AI with Alex's Blog

Building AI Agents: From Context to Memory

Posted on 2026-06-10 Edited on 2026-07-23 In AI , AI Agent
Symbols count in article: 35k Reading time ≈ 32 mins.

• Introduction
• What Is an AI Agent
  • The Core Formula: LLM + Context + Tools
  • The ReAct Loop: How Agents Actually Work
• Context Engineering: The Ceiling of Agent Capability
  • Context at the API Level: Static Prefix + Dynamic Trajectory
  • KV Cache: Why Prefix Stability Matters
  • Prompt Engineering: Writing the Agent’s Operating Manual
  • Agent Skills: Load Knowledge On Demand
  • Agent Status Bar: From Implicit State to Explicit Knowledge
  • Context Compression: When Less Is More
• From Context to Memory: Making Agents Remember
  • User Memory: Building a Model of the User
  • Four Storage Formats: From Simple Notes to Advanced JSON Cards
  • RAG: Giving Agents a Knowledge Base
  • Beyond Flat Text: Structured Indexing and Agentic RAG
  • Contextual Retrieval: Fixing Chunking at the Root
  • The Two-Tier Memory Architecture
• Harness Engineering: Reliability Beyond the Demo
  • Constrain, Verify, Correct: The Three Safety Layers
  • Workflow vs. Autonomous: Choosing the Right Pattern
• Best Practices
• FAQ
• Summary

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LangChain Runtime & Middleware: Core Principles and Practical Guide

Posted on 2026-05-18 Edited on 2026-06-03 In Python , AI
Symbols count in article: 29k Reading time ≈ 26 mins.

• Introduction
• What
  • What is Runtime?
  • What is Middleware?
• Why
  • Why Runtime Matters
  • Why Middleware Matters
• How
  • Runtime Deep Dive
    • State — Short-term Memory
    • Store — Long-term Memory
    • Context — Runtime Context
  • Middleware Deep Dive
    • Prebuilt Middleware
      • PIIMiddleware
      • ModelFallbackMiddleware
      • HumanInTheLoopMiddleware
      • Approve, Reject, Edit
    • Custom Middleware
      • Node-style Hooks
      • Wrap-style Hooks
      • Class-based Middleware

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A Multimodal AI Agent Application: AI Private Chef

Posted on 2026-05-11 Edited on 2026-06-10 In Python , AI
Symbols count in article: 26k Reading time ≈ 23 mins.

• Introduction
• What Are We Building?
  • Feature Overview
  • Architecture Overview
• Implementation Strategy
  • Model Selection
  • Tool Selection
  • Memory Strategy
  • System Prompt Design
• Prototyping in Jupyter
  • Environment Configuration
  • Dependencies
  • Loading Configuration
  • Defining Tools
  • Initializing the Multimodal Model
  • Memory Management
  • Creating the Agent
  • Testing with Image Input
  • Testing Conversation Memory
• Deploying with LangGraph and LangSmith
  • LangSmith Setup
  • Developing the Agent
  • Local Deployment with LangGraph CLI
  • Testing in LangSmith Studio

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LangChain Core Components: Model, Message, Prompt, Tool, Memory

Posted on 2026-05-04 Edited on 2026-06-06 In Python , AI
Symbols count in article: 26k Reading time ≈ 24 mins.

• What is LangChain?
  • The Platform
  • What is an Agent?
  • LLM vs Agent: The Difference
• Models — The Brain
  • Initializing a Model
  • Custom Models and Parameters
  • Using Model Classes
  • Calling the Model: invoke vs stream
  • Using Models in an Agent
• Messages — The Building Blocks of Conversation
  • Message Types
  • Multimodal Messages
• Prompts — Steering the Output
  • System Prompts
  • Prompt Engineering
  • Structured Output
• Tools — The Hands
  • Defining Tools
  • Custom Tools
  • Predefined Tools: Tavily Search
  • Combining Tools with an Agent
• Memory — Making the Agent Remember
  • Short-Term vs Long-Term Memory
  • Short-Term Memory with InMemorySaver
  • Persistent Memory (Optional)
  • Memory Management Strategies

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LangChain4J in Action: Building a Medical AI Assistant Agent

Posted on 2026-04-27 Edited on 2026-06-06 In Java , AI , Spring Boot
Symbols count in article: 19k Reading time ≈ 17 mins.

• 1. What is LangChain4J?
  • 1.1 The Problem LangChain4J Solves
  • 1.2 Core Concepts
• 2. Project Setup
  • 2.1 Dependencies
  • 2.2 Configuration
• 3. Your First LLM Integration
  • 3.1 Direct API Call
  • 3.2 Spring Boot Auto-Configuration
• 4. Building the AI Service
  • 4.1 The Assistant Interface
  • 4.2 System Messages
• 5. Adding Chat Memory
  • 5.1 Why Memory Matters
  • 5.2 Implementing Memory
  • 5.3 Memory Isolation
  • 5.4 Persistent Storage with MongoDB

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Message Middleware Selection Guide: RabbitMQ

Posted on 2026-04-26 Edited on 2026-06-05 In Backend Development
Symbols count in article: 11k Reading time ≈ 10 mins.

1. Introduction: Why We Need Message Middleware
2. Message Queue Comparison
3. RabbitMQ Core Concepts
4. Exchange Types Explained
5. Spring AMQP in Practice
6. Message Reliability Guarantees
7. Delayed Message Implementation
8. Best Practices & Common Issues
9. Summary

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