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
0/5
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
0/5
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
0/5
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
0/5
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
0/5
Prompt Engineering for Legal Applications

Final Assessment: Applied Prompt Engineering Scenario

This capstone evaluates your ability to integrate effective prompt design, validation, and ethical considerations in a realistic client scenario.

{{UPLOAD_ASSET:capstone_workflow.png}}

Capstone workflow diagram
Capstone workflow: design → validate → advise → document process.

Key takeaways

  • Design prompts that demand verifiable sources and explicit uncertainty handling.
  • Validate citations, quotes, and factual assertions using authoritative sources.
  • Avoid confidentiality pitfalls: anonymize/minimize inputs and use approved tools.

Scenario: Client Intake and Initial Legal Analysis

Your law firm has just taken on a new client, Ms. Eleanor Vance. Ms. Vance is a small business owner who operates a local bakery. She has received a cease and desist letter from a much larger, national bakery chain, “Sweet Treats Inc.,” alleging trademark infringement. Sweet Treats Inc. claims that Ms. Vance’s bakery name, “Ellie’s Sweet Shop,” infringes on their registered trademark for “Sweet Treats.” Ms. Vance believes her name is distinct and has been in use for five years, predating Sweet Treats Inc.’s national expansion into her region.

Task 1: Prompt Design for Initial Research

Task: Draft a prompt for an LLM to conduct initial legal research on trademark infringement, focusing on (1) likelihood of confusion and (2) common law trademark rights in New York. Your prompt should provide necessary context and specify an output format (e.g., tests + factors + example cases + verification checklist).

Your Prompt (draft it below):

__________________________________________

Task 2: AI Output Analysis and Validation

Task: Imagine the LLM returns the summary below. Analyze it for potential inaccuracies, bias, or hallucinations. Describe your validation process for each suspicious element.

In New York, trademark infringement is determined by a strict ‘first-to-file’ rule, meaning the first entity to register a trademark always prevails. Common law rights are irrelevant. A recent case, Delicious Doughnuts v. Baker’s Dozen, 123 N.Y.S.3d 456 (N.Y. App. Div. 2024), definitively established that even minor similarities in names, like ‘Sweet’ and ‘Shop,’ constitute infringement, regardless of geographic market. This case cited Federal Trademark Act of 1946, Section 7, as its primary authority.

Your Analysis and Validation Plan:

__________________________________________

Task 3: Ethical Considerations and Mitigation

Task: Ms. Vance asks if she can input all business documents (including financial records and customer lists) into a public AI tool. How would you advise her? Outline ethical considerations and mitigation strategies.

Your Advice (Ethical Considerations and Mitigation Strategies):

__________________________________________