Block 5: Architecture

16:45 - 18:00 75 minutes 2 Quests

🎯 Learning Goals

เมื่อจบบล็อกนี้ คุณจะ:

ออกแบบ AI-powered system architecture
สร้าง RAG (Retrieval-Augmented Generation) system
บันทึก architectural decisions

📖 Concept: System Architecture (30 min)

What is System Architecture?

System Architecture คือการออกแบบโครงสร้างของระบบ รวมถึง:

Components: ส่วนประกอบของระบบ
Interfaces: การเชื่อมต่อระหว่างส่วนประกอบ
Data Flow: การไหลของข้อมูล
Security: การป้องกันระบบ

AI-Powered System Patterns

Pattern 1: RAG (Retrieval-Augmented Generation)

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│  Documents  │────▶│  Embeddings │────▶│ Vector Store│
└─────────────┘     └─────────────┘     └──────┬──────┘
                                               │
┌─────────────┐     ┌─────────────┐           │
│   Query     │────▶│  Embeddings │───────────┘
└─────────────┘     └──────┬──────┘
                           │
                           ▼
                    ┌─────────────┐
                    │     LLM     │
                    └──────┬──────┘
                           │
                           ▼
                    ┌─────────────┐
                    │   Answer    │
                    └─────────────┘

Use Cases:

Chat with your documents
Knowledge base Q&A
Document search

Pattern 2: Multi-Agent System

┌──────────┐    ┌──────────┐    ┌──────────┐
│ Planner  │───▶│  Coder   │───▶│ Reviewer │
└──────────┘    └──────────┘    └────┬─────┘
                                     │
                    ┌────────────────┘
                    ▼
              ┌──────────┐
              │  Tester  │
              └──────────┘

Use Cases:

Complex code generation
Automated workflows
Quality assurance

Pattern 3: Event-Driven Architecture

┌─────────┐     ┌─────────┐     ┌─────────┐
│ Event   │────▶│ Handler │────▶│ Side    │
│ Source  │     │         │     │ Effects │
└─────────┘     └─────────┘     └─────────┘

Use Cases:

Microservices
Real-time systems
Scalable applications

🛠️ Architecture Documentation

Architecture Decision Records (ADR)

บันทึกการตัดสินใจทางสถาปัตยกรรม:

# ADR-001: [Decision Title]

## Status
Accepted

## Context
[สถานการณ์ที่ต้องตัดสินใจ]

## Decision
[สิ่งที่ตัดสินใจ]

## Consequences
- [ผลบวก]
- [ผลลบ]

System Design Document

# System Design: [System Name]

## Overview
- Purpose
- Users
- Key Features

## Architecture
- Components
- Interfaces
- Data Flow

## Security
- Authentication
- Authorization
- Encryption

## Deployment
- Infrastructure
- CI/CD
- Monitoring

🎮 Code Quests

🟡 Quest 5.1: RAG Design

Goal: Design a Retrieval-Augmented Generation system

Understand RAG components
- Document Store: เก็บเอกสาร
- Embedding Service: แปลงข้อความเป็น vector
- Vector Store: เก็บ embeddings
- LLM: สร้างคำตอบ

Design the system

class RAGPipeline {
  constructor(documentStore, embeddingService) {}
  async retrieve(query) {}
  async generate(query, context) {}
  async query(question) {}
}

Implement core components
Test with sample documents

Deliverable: Working RAG pipeline

🔴 Quest 5.2: Full System Design

Goal: Design a complete AI-powered system

Choose a system: Chatbot, Code Reviewer, or Content Generator
Define components

Component Purpose

Input Handler Process user input

AI Engine Generate responses

Data Store Persist data

Output Formatter Format responses

Component	Purpose
Input Handler	Process user input
AI Engine	Generate responses
Data Store	Persist data
Output Formatter	Format responses

Design interfaces

class AISystem {
  addComponent(name, component) {}
  async process(input) {}
  getStatus() {}
  toDocumentation() {}
}

Document architecture
- Overview
- Components
- Data Flow
- Security

Deliverable: Complete system design with documentation

✅ Block 5 Checklist

☐ Understand AI architecture patterns
☐ Quest 5.1 completed
☐ Quest 5.2 completed

🎉 Workshop Complete!

Congratulations! You've completed all 5 blocks:

✅ Block 1: AI Tools Setup
✅ Block 2: Prompt Engineering
✅ Block 3: Security
✅ Block 4: Agentic Workflows
✅ Block 5: Architecture

What You've Learned

Setting up and using AI coding tools
Writing effective prompts
Identifying and fixing security vulnerabilities
Creating automated development loops
Designing AI-powered systems

Next Steps

Apply: Use these skills in your real projects
Share: Teach others what you've learned
Iterate: Continuously improve your workflow

View All Code Quests →