Tutorial 12: Practice Area Deep Dives for Legal Professionals (OpenAI)
Master ChatGPT's capabilities across M&A, real estate, banking, employment, and IP practice areas with specialized prompting techniques
Practice Area Deep Dives for Legal Professionals
What You Will Complete Today
This tutorial shows you how to use ChatGPT for M&A, real estate, banking, employment, and IP work. You will follow one clear workflow per practice area—no platform switching in the main steps.
Primary workflow (ChatGPT): Use domain-specific prompts and checklist templates per practice area. Escalate high-risk findings with explicit review triggers.
Intermediate Level
Basic ChatGPT experience required | Time: 75 minutes
Learning Objectives
By the end of this tutorial, you will:
- Master ChatGPT's capabilities in M&A/Private Equity document analysis
- Develop expertise in real estate transaction document review
- Understand banking and finance agreement analysis workflows
- Apply ChatGPT to employment law matters efficiently
- Navigate intellectual property assessment and portfolio analysis
Part 1: M&A/Private Equity Deep Dive
Understanding M&A Document Complexity
M&A transactions involve multiple interconnected documents. ChatGPT excels at this complexity:
| Document Type | Analysis Challenge | ChatGPT's Strength |
|---|---|---|
| Share Purchase Agreement (SPA) | Warranties/conditions/covenants layers | Extracts all provisions systematically |
| Limited Partnership Agreement (LPA) | Fee structures across tiers | Creates comparison tables automatically |
| Due Diligence Reports | Volume of documents (500+) | Summarizes key risks across all docs |
| Term Sheets | Multiple conditions precedent | Maps contingencies and interdependencies |
Exercise 1: Share Purchase Agreement (SPA) Analysis
Scenario: Your client is acquiring a tech startup. You've received a 50-page SPA and need to assess warranty and indemnification provisions.
Prompt Template:
Always Specify Perspective
Specify whether you represent BUYER or SELLER early in the prompt to get tailored risk analysis.
Exercise 2: Limited Partnership Agreement (LPA) Review
Scenario: Your fund is investing in a new fund. You need to understand fee structures and distribution waterfall.
Prompt:
Exercise 3: Due Diligence Document Compilation
Scenario: Managing a 450-document data room for acquisition due diligence.
Workflow:
ChatGPT vs. Harvey vs. Legora for M&A
| Capability | ChatGPT | Harvey | Legora |
|---|---|---|---|
| SPA Analysis | Customizable criteria | Template-based | Not focused |
| LPA Economics | Waterfall visualization | Limited | Good for comparisons |
| Bulk DD Review | 450+ docs, custom priorities | Structured workflow | Tabular extraction |
| Cost model | Usage-based (verify current pricing) | Vendor quote-based | Vendor quote-based |
| Customization | Complete | Moderate | Moderate |
| Speed (450 docs) | Depends on workflow/QC and document quality | Depends on workflow/QC and document quality | Depends on workflow/QC and document quality |
Part 2: Real Estate Transactions
Exercise 4: Commercial Lease Analysis & Abstraction
Scenario: Your client is the landlord reviewing a 40-page triple-net lease. You need to extract operative terms.
Comprehensive Prompt:
Exercise 5: Title and Survey Review
Scenario: Real estate closing tomorrow. Reviewing title commitment and survey.
Prompt:
Real Estate Comparison: ChatGPT vs. Competitors
| Task | ChatGPT | Legora | iManage RE |
|---|---|---|---|
| Lease abstraction | Full-featured | Not designed | Automated |
| Title review | Risk identification | No capability | No capability |
| Multi-document comparison | Portfolio view | Portfolio view | Full suite |
| Cost model | Usage-based (verify current pricing) | Vendor quote-based | Vendor quote-based |
| Custom criteria | Full | Limited | Limited |
Request Year 10 Projections
For rent escalation clauses, ask ChatGPT to calculate Year 10 rent to visualize long-term impact.
Part 3: Banking & Finance Agreements
Exercise 6: Facility Agreement Analysis
Scenario: Your client is borrowing $50M. You need to understand the credit agreement structure.
Prompt:
Verify Rate Calculations
For SOFR/LIBOR rates, ask ChatGPT to show the formula step-by-step and verify independently.
Exercise 7: ISDA Master Agreement Review
Scenario: Your client is a financial institution executing derivatives. Reviewing ISDA for counterparty.
Prompt:
Part 4: Employment Law
Exercise 8: Dismissal and Discrimination Claims Analysis
Scenario: Your client company received notice of an employment discrimination claim. Assess exposure.
