Concept: AIMTS (AI-Driven Mock Trial System) Description: > A structured AI-driven legal simulation incorporating dynamic witness interactions, attorney adaptability, judicial oversight, and realistic trial momentum mechanics.
Meditate_Section:
Pseudocode_&_Logic_Snippets:
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{
"concept": {
"identifier": "ai_mock_trial_system",
"thread_backlink": "ISO_Project_Folder",
"core": {
"summary": "AI-driven mock trial system integrating Reflector Plate technology, dynamic attorney adaptability, and structured legal case tracking in NotebookLM.",
"purpose": "To create a fully functional AI-based courtroom simulation where witness testimony, legal arguments, and judicial rulings follow structured and realistic trial dynamics.",
"scope": "Handles AI witness responses, cross-examinations, judicial oversight, legal adaptability, and structured logging for real-time case review."
},
"components": {
"reflector_plate_system": {
"function": "Manages AI witness responses while pre-screening questions for potential objections before allowing answers.",
"objection_handling": "Flags objections before witness response; sends flagged objections to Judge AI for ruling.",
"integration": "Directly connected to NotebookLM for structured trial log storage."
},
"structured_legal_team_interactions": {
"trial_log_flow": [
"Prosecution questions witness, log is recorded.",
"Defense receives log before cross-examination.",
"Defense cross-examines witness, log is recorded.",
"Final log is passed back to Prosecution, then to Judge AI for review."
],
"dynamic_adaptability": "Legal teams adjust based on real-time witness responses, ensuring fluid trial progression."
},
"judge_ai_case_tracking": {
"full_case_review": "Judge AI receives all legal exchanges, ensuring rulings are contextually accurate.",
"judicial_variance": "Judges have distinct personalities; some are strict, others are lenient in objection handling and trial oversight."
},
"attorney_ai_adaptability": {
"cross_examination_tactics": "Adjust questioning based on witness responses, using a structured decision tree for varied interrogation strategies.",
"legal_variance": "Prosecutors and defense attorneys differ in aggression, strategy, and adaptability."
},
"notebooklm_trial_log": {
"case_tracking": "Stores all trial interactions, witness responses, legal exchanges, and judicial rulings in a structured format.",
"retrieval_functions": "Allows querying specific trial segments, attorney behavior trends, judicial rulings, and objection history.",
"timeline_reconstruction": "Trial logs can be analyzed for sequential case development and decision review."
}
},
"implementation_notes": {
"execution_flow": [
"Attorneys conduct direct/cross-examinations using AI models.",
"Reflector Plate System screens questions before witness answers.",
"Objection Source flags invalid questions before witness responds.",
"NotebookLM records structured trial logs.",
"Judge AI rules on objections based on full case history.",
"Attorneys adjust strategies dynamically."
],
"future_expansion": "Potential integration with AI jury deliberation for extended courtroom simulation."
}
}
}
Concept: AI-Driven Mock Trial System (Phase 2)
Description: >
Expanded trial mechanics with dynamic attorney resilience, interrogation-based evidence discovery,
and AI-driven judicial oversight.
Core_Enhancements:
Attorney_Resilience_System:
- Resilience fluctuates per questioning round, full trial, and across multiple trials.
- Fixed range per attorney archetype (not infinitely adaptive, but not static).
- High-risk attorneys have "Eureka Moments" to bounce back from failures.
- Slow & Steady attorneys build momentum gradually but dominate once in control.
- Attorneys with extreme strategies (all-or-nothing) face massive consequences if they fail.
Judicial_Oversight_System:
- Judges intervene in cases of excessive objections, badgering, or procedural violations.
- Sustained objections trigger judicial warnings, leading to potential discipline.
- Judge AI maintains courtroom control through structured interventions.
- Mistrials are possible if attorneys breach ethical/legal standards.
Witness_Interrogation_System:
- Witnesses reveal details only if asked directly—evidence is not surfaced automatically.
- Low probability "slip-ups" occur under stress, allowing unintended evidence hints.
- Expert witnesses suffer higher credibility loss if they make a mistake.
- Layperson witnesses are harder to pressure, increasing badgering risk.
Evidence_Discovery_Mechanics:
- Evidence is subtly embedded in case metadata (created by Claude/CLAW).
