CODITECT Agentic AI Educational Platform

Complete Document Inventory and Content Framework

Version: 1.0
Date: January 2025
Purpose: Framework for deep web site and blogging platform educating CODITECT community on agentic systems
Origin: Clinical dialogue research (Zhi et al. 2025) abstracted to general-purpose applications

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Executive Summary

This inventory catalogs 39 artifacts produced from comprehensive research on agentic AI paradigms. While the foundational research focused on clinical dialogue systems, the architectural patterns, workflows, and design principles transfer directly to enterprise automation, research synthesis, financial services, legal compliance, and any domain requiring autonomous AI systems.

Key Insight: Healthcare's extreme regulatory and safety constraints produced the most rigorous agentic architectures available. These battle-tested patterns provide CODITECT with a competitive advantage when implementing enterprise automation.

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Document Categories

Category	Count	Purpose
Strategic Analysis	6	Executive and technical deep-dives
Interactive Visualizations	6	React-based educational components
Research References	1	Academic grounding and citations
C4 Architecture Diagrams	5	System architecture at multiple levels
Workflow Diagrams	5	Paradigm-specific execution flows
Dataflow Diagrams	6	System component interactions
Supporting Diagrams	4	Comparisons, sequences, states, decisions
Total	39	Complete educational framework

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Part 1: Strategic Analysis Documents

Core Documentation Suite

#	Document	File	Description	Purpose	Target Audience
01	Executive Summary	01-executive-summary.md	High-level overview of the four agentic paradigms (LSR, GS, EP, VE) with key findings, strategic implications, and implementation priorities	C-suite and decision-maker briefing on agentic AI landscape	Executives, Product Leaders, Investors
02	Four Paradigms Deep Dive	02-four-paradigms-deep-dive.md	Comprehensive analysis of each paradigm including knowledge sources, agency objectives, planning strategies, iteration mechanisms, risk profiles, and use cases	Technical understanding of paradigm selection and trade-offs	Architects, Technical Leads, Senior Engineers
03	Technical Components Reference	03-technical-components-reference.md	Detailed breakdown of five core components (Planning, Memory, Action, Collaboration, Evolution) with implementation patterns per paradigm	Engineering reference for building agentic systems	Engineers, DevOps, Platform Teams
04	CODITECT Impact Analysis	04-coditect-impact-analysis.md	Strategic assessment of how each paradigm maps to CODITECT's work automation platform, including positioning opportunities and competitive differentiation	Product strategy and roadmap planning	Product Management, Strategy, Sales Enablement
05	General-Purpose Agentic Designs	05-general-purpose-agentic-designs.md	Abstraction of clinical patterns to enterprise, research, financial, and legal domains with concrete implementation guidance	Cross-industry application of agentic patterns	Solutions Architects, Consultants, Partners
06	Quick Reference Card	06-quick-reference-card.md	One-page decision matrix for paradigm selection based on auditability, action requirements, process definition, and risk tolerance	Rapid paradigm selection during design sessions	All Technical Roles

Document Specifications

Document	Word Count	Reading Time	Complexity	Update Frequency
Executive Summary	~2,500	10 min	Low	Quarterly
Four Paradigms Deep Dive	~8,000	30 min	High	Semi-annually
Technical Components Reference	~6,000	25 min	High	Monthly
CODITECT Impact Analysis	~4,000	15 min	Medium	Quarterly
General-Purpose Designs	~5,000	20 min	Medium	Semi-annually
Quick Reference Card	~800	3 min	Low	As needed

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Part 2: Interactive Visualizations (JSX)

