and Future Trends
Designing a Personal Prompt Library Future Trends: Specialized Legal Models, RAG, and Agents Build 10 High-Value Prompts You’ll Actually Reuse Final Assessment: Applied Prompt Engineering Scenario
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Prompt Engineering for Legal Applications

Module 5 Knowledge Check (Self‑Check)

This self-check mirrors the Module quiz. Use it to test your understanding. If your site uses Tutor LMS Quiz Import, you can import the CSV quiz file provided in the package instead of (or in addition to) this self-check.

  1. A key benefit of building a personalized prompt library is:

    • It eliminates the need for any human review of AI output.
    • It ensures consistent quality and increased efficiency in AI interactions.
    • It allows AI to make independent legal decisions.
    • It is only useful for very simple, non-legal tasks.
  2. When organizing a prompt library, it is most effective to categorize prompts by:

    • The length of the prompt.
    • The color of the AI tool’s interface.
    • Specific legal tasks (e.g., legal research, document drafting).
    • The date the prompt was created.
  3. True or False: Prompts should be considered static and never refined once created.

    • True
    • False
  4. Which of the following is an example of a future trend in legal AI?

    • A decrease in the use of LLMs in law.
    • More specialized legal LLMs and agentic AI.
    • A complete replacement of human lawyers by AI.
    • A reduction in the importance of prompt engineering.

Answer key

  1. b
  2. c
  3. b
  4. b