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Agentic Paradigms Quick Reference Card

The Two Fundamental Trade-offs

TRADE-OFF 1: RELIABILITY ← → CREATIVITY
├── IMPLICIT KNOWLEDGE (Creative)
│ └── Model parameters as source of truth
│ └── Risk: Hallucination
└── EXPLICIT KNOWLEDGE (Reliable)
└── External sources as source of truth
└── Risk: Rigidity

TRADE-OFF 2: SAFETY ← → AUTONOMY
├── EVENT COGNITION (Safe)
│ └── Understand and advise
│ └── Human makes decisions
└── GOAL EXECUTION (Autonomous)
└── Plan and execute
└── Agent takes action

The Four Paradigms at a Glance

ParadigmKnowledgeAgencyOne-Liner
Latent Space Clinician (LSC)ImplicitCognitionCreative synthesis from internal knowledge
Grounded Synthesizer (GS)ExplicitCognitionEvidence-based information synthesis
Emergent Planner (EP)ImplicitExecutionAutonomous multi-step planning
Verifiable Workflow Automator (VWA)ExplicitExecutionProtocol-driven process execution

Five Technical Components

1. Strategic Planning

ComponentLSCGSEPVWA
DecompositionChain-of-thoughtQuery dependency graphCognitive mapsProtocol mapping
IterationSelf-consistencyGap-filling loopsSelf-reflectionClosed-loop correction

2. Memory Management

ComponentLSCGSEPVWA
ParametricKnowledge sourceQuery generatorStrategic engineIntent parser
Non-ParametricContext windowEvidence ledgerWorkflow logState register

3. Action Execution (Explicit paradigms only)

Action TypeGS PurposeVWA Purpose
Knowledge-BasedLogical grounding via KGVerifiable inference via DB
Search-BasedForage-Constrain-AttributeOptimize-Route-Validate
Tool-UseLiability offloadingClinical orchestration

4. Collaboration

TopologyDescriptionBest For
Single-AgentOne model handles allSimple tasks
Dominant (Hierarchical)Central orchestrator delegatesComplex workflows
Distributed (Peer-to-Peer)Agents negotiate consensusAmbiguous decisions

5. Evolution

ParadigmWhat EvolvesHow
LSCModel parametersContinual learning
GSQuery strategiesEfficiency optimization
EPAction policiesRL / meta-learning
VWAWorkflow componentsEvolutionary refinement

Decision Matrix

When to Use Each Paradigm

                          HIGH STAKES?
NO YES
┌─────────────────┬─────────────────┐
│ │ │
NEEDS │ LSC │ GS │
CREATIVITY │ (Creative + │ (Reliable + │
│ Advisory) │ Auditable) │
│ │ │
├─────────────────┼─────────────────┤
│ │ │
NEEDS │ EP │ VWA │
EXECUTION │ (Flexible + │ (Predictable + │
│ Autonomous) │ Compliant) │
│ │ │
└─────────────────┴─────────────────┘

Key Patterns Cheat Sheet

LSC Pattern: Chain-of-Thought + Self-Consistency

Query → Multiple reasoning paths → Vote → Consensus answer

GS Pattern: Decompose + Ground + Cite

Query → Sub-queries → Retrieve evidence → Synthesize with citations

EP Pattern: Plan + Execute + Reflect + Adapt

Goal → Cognitive map → Execute step → Reflect → Adjust plan → Repeat

VWA Pattern: Map + Validate + Execute + Log

Request → Match protocol → Validate preconditions → Execute → Audit trail

Risk Mitigation Quick Reference

RiskLSC MitigationGS MitigationEP MitigationVWA Mitigation
HallucinationHuman validationEvidence firewallReflection checkpointsProtocol constraints
StalenessPeriodic fine-tuningSource updatesPolicy updatesWorkflow versioning
Cascade FailureN/A (advisory)Source diversityRollback capabilityCircuit breakers
ComplianceNot recommendedAudit trailsHuman escalationBuilt-in logging

Enterprise Application Mapping

Use CasePrimary ParadigmSupporting Paradigm
Document GenerationGSLSC (creativity)
Data Entry AutomationVWA-
Customer SupportGSLSC (empathy)
Process AutomationVWAEP (exceptions)
Research SynthesisGSLSC (insights)
Strategic AnalysisLSCGS (grounding)
Compliance ReportingVWAGS (verification)
Exception HandlingEPVWA (escalation)

Memory Architecture Reference

┌─────────────────────────────────────────────────────────────┐
│ MEMORY STACK │
├─────────────────────────────────────────────────────────────┤
│ STATIC LAYER │
│ └── Business rules, protocols, domain knowledge │
├─────────────────────────────────────────────────────────────┤
│ DYNAMIC LAYER │
│ └── Session state, workflow progress, entity tracking │
├─────────────────────────────────────────────────────────────┤
│ AUDIT LAYER │
│ └── Action logs, decision traces, compliance records │
├─────────────────────────────────────────────────────────────┤
│ LEARNING LAYER │
│ └── Pattern cache, optimization data, feedback history │
└─────────────────────────────────────────────────────────────┘

Collaboration Topology Selection

Single Agent ← Choose when →
✓ Task is simple and well-defined
✓ Low complexity
✓ Resource constraints

Dominant Topology ← Choose when →
✓ Clear hierarchy needed
✓ Complex multi-step workflows
✓ Centralized control preferred

Distributed Topology ← Choose when →
✓ Multiple perspectives needed
✓ Ambiguous decisions
✓ Peer review beneficial

Metrics Reference

CategoryKey Metrics
AccuracyCompletion rate, Error rate, Compliance score
EfficiencyLatency, Human touches per task, Cycle time
QualityCitation accuracy, Reasoning validity, User satisfaction
SafetyEscalation rate, Rollback frequency, Audit findings

Implementation Checklist

For Any Paradigm

  • Define clear component boundaries (Planning, Memory, Action, etc.)
  • Implement appropriate memory architecture
  • Establish evolution mechanism
  • Create audit logging
  • Build human escalation paths

For Explicit Paradigms (GS, VWA)

  • Define knowledge sources
  • Implement evidence firewalling
  • Create citation/attribution system
  • Validate source freshness

For Execution Paradigms (EP, VWA)

  • Define rollback mechanisms
  • Implement circuit breakers
  • Create state persistence
  • Build monitoring dashboards

Source Reference

Paper: "Reinventing Clinical Dialogue: Agentic Paradigms for LLM-Enabled Healthcare Communication"
Authors: Zhi, Zhao, Wu, Zhao, Zhu (Tianjin University, Chinese Academy of Sciences)
Scope: 300+ papers surveyed | Dec 2025
Primary Contribution: Two-axis taxonomy for agentic systems (Knowledge Source × Agency Objective)