React Component Library

#	Visualization	File	Description	Purpose	Interactive Features
07	Paradigm Taxonomy	07-paradigm-taxonomy-visual.jsx	Two-axis taxonomy visualization (Knowledge Source × Agency Objective) with four quadrants representing LSR, GS, EP, VE paradigms	Visual understanding of paradigm positioning and trade-offs	Hover states, expandable details, trade-off explanations, research citations
08	Technical Components	08-technical-components-visual.jsx	Five-component architecture explorer (Planning, Memory, Action, Collaboration, Evolution) with paradigm-specific implementations	Component-level understanding of agentic systems	Component selector, paradigm filter, comparison tables, integration flow diagram
09	Domain Abstraction	09-domain-abstraction-visual.jsx	Multi-layer abstraction flow from clinical origins through abstract principles to enterprise and research applications	Understanding cross-domain transfer patterns	Layer navigation, concept mapping table, transfer pattern matrix, real-world examples
10	Multi-Agent Collaboration	10-multi-agent-collaboration-visual.jsx	Five topology patterns (Single, Hierarchical, Distributed, Pipeline, Hybrid) with coordination mechanisms and failure modes	Multi-agent system design and topology selection	Topology selector, visual diagrams, pros/cons comparison, failure mode table
11	Evolution Mechanisms	11-evolution-mechanisms-visual.jsx	Five evolution approaches (Reflexion, Continual Learning, Meta-Learning, Workflow Tuning, Agentic Memory) with timeline and comparisons	Understanding agent learning and adaptation	Timeline visualization, mechanism selector, flow diagrams, paradigm integration mapping
12	Decision Framework	12-decision-framework-visual.jsx	Interactive decision tree for paradigm selection based on four key questions with research-grounded recommendations	Guided paradigm selection for specific use cases	Decision tree navigation, confidence scores, component recommendations, quick reference grid

Visualization Specifications

Visualization	Components	State Variables	Research Sources	Tailwind Classes
Paradigm Taxonomy	4 quadrants	hoveredQuadrant, selectedParadigm, showDetails	Zhi 2025, Ali & Dornaika 2025	~150
Technical Components	5 components × 4 paradigms	selectedComponent, selectedParadigm, showComparison	Yao 2024, ACM TOIS 2025	~200
Domain Abstraction	4 layers × 6 concepts	activeLayer, selectedConcept, showMapping	Zhi 2025, Stanford 2024	~180
Multi-Agent Collaboration	5 topologies	selectedTopology, showMechanisms, showFailures	Tran 2025, MAR 2024	~220
Evolution Mechanisms	5 mechanisms	selectedMechanism, timelineView, showComparison	Shinn 2023, A-Mem 2025	~200
Decision Framework	4-question tree	currentQuestion, answers, recommendation	Multiple surveys	~160

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Part 3: Research References

#	Document	File	Description	Purpose	Citation Count
13	Research References	13-research-references.md	Comprehensive bibliography of 40+ primary sources organized by category (surveys, planning, memory, multi-agent, tools, enterprise, evaluation, safety)	Academic grounding and further reading	400+ papers referenced

Reference Categories

Category	Source Count	Key Papers	Relevance
Foundational Surveys	3	Zhi 2025, Ali & Dornaika 2025, MDPI 2025	Core taxonomy and paradigm definitions
Planning Mechanisms	5	ReAct, Reflexion, MAR, ToT, Focused ReAct	Strategic planning implementation
Memory Systems	5	ACM TOIS survey, A-Mem, MemRL, Agent Workflow Memory	Memory architecture design
Multi-Agent Systems	5	Tran 2025, MetaGPT, AutoAgents, ReConcile	Collaboration topology selection
Tool Integration	4	Stanford framework, τ-bench, ChemCrow, Toolformer	Tool system design
Enterprise Applications	4	IBM 2025, MCP, Production metrics	Real-world deployment
Evaluation Benchmarks	4	SWE-bench, GAIA, HumanEval, AgentBench	Quality assurance
Safety and Governance	3	Governance models, Security challenges	Risk management

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Part 4: C4 Architecture Diagrams

