Concepts — Overview of Design Philosophy
A bird's-eye view of the "AI Agent Architecture Design Philosophy" across seven chapters.
Document Chain
Chapter Overview
| Ch. | Label | Central Question | Link |
|---|---|---|---|
| 01 | WHY | Why do AI agents need guiding principles? | 01-vision |
| 02 | WHAT | What should be used as reference sources? | 02-reference-sources |
| 03 | HOW | How should the system be structured? | 03-architecture |
| 04 | WHICH | Which pattern should be chosen and when? | 04-ai-design-patterns |
| 05 | REALITY | How do we address real-world constraints? | 05-solving-ai-limitations |
| 06 | EXTENSION | Does the three-layer model hold in the physical world? | 06-physical-ai |
| 07 | DOCTRINE | On what basis should AI judge and act? | 07-doctrine-and-intent |
Layer × Concern Cross-Reference Matrix
Shows which chapters cover which concerns for each layer.
| Concern | Agent Layer | Skills Layer | MCP Layer | Doctrine Layer |
|---|---|---|---|---|
| Structural Definition | 03 | 03 | 03 | 07 |
| Design Patterns | 04 | 04 | 04 | — |
| Constraints & Countermeasures | 05 | 05 | 05 | 05 |
| Edge Extension | 06 | 06 | 06 | 06 |
| Judgment Criteria | 07 | 07 | — | 07 |
| Reference Source Taxonomy | — | 02 | 02 | — |
| Design Philosophy (WHY) | 01 | 01 | 01 | 01 |
Mermaid Diagram Color Legend
The following color codes represent layers consistently across all chapters.
| Layer | Color | Mermaid fill |
|---|---|---|
| Agent Layer | Light Blue | #87CEEB |
| Skills Layer | Light Green | #90EE90 |
| MCP Layer | Pink | #FFB6C1 |
| Doctrine Layer | Light Orange | #FFE4B5 |
Normative Strength Ladder (shall / should / may)
This site's documentation uses normative keywords conforming to RFC 2119.
| Keyword | Strength | Meaning |
|---|---|---|
| MUST / SHALL | Required | An absolute requirement. Violation constitutes a design defect |
| MUST NOT / SHALL NOT | Prohibited | An absolute prohibition |
| SHOULD | Recommended | Deviation only with justified reason |
| SHOULD NOT | Not Recommended | Adoption only with justified reason |
| MAY | Optional | Entirely discretionary |
Constraints within doctrine (07-doctrine-and-intent) and normative requirements extracted from spec MCPs are interpreted according to this strength ladder.
Concepts → Implementation Exit Checklist
A checklist to confirm that your understanding of the Concepts section is sufficient to proceed to the implementation phase.
Minimum Readiness Conditions
- [ ] Reference Sources Minimum Catalog — Have you identified the authoritative sources your project will reference, and prioritized them for MCP integration? (See 02)
- [ ] Three-Layer Separation Understanding — Can you explain the responsibility boundaries of Agent / Skills / MCP, and recognize anti-patterns (layer confusion)? (See 03)
- [ ] Pattern Selection Rationale — Can you justify whether to adopt RAG, MCP, or Fine-tuning, and explain the reasoning? (See 04)
- [ ] Constraint Boundary Awareness — Can you distinguish between constraints solvable by technology (knowledge constraints) and those not solvable by technology alone (institutional constraints)? (See 05)
- [ ] Human Intervention Point Agreement — Has your team agreed on the agent's autonomy level and the conditions for escalation to humans? (See 07)
- [ ] Evidence Trail Minimum Requirements — Does your design include mechanisms for post-hoc verification of AI decisions (verification status, source records)? (See 05)
Once These Are Met
→ Proceed to Development Phases and implement MCP integration at each phase → Refer to the Skills Design Guide and formalize domain knowledge as Skills
Correspondence with AI Research
The conceptual framework of this site corresponds to standard structures in AI agent research as follows.
| Standard AI Research Structure | Corresponding Concept in This Site | Chapter |
|---|---|---|
| Goal | Intent | 07 |
| Policy | Doctrine | 07 |
| Reasoning | Agent Layer (inference & judgment) | 03 |
| Tools / Skills | Skills Layer + MCP Layer | 03 |
| Execution | Tool execution via MCP | 03, 04 |
| Physical Action | Physical AI | 06 |