Prompt:
Provide Comparator Lists Upfront
Include a list of comparable employees with demographics to get accurate comparator analysis.
Exercise 9: Employment Contract Review
Scenario: Executive hire. Review offer letter and employment agreement.
Prompt:
Exercise 10: Non-Compete Enforceability Assessment
Scenario: Your company wants to enforce a non-compete. Assess likelihood of success.
Prompt:
Part 5: Intellectual Property
Exercise 11: Patent Application Review
Scenario: Technical team developed new software process. Assess patentability before application.
Prompt:
Verify Prior Art Searches
Request USPTO prior art search results before relying on patentability analysis.
Exercise 12: Trademark Analysis
Scenario: Company wants to protect brand. Analyze registration options and risks.
Prompt:
Exercise 13: IP Portfolio Assessment
Scenario: Company acquired by PE firm. Assess IP value and gaps.
Prompt:
Part 6: Quality Control & Best Practices
The Practice Area Verification Framework
PACE Checklist for each practice area deep dive:
- P - Provision Accuracy: Verify ChatGPT referenced actual contract language
- A - Assumption Check: Confirm jurisdictional law assumptions (state, country, industry)
- C - Comparator Validation: For employment/discrimination, verify you identified true comparators
- E - Economic Analysis: For finance/M&A, verify math on waterfall calculations
Common Errors by Practice Area
| Practice Area | Common Error | Prevention |
|---|---|---|
| M&A | Misunderstood warranty basket mechanism | Request specific section references |
| Real Estate | Missed ground lease implications | Ask "Are there any ground leases?" |
| Banking | Wrong SOFR/LIBOR rate calculation | Verify rate formulas with ChatGPT |
| Employment | Insufficient comparator analysis | Require names and detailed comparison |
| IP | Patentability overconfidence | Require USPTO search results verification |
Quality Control Template
Red Flag Triggers
Any risk marked HIGH requires attorney review before action. Any numerical analysis should be recalculated independently. Any citation to specific case law must be Shepardized/KeyCited before relying on it.
Part 7: Practice-Area Specific Prompting Tips
M&A Specific
- Always specify BUYER or SELLER perspective
- Request side-by-side market comparison tables
- Ask for waterfall visualizations (easier to verify than text)
- Request specific survival periods and baskets in dollar amounts, not percentages
Real Estate Specific
- Specify tenant/landlord perspective early
- Request lease abstracts in consistent format for portfolio analysis
- For rent escalation, ask ChatGPT to calculate Year 10 rent
- Request specific state law analysis for enforceability
Banking Specific
- Request step-by-step covenant calculation examples
- For SOFR/LIBOR, ask ChatGPT to show rate formula
- Request comparison to syndicated loan market data (Loan Pricing Corporation)
- Specify bilateral vs. unilateral for termination provisions
Employment Specific
- Provide comparable employee list upfront
- Ask for specific state law analysis (non-compete rules vary widely)
- Request draft demand letter/response
- Ask for detailed investigation checklist
IP Specific
- Request USPTO prior art search before patentability analysis
- Ask ChatGPT to draft claim language, not just assess
- For trademark, request clearance search results review
- Request cost-benefit analysis for enforcement
Do This Now
- Complete one SPA or LPA analysis using the prompt templates
- Run one lease abstraction or title review for real estate
- Analyze one credit facility or ISDA using the banking prompts
- Apply the employment discrimination or non-compete assessment template
- Run one patent or trademark analysis using the IP prompts
- Apply the PACE checklist to verify one output
- Save your practice-area templates for reuse
Homework Before Tutorial 13
- Complete 2 practice-area analyses (pick different practice areas)
- Apply the PACE framework to verify ChatGPT's output
- Create practice-area templates for documents you work with regularly
- Document lessons learned from each analysis
- Update your SOP with ChatGPT integration points
Related family pages
- Claude Practice Areas - Same concepts with Claude
- Core Concepts - Platform-neutral legal workflow model
Sources
- ABA Business Law Section (M&A and Transactions)
- SEC EDGAR Search and Access (public company deal filings)
- American Land Title Association (title/closing industry resources)
- ISDA Legal Documentation Resources
- EEOC: Laws Enforced by EEOC
- USPTO Patent and Trademark Resources
Additional Reading
- Practical Law: Resource Center (practice-area templates)
- FDIC Banker Resource Center
- NIST AI Risk Management Framework