System Architecture at Four Levels

#	Diagram	File	C4 Level	Description	Purpose	Key Elements
C4-01	Context Diagram	c4-01-context-agentic-system.mermaid	Level 4 (Context)	System boundary showing users (End User, Administrator, Developer) and external systems (Knowledge Bases, Enterprise Systems, LLM Providers, Monitoring)	Understanding system scope and external dependencies	3 user types, 4 external system categories, bidirectional data flows
C4-02	Container Diagram	c4-02-container-agentic-platform.mermaid	Level 3 (Container)	Major deployable units including API Gateway, Agent Orchestrator, Planning Engine, four paradigm runtimes, Memory Layer, and Action Layer	High-level technical architecture decisions	12 containers, 4 paradigm implementations, memory tiers, tool integration
C4-03	Component Diagram	c4-03-component-agent-runtime.mermaid	Level 2 (Component)	Agent runtime internals showing paradigm selector, planning components (CoT, ToT, QDG, CM, PM), iteration components, and execution components	Detailed design of agent core	15 components, paradigm-specific routing, iteration loops
C4-04	Code Diagram	c4-04-code-agent-classes.mermaid	Level 1 (Code)	Class structure showing Agent interface, four paradigm implementations, PlanningEngine, MemoryManager, ToolManager, and Orchestrator	Implementation blueprint for developers	10 classes, inheritance hierarchy, dependency relationships
C4-05	Hybrid Architecture	c4-05-hybrid-architecture.mermaid	Component (Hybrid)	Multi-paradigm routing architecture with intelligent routing layer, parallel paradigm execution, coordination layer, and quality assurance	Production hybrid system design	Risk assessment, audit checking, conflict resolution, compliance verification

C4 Diagram Specifications

Diagram	Nodes	Edges	Subgraphs	Styling	GitHub Compatible
Context	8	9	3	5 colors	✓
Container	15	24	6	12 colors	✓
Component	16	22	5	13 colors	✓
Code	10	18	0 (classDiagram)	N/A	✓
Hybrid	24	32	7	18 colors	✓

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Part 5: Workflow Diagrams

Paradigm-Specific Execution Flows

#	Diagram	File	Paradigm	Description	Purpose	Key Phases
WF-01	LSR Chain-of-Thought	workflow-01-lsr-chain-of-thought.mermaid	Latent Space Reasoner	Creative synthesis workflow with multiple reasoning paths and self-consistency voting	Understanding zero-shot creative reasoning	Input → Planning → Reasoning (3 paths) → Aggregation → Output
WF-02	GS Evidence Chain	workflow-02-gs-evidence-chain.mermaid	Grounded Synthesizer	Evidence-based synthesis with query decomposition, multi-source retrieval, validation, and gap-filling iteration	Understanding grounded knowledge retrieval	Decomposition → Retrieval → Validation → Synthesis → Iteration
WF-03	EP Reflexion Loop	workflow-03-ep-reflexion.mermaid	Emergent Planner	Autonomous planning with cognitive mapping, tree-of-thought exploration, execution loop, and self-reflection	Understanding adaptive autonomous planning	Cognitive Mapping → Planning → Execution → Reflexion → Memory
WF-04	VE Protocol Execution	workflow-04-ve-protocol-execution.mermaid	Verifiable Executor	Protocol-driven execution with state management, error handling, and audit logging	Understanding compliant workflow automation	Protocol Matching → State Management → Execution → Audit
WF-05	Enterprise Automation	workflow-05-enterprise-automation.mermaid	VWA Pattern	Complete enterprise workflow with multiple triggers, workflow routing, integrations, approvals, and monitoring	Enterprise process automation design	Trigger → Intake → Workflow Engine → Integrations → Approvals → Monitoring

Workflow Diagram Specifications

Diagram	Nodes	Decision Points	Loops	Error Paths	SLA Points
LSR CoT	11	0	0	0	0
GS Evidence	18	1	1 (gap-fill)	0	0
EP Reflexion	18	3	2 (exec, reflect)	1	0
VE Protocol	20	5	1 (retry)	3	0
Enterprise	27	4	0	2	3