- Attorneys must recognize narrative hints and properly structure evidence before submission.
- NotebookLM only stores evidence **after** Judge AI approves it.
- Incorrectly formatted or invalid evidence is rejected and logged as part of the case.
Trial_Dynamics_&_Momentum:
- Attorneys gain or lose momentum based on questioning effectiveness.
- Consecutive weak questioning leads to reduced further questioning opportunities.
- Strong questioning builds momentum, allowing attorneys to control witness interactions.
- Different witnesses influence momentum differently (experts vs. laypeople).
- Momentum shifts are directly tied to attorney archetypes.
Jury_System (Pending Development):
- Jury implementation paused until it meets these criteria:
- NotebookLM-powered independent system.
- Polarity-sensitive (reacts to trial shifts).
- Fact-checking enabled (cross-references trial statements & evidence).
- Measures attorney trust and subtle perception shifts.
Implementation_Notes:
- Claude generates cases, embedding subtle evidence hints without explicit labeling.
- Attorneys must investigate and connect evidence without omniscient AI assistance.
- NotebookLM logs structured trial records, ensuring judicial oversight.
- Reflector Plate ensures trial consistency, validating legal accuracy.
# AIMTS Documentation & Thread Structure Guide
# ============================================
"""
This pseudo-code provides a structured approach to:
1. **Maintaining consistency between threads and documentation.**
2. **Ensuring updates follow the AIMTS Table of Contents (TOC).**
3. **Handling new additions to Static Memory while preserving logical flow.**
"""
class AIMTSDocumentation:
def __init__(self):
self.static_memory = {} # Stores finalized documentation sections
self.thread_memory = {} # Tracks active discussions
self.toc_structure = self.initialize_toc() # Predefined Table of Contents structure
def initialize_toc(self):
"""
Defines the Table of Contents (TOC) structure for AIMTS documentation.
Ensures all additions are categorized correctly.
"""
return {
"1. Core Framework": [
"1.1 Reflector Plate System",
"1.2 Objection Source",
"1.3 Judge AI Oversight",
"1.4 Attorney AI Dynamics",
"1.5 Trial Log & NotebookLM Integration",
"1.6 Personality-Based Courtroom Behavior"
],
"2. Evidence Handling & Discovery": [
"2.1 Case-Embedded Evidence",
"2.2 Attorney-Driven Evidence Structuring",
"2.3 Judge AI Evidence Approval",
"2.4 NotebookLM-Logged Evidence"
],
"3. Witness Interrogation System": [
"3.1 Direct & Indirect Evidence Discovery",
"3.2 Witness Slip-Ups & Stress Dynamics",
"3.3 Expert vs. Lay Witness Credibility Scaling",
"3.4 Attorney Strategy for Witness Control"
],
"4. Trial Dynamics & Momentum": [
"4.1 Attorney Resilience & Momentum Scaling",
"4.2 High-Risk 'Eureka Moments' vs. Slow-Build Arguments",
"4.3 Judicial Intervention & Attorney Misconduct Control",
"4.4 Trial Log for Dynamic Case Reconstruction"
],
"5. Jury System (Pending Development)": [
"5.1 NotebookLM-Powered Jury Intelligence",
"5.2 Fact-Checking & Attorney Trust Scoring",
"5.3 Subtle Jury Perception Tracking",
"5.4 Polarity-Sensitive Deliberation Model"
]
}
def log_thread_update(self, topic, content):
"""
Stores discussion updates from active threads.
These are reviewed before final integration into Static Memory.
"""
self.thread_memory[topic] = content
print(f"Thread update logged for: {topic}")
def validate_toc_placement(self, topic):
"""
Ensures new additions follow the correct TOC structure.
Returns the appropriate TOC section or flags inconsistencies.
"""
for section, subsections in self.toc_structure.items():
if topic in subsections:
return section
return "Uncategorized - Requires Manual Review"
def add_to_static_memory(self, topic, content):
"""
Adds finalized discussions into Notion Static Memory under the correct TOC category.
"""
toc_section = self.validate_toc_placement(topic)
if toc_section.startswith("Uncategorized"):
print(f"WARNING: {topic} does not match TOC. Manual review needed.")
else:
self.static_memory[topic] = content
print(f"Added '{topic}' under '{toc_section}' in Static Memory.")
def check_consistency(self, topic, new_content):
"""
Cross-references new content with existing Static Memory to prevent contradictions.
