Documentation Index
Fetch the complete documentation index at: https://docs.pincites.com/llms.txt
Use this file to discover all available pages before exploring further.
Negative prompting means explicitly telling the AI what you don’t want. Instead of just saying what to do, you also specify what to avoid. This technique prevents common mistakes and keeps the AI focused on what matters.
Why Negative Prompting Works
AI models try to be helpful and comprehensive, which sometimes means they do too much. By setting clear boundaries about what not to include, you get:
- More focused results without irrelevant additions
- Protection against common AI tendencies (like over-editing)
- Cleaner output that matches your actual needs
- Consistency across multiple reviews
Common Negative Prompts for Legal Work
Scope Control
Tell the AI what areas to ignore completely:
Do NOT review or change:
- Payment terms
- Defined terms
- Signature blocks
- Exhibit references
Style Preservation
Prevent unnecessary cosmetic changes:
Do NOT make stylistic changes such as:
- Reformatting paragraphs
- Changing capitalization
- Adjusting punctuation unless grammatically incorrect
- Revising language that's already clear
Edit Restraint
Control how aggressive the AI is with changes:
Do NOT:
- Delete entire sections
- Add new obligations for the counterparty
- Change the fundamental deal structure
- Suggest more than 5 material changes
Output Control
Prevent unwanted formats or information:
Do NOT:
- Include legal citations or case law
- Provide historical context
- Explain basic legal concepts
- Add commentary about negotiation strategy
Advanced Negative Prompting Techniques
The Boundary Setting Approach
Define clear boundaries for complex reviews:
Review this agreement but do NOT:
- Flag issues below $10,000 in potential impact
- Suggest changes to industry-standard language
- Modify provisions that match our template
- Comment on terms already marked as "Agreed"
The Focus Technique
Use negatives to narrow attention:
Analyze liability provisions but do NOT:
- Consider standard limitations of liability
- Review mutual indemnification (only one-sided)
- Include insurance requirements (separate review)
The Assumption Preventer
Stop the AI from filling in gaps with assumptions:
If information is missing, do NOT:
- Assume industry standards apply
- Infer party intentions
- Create placeholder language
Simply note what's missing and move on
When to Use Negative Prompting
Always Useful For:
- Template Protection: When certain language must remain unchanged
- Scope Management: When you need focused review of specific issues
- Counterparty Sensitivity: When you know certain changes won’t be accepted
- Final Reviews: When you just need specific fixes, not comprehensive edits
Especially Important For:
- Low-Leverage Negotiations: Prevent aggressive changes you can’t support
- Regulated Language: Protect required compliance language from modification
- Precedent Documents: Maintain established terms that set company standards
- Quick Turnarounds: Focus only on what truly needs attention
Combining Negative with Positive Prompts
The most effective prompts combine what to do with what not to do:
DO: Flag uncapped liability exposure
DO NOT: Suggest specific cap amounts (we'll handle internally)
DO: Identify missing data protection terms
DO NOT: Draft new terms (we have standard language)
DO: Check notice provisions for completeness
DO NOT: Change the notice addresses or methods
Common Mistakes with Negative Prompting
-
Being Too Restrictive If you say “don’t” to everything, the AI won’t know what it should do. Balance negatives with clear positive instructions.
-
Contradictory Instructions Don’t say “review all terms” then “don’t review payment terms.” Be consistent.
-
Vague Negatives “Don’t make unnecessary changes” is too subjective. Be specific about what counts as unnecessary.
-
Forgetting Context Negative prompts still need context. “Don’t change indemnity” means nothing without knowing your role and the document type.
Examples in Practice
For Contract Review:
Review this MSA for vendor risks but do NOT:
- Suggest changes to payment terms (already negotiated)
- Modify any terms marked with [AGREED]
- Add new sections or exhibits
- Change defined terms
For Redlining:
Redline problematic provisions but do NOT:
- Delete anything (use strikethrough)
- Add more than one paragraph of new text per issue
- Touch any provisions that reference other agreements
For Analysis:
Analyze compliance risks but do NOT:
- Include risks below "medium" severity
- Reference laws outside our jurisdiction
- Suggest operational changes (legal only)
Remember
AI models try to be thorough and helpful, which sometimes means they do too much. Negative prompting keeps the AI focused by setting clear boundaries — like the difference between “review everything” and “review these three issues and ignore everything else.” By clearly stating what not to do, you free the AI to excel at what you actually need done.