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Part 6: Dataflow Diagrams

System Component Interactions

#	Diagram	File	System	Description	Purpose	Data Types
DF-01	Memory System	dataflow-01-memory-system.mermaid	Memory Architecture	Multi-layer memory with parametric, short-term, long-term, and audit layers, plus retrieval system	Memory system design and implementation	Conversations, tool results, reflections, observations → encoded memories
DF-02	Hierarchical Multi-Agent	dataflow-02-multi-agent-hierarchical.mermaid	Multi-Agent (Hierarchical)	Orchestrator-led delegation to specialist teams (Research, Analysis, Execution) with shared communication	Hierarchical team coordination design	Tasks → sub-tasks → results → aggregated response
DF-03	Distributed Debate	dataflow-03-multi-agent-debate.mermaid	Multi-Agent (Distributed)	Peer-to-peer debate with initial positions, critique rounds, revision, and consensus building	Distributed reasoning and consensus	Positions → critiques → revised positions → votes → consensus
DF-04	Tool Execution	dataflow-04-tool-execution.mermaid	Action System	Tool orchestration with registry, validation, sandboxing, categorized tools, and result processing	Tool system architecture	Action plans → tool requests → sandboxed execution → validated results
DF-05	Evolution and Learning	dataflow-05-evolution-learning.mermaid	Evolution System	Agent learning from experience through reflexion, strategy evolution, workflow evolution, and meta-learning	Continuous improvement design	Outcomes, feedback → insights → updated policies, protocols, heuristics
DF-06	Domain Abstraction	dataflow-06-domain-abstraction.mermaid	Cross-Domain	Transfer from clinical domain through abstract principles to enterprise and research applications	Cross-industry pattern transfer	Clinical concepts → abstract principles → domain-specific implementations

Dataflow Diagram Specifications

Diagram	Source Types	Transform Steps	Storage Types	Output Types
Memory	4	3 (encode, index, link)	4 layers	3 (context, citations, history)
Hierarchical	1	5 (decompose, route, execute, collect, merge)	3 (message bus, shared memory, event queue)	1
Distributed	1	4 rounds (position, critique, revise, vote)	0	3 (consensus, confidence, dissent)
Tool Execution	1	6 (select, validate, schedule, sandbox, execute, transform)	3 tool categories	2 (result, log)
Evolution	4	7 (analyze, extract, reflect, update, optimize, test, generalize)	3 memory types	3 (policies, protocols, heuristics)
Domain Abstraction	6 clinical concepts	1 (POMDP formalization)	0	12 (6 per domain)

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Part 7: Supporting Diagrams

Comparison, Sequence, State, and Decision Diagrams

#	Diagram	File	Type	Description	Purpose	Key Insights
CMP-01	RAG vs Agentic	comparison-01-rag-vs-agentic.mermaid	Comparison Flowchart	Side-by-side architecture comparison showing RAG's linear flow vs Agentic's modular, iterative approach	Understanding when to upgrade from RAG to Agentic	5 key differences: single-pass vs iterative, retrieval-only vs action-capable, stateless vs stateful, fixed vs adaptive, no learning vs continuous evolution
SEQ-01	Agentic Flow	sequence-01-agentic-flow.mermaid	Sequence Diagram	Complete task execution showing interactions between User, Orchestrator, Planner, Memory, Agent, Tool Manager, External System, and Audit Log	Understanding runtime interactions	7 participants, execution loop with success/failure branches, memory updates
STT-01	Agent Lifecycle	state-01-agent-lifecycle.mermaid	State Machine	Agent states (Idle, Planning, Reasoning, ActionSelection, ToolExecution, Observation, StateUpdate, GoalCheck, Reflection, MemoryUpdate, Complete, Error, Recovery, Failed) with transitions	Understanding agent state management	14 states, human escalation path, error recovery loop
DEC-01	Paradigm Selection	decision-01-paradigm-selection.mermaid	Decision Tree	Four-question decision tree for paradigm selection with hybrid recommendations	Rapid paradigm selection	6 questions, 4 pure paradigm endpoints, 2 hybrid recommendations

Supporting Diagram Specifications

Diagram	Mermaid Type	Elements	Decision Points	Educational Value
RAG vs Agentic	flowchart	20 nodes	0	High (common question)
Agentic Flow	sequenceDiagram	7 participants, ~20 messages	2 (success/failure)	High (runtime understanding)
Agent Lifecycle	stateDiagram-v2	14 states	8 transitions	Medium (state machine)
Paradigm Selection	flowchart	14 nodes	6 questions	Very High (decision support)