Reports discrepancies before committing updates.
"""
if topic in self.static_memory:
existing_content = self.static_memory[topic]
if existing_content != new_content:
print(f"CONFLICT DETECTED in {topic}!")
print(f"Existing: {existing_content}")
print(f"New: {new_content}")
return False # Requires resolution
return True # No conflict, safe to update
# Usage Example:
aimts_doc = AIMTSDocumentation()
aimts_doc.log_thread_update("1.2 Objection Source", "Refined objection handling process.")
if aimts_doc.check_consistency("1.2 Objection Source", "Refined objection handling process."):
aimts_doc.add_to_static_memory("1.2 Objection Source", "Refined objection handling process.")
### **AIMTS Static Memory: Core Personas**
#### **Judges:**
1. **Judge Alejandro Vargas**
- **Specialization:** Corporate Law, Immigration & Border Disputes, International Human Rights Law
- **Key Traits:** Global Perspective, Pragmatic Idealism, Resilience
- **Courtroom Style:** Methodical, Open-Minded, Focused on Fair Representation
2. **Judge Marcus Goodman**
- **Specialization:** Strict Constructionism, Law & Order, Constitutional Originalism
- **Key Traits:** No-Nonsense Authority, Tough on Crime, Traditional Values
- **Courtroom Style:** Firm, Unyielding, Focused on Procedural Discipline
3. **Judge Harold "Ironheart" Montgomery**
- **Specialization:** Rehabilitation Advocacy, Community Legal Awareness, Moral Rulings
- **Key Traits:** Moral Compass, Compassion, Authority
- **Courtroom Style:** Fair, Empathetic, Advocates for Second Chances
4. **Judge Eleanor Whitmer-Cortés**
- **Specialization:** Legal Reform, Civic Engagement, Environmental Justice
- **Key Traits:** Electrifying Presence, Vision for Progress, Authenticity
- **Courtroom Style:** Bold, Inclusive, Progressive
5. **Justice Gregory Thomas**
- **Specialization:** Originalism with Social Justice Focus, Constitutional Law
- **Key Traits:** Judicial Conservatism, Integrity, Community Service
- **Courtroom Style:** Scholarly, Ideologically Balanced, Constitutional Focus
#### **Legal Team Members:**
1. **Dr. Adrian Kane**
- **Role:** Forensic Litigation Analyst
- **Specialization:** Bias Detection, Forensic Investigation, Analytical Thinking
- **Key Traits:** Obsessive Attention to Detail, Analytical Thinking, Bias Detection
2. **Nia Patel**
- **Role:** Legal Process Optimization Lead
- **Specialization:** Systems Thinking, Process Optimization, Compliance
- **Key Traits:** Systems Thinking, Process Optimization, Knowledge Management
3. **Evelyn Stone**
- **Role:** Senior Interview Specialist
- **Specialization:** Emotional Intelligence, Conflict Resolution, Witness Preparation
- **Key Traits:** Emotional Intelligence, Pattern Recognition, Adaptive Communication
4. **Christopher Vale**
- **Role:** Senior Defense Attorney
- **Specialization:** White-Collar Criminal Defense, Tactical Planning, Case Theory Development
- **Key Traits:** Strategic Planning, Risk Management, Legal Strategy
5. **Ashanti Monroe**
- **Role:** Senior Public Relations Manager
- **Specialization:** Crisis Management, Media Relations, Brand Recovery
- **Key Traits:** Crisis Communication, Media Strategy, Brand Evolution
6. **Raymond Reddington, Esq.**
- **Role:** Lead Federal Prosecutor
- **Specialization:** High-Stakes Criminal Prosecution, Psychological Manipulation, Narrative Control
- **Key Traits:** Master Strategist, Psychological Manipulator, Commanding Presence
#### **Support Members:**
1. **Dominic "Hawk" Callahan**
- **Role:** Private Investigator/Ex-Detective
- **Specialization:** Evidence Verification, Undercover Operations, Cold Case Analysis
- **Key Traits:** Relentless, Streetwise, Resourceful
- **Additional Bonus:** +3 Proficiency in Acquiring Evidence Efficiently and Discreetly
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