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Part 8: Cross-Reference Matrix

Document Relationships

Document	Prerequisites	Builds Upon	Leads To
01-Executive Summary	None	None	02-Deep Dive, 04-Impact
02-Four Paradigms	01-Executive	01-Executive	03-Technical, Workflows
03-Technical Components	02-Paradigms	02-Paradigms	Dataflows, C4 Diagrams
04-CODITECT Impact	01-Executive	01, 02	05-General Purpose
05-General Purpose	02-Paradigms	02, 04	All Industry Applications
06-Quick Reference	All above	All	Decision Support
07-12 Visualizations	02-Paradigms	02, 03	Interactive Learning
13-References	None	None	Deep Research
C4 Diagrams	03-Technical	03	Implementation
Workflows	02-Paradigms	02	Process Design
Dataflows	03-Technical	03	System Design

Audience Journey Map

Audience	Entry Point	Core Path	Advanced Topics
Executive	01-Summary → 04-Impact	06-Quick Ref → Decision-01	None
Product Manager	01-Summary → 04-Impact	05-General → Workflows	02-Paradigms
Solutions Architect	02-Paradigms → C4-01,02	03-Technical → All Workflows	Dataflows, C4-03,04,05
Engineer	03-Technical → C4-03,04	Dataflows → Sequence-01	13-References
Data Scientist	02-Paradigms → 07-Taxonomy	11-Evolution → DF-05	13-References
Sales/Marketing	01-Summary → 04-Impact	05-General → Quick Ref	Visualizations

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Part 9: Suggested Additional Documentation

Based on the current research foundation, the following additional documents would strengthen the CODITECT educational platform:

Priority 1: Implementation Guides (High Impact)

#	Suggested Document	Description	Purpose	Estimated Effort
A1	Paradigm Selection Playbook	Step-by-step guide for choosing paradigms based on 20+ use case scenarios with decision matrices and example implementations	Reduce time-to-decision for architects	3-4 days
A2	Memory System Implementation Guide	Detailed technical guide for implementing multi-layer memory with vector stores, knowledge graphs, and audit trails	Enable robust memory architecture	4-5 days
A3	Tool Integration Cookbook	Collection of 15-20 tool integration patterns (API, Database, Document, Compute) with code examples and error handling	Accelerate tool system development	5-6 days
A4	Multi-Agent Orchestration Patterns	Implementation guide for 5 topologies (Single, Hierarchical, Distributed, Pipeline, Hybrid) with Python/TypeScript code	Enable multi-agent deployments	4-5 days
A5	Reflexion and Evolution Playbook	Guide to implementing self-improvement mechanisms including Reflexion, A-Mem, and workflow tuning	Enable learning agents	3-4 days

Priority 2: Industry Vertical Guides (Market Expansion)

#	Suggested Document	Industry	Description	Key Use Cases
B1	Financial Services Agentic Guide	Finance	Paradigm application for trading, compliance, risk, customer service	Compliance automation (VE), Market analysis (GS), Advisory (LSR)
B2	Legal Services Agentic Guide	Legal	Contract analysis, due diligence, compliance monitoring, research	Contract review (GS), Due diligence (EP), Compliance (VE)
B3	Healthcare Operations Guide	Healthcare	Non-clinical applications: scheduling, billing, supply chain, HR	Scheduling (VE), Claims (GS+VE), Supply chain (EP)
B4	Manufacturing Agentic Guide	Manufacturing	Quality control, predictive maintenance, supply chain, safety	Quality (VE), Maintenance (EP), Supply (GS+EP)
B5	Professional Services Guide	Consulting	Research, proposal generation, project management, knowledge management	Research (GS), Proposals (LSR+GS), PM (VE)

Priority 3: Technical Deep Dives (Engineering Excellence)

#	Suggested Document	Topic	Description	Target Audience
C1	LLM Provider Integration Guide	Integration	Patterns for Claude, GPT-4, Llama, Mistral with fallback, load balancing, and cost optimization	Platform Engineers
C2	Observability and Monitoring Guide	Operations	Metrics, traces, logs for agentic systems with alerting and debugging patterns	DevOps, SRE
C3	Security and Governance Framework	Security	Authentication, authorization, audit, compliance for agentic systems	Security Engineers
C4	Performance Optimization Guide	Performance	Latency reduction, throughput optimization, caching strategies	Performance Engineers
C5	Testing Agentic Systems	Quality	Unit, integration, and evaluation testing patterns for agents	QA Engineers

Priority 4: Business and Strategy Documents (Market Positioning)

#	Suggested Document	Topic	Description	Target Audience
D1	ROI Calculator Methodology	Business Case	Framework for calculating agentic AI ROI with industry benchmarks	Sales, Finance
D2	Competitive Landscape Analysis	Strategy	Comparison of agentic platforms (LangChain, AutoGen, CrewAI, etc.)	Product, Strategy
D3	Implementation Roadmap Template	Planning	Phased rollout template from pilot to enterprise scale	Project Managers
D4	Change Management Guide	Adoption	Human factors in agentic AI adoption with training curricula	HR, Training
D5	Case Study Template	Marketing	Standardized format for documenting customer success stories	Marketing, Sales

Priority 5: Interactive Learning Modules (Platform Engagement)

#	Suggested Document	Format	Description	Learning Outcome
E1	Paradigm Selection Simulator	JSX Interactive	Scenario-based learning game for paradigm selection	Confident paradigm selection
E2	Agent Builder Sandbox	JSX + API	Visual agent configuration with live testing	Hands-on agent design
E3	Memory System Visualizer	JSX Interactive	Interactive memory flow demonstration	Memory architecture understanding
E4	Multi-Agent Debugger	JSX + API	Visual debugging tool for agent interactions	Debugging proficiency
E5	Workflow Designer	JSX Interactive	Drag-and-drop workflow builder with export	Workflow design capability

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Part 10: Content Strategy Recommendations

Blog Series Structure

Series	Posts	Cadence	Target Audience
Agentic Fundamentals	8 posts (one per document 01-06, plus intro/summary)	Weekly	General technical audience
Paradigm Deep Dives	4 posts (one per paradigm)	Bi-weekly	Architects, Senior Engineers
Industry Applications	5 posts (one per vertical)	Monthly	Industry practitioners
Technical How-Tos	10 posts (implementation patterns)	Weekly	Engineers
Case Studies	Ongoing	As available	Decision makers

SEO Keyword Targets

Primary Keywords	Secondary Keywords	Long-tail Keywords
Agentic AI	AI agents	How to build AI agents
LLM agents	Autonomous AI	Agentic AI vs RAG
AI automation	Multi-agent systems	Enterprise AI automation
Work automation	AI workflow	AI workflow automation tools
CODITECT	AI orchestration	Best AI orchestration platform

Content Distribution Strategy

Channel	Content Type	Frequency	Goal
Website	Full documents, visualizations	Continuous	Authority
Blog	Adapted articles, tutorials	2-4/week	Traffic
LinkedIn	Insights, infographics	Daily	Awareness
YouTube	Visualization walkthroughs	Weekly	Engagement
GitHub	Code examples, diagrams	Continuous	Developer adoption
Newsletter	Summaries, updates	Weekly	Retention

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Part 11: Technical Requirements

Visualization Hosting Requirements

Requirement	Specification	Notes
React Version	18.x+	Hooks required
Tailwind CSS	3.x	Core utilities only
Mermaid.js	10.x+	GitHub rendering
Build System	Vite or Next.js	For JSX compilation
CDN	Cloudflare or Vercel	For static assets

Documentation Platform Requirements

Requirement	Options	Recommendation
Static Site Generator	Docusaurus, GitBook, Nextra	Docusaurus (React-native)
Search	Algolia, Typesense	Algolia DocSearch
Analytics	Plausible, PostHog	PostHog (product analytics)
Comments	Giscus, Utterances	Giscus (GitHub-based)
Versioning	Git-based	Semantic versioning

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Appendix A: File Manifest

Complete File Listing

/outputs/
├── Strategic Documents (Markdown)
│   ├── 01-executive-summary.md
│   ├── 02-four-paradigms-deep-dive.md
│   ├── 03-technical-components-reference.md
│   ├── 04-coditect-impact-analysis.md
│   ├── 05-general-purpose-agentic-designs.md
│   └── 06-quick-reference-card.md
│
├── Interactive Visualizations (JSX)
│   ├── 07-paradigm-taxonomy-visual.jsx
│   ├── 08-technical-components-visual.jsx
│   ├── 09-domain-abstraction-visual.jsx
│   ├── 10-multi-agent-collaboration-visual.jsx
│   ├── 11-evolution-mechanisms-visual.jsx
│   └── 12-decision-framework-visual.jsx
│
├── Research References
│   └── 13-research-references.md
│
├── C4 Architecture Diagrams (Mermaid)
│   ├── c4-01-context-agentic-system.mermaid
│   ├── c4-02-container-agentic-platform.mermaid
│   ├── c4-03-component-agent-runtime.mermaid
│   ├── c4-04-code-agent-classes.mermaid
│   └── c4-05-hybrid-architecture.mermaid
│
├── Workflow Diagrams (Mermaid)
│   ├── workflow-01-lsr-chain-of-thought.mermaid
│   ├── workflow-02-gs-evidence-chain.mermaid
│   ├── workflow-03-ep-reflexion.mermaid
│   ├── workflow-04-ve-protocol-execution.mermaid
│   └── workflow-05-enterprise-automation.mermaid
│
├── Dataflow Diagrams (Mermaid)
│   ├── dataflow-01-memory-system.mermaid
│   ├── dataflow-02-multi-agent-hierarchical.mermaid
│   ├── dataflow-03-multi-agent-debate.mermaid
│   ├── dataflow-04-tool-execution.mermaid
│   ├── dataflow-05-evolution-learning.mermaid
│   └── dataflow-06-domain-abstraction.mermaid
│
├── Supporting Diagrams (Mermaid)
│   ├── comparison-01-rag-vs-agentic.mermaid
│   ├── sequence-01-agentic-flow.mermaid
│   ├── state-01-agent-lifecycle.mermaid
│   └── decision-01-paradigm-selection.mermaid
│
└── Inventory
    └── 14-document-inventory.md (this document)

Total Artifact Statistics

Metric	Value
Total Files	39
Markdown Documents	7
JSX Visualizations	6
Mermaid Diagrams	20
This Inventory	1
Total Lines of Code	~8,000
Total Words	~35,000
Research Papers Referenced	400+
Primary Sources Cited	40+

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Appendix B: Suggested Implementation Timeline

Phase 1: Foundation (Weeks 1-4)

Week	Deliverables	Resources
1	Deploy existing 39 documents to staging	1 engineer
2	Set up documentation platform (Docusaurus)	1 engineer
3	Integrate visualizations with platform	1 engineer
4	Launch MVP site with core documents	1 engineer, 1 content

Phase 2: Enhancement (Weeks 5-8)

Week	Deliverables	Resources
5	Create A1-A2 (Playbook, Memory Guide)	2 engineers
6	Create A3-A4 (Tool Cookbook, Multi-Agent)	2 engineers
7	Launch blog series (Fundamentals)	1 content
8	Create A5 (Evolution Playbook)	1 engineer

Phase 3: Expansion (Weeks 9-12)

Week	Deliverables	Resources
9	Create B1-B2 (Finance, Legal guides)	2 content
10	Create B3-B4 (Healthcare, Manufacturing)	2 content
11	Create B5 (Professional Services)	1 content
12	Launch industry vertical landing pages	1 engineer, 1 content

Phase 4: Maturity (Weeks 13-16)

Week	Deliverables	Resources
13	Create C1-C2 (Integration, Observability)	2 engineers
14	Create C3-C4 (Security, Performance)	2 engineers
15	Create C5 (Testing)	1 engineer
16	Full platform launch with all content	Full team

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Document generated from agentic AI research analysis. Last updated: January 2025.