A practical comparison of 12 major AI Agent frameworks and Coding Agent products, covering Agent Loops, context, tools, permissions, subagents, MCP, persistence, sandboxing, and human-in-the-loop design.
AI & Agents
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Chapter 4 — What Is an Agent Harness?
An Agent Harness is the runtime framework that transforms LLM reasoning into reliable, safe, controllable, and stateful real-world actions. This chapter explains the relationship between Model, Agent, and Harness, its core responsibilities, Harness Engineering, production challenges, and why the Harness will remain essential as AI models evolve.
AI & Agents
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Chapter 3 — The Agent Loop: The Core Execution Cycle of an AI Agent
Agent Loop is the core execution cycle of an AI Agent. This chapter explains Observe–Think–Act, ReAct, Tool-use Agents, Self-correction, error handling, context overflow, and why Agent Harness complexity matters.
System Architecture
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AI Agent Architecture and Engineering Practice Guide
Explore AI Agent architecture from LLMs and Agent Loops to Harnesses, Claude Code, Coding Agents, and production-grade Agent Platforms
AI & Agents
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Chapter 2 — LLM Application Architecture: Core Components and Engineering Foundations
Learn the core architecture of LLM applications, including models, prompts, context, tools, memory, state, runtime, Tool Calling, streaming, structured output, error handling, model routing, and cost management.
AI & Agents
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Chapter 1: Rethinking AI Agents
Chapter Objective: Build an accurate understanding of AI Agents, clarify the boundaries between Chatbots, Copilots, Agents, Autonomous Agents, and Coding Agents, understand why an LLM can serve as the “brain” of an Agent, and establish the fundamental definition of an Agent: Agent = LLM + Harness. This chapter provides the conceptual foundation for the entire book
Tech History
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The Key Milestones in the History of Artificial Intelligence (2026.08)
From symbolic AI and expert systems to foundation models and autonomous AI agents, the evolution of artificial intelligence has been shaped by decades of breakthroughs in algorithms, data, computing power, and software engineering.
Tech Notes
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Building a Python-based AI Agent with LangGraph and OpenRouter: A Hands-On Guide
In this guide, learn how to build a Python-based AI agent using LangGraph and OpenRouter. Explore how to integrate tools like weather services and PDF parsing into your agent to create real-world applications.
Tech Notes
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System Architecture Design: What Is It Really “Designing”? Understanding Through a Building Analogy
Understanding system architecture design doesn’t require deep IT knowledge. Using the analogy of building a house, learn how business, application, data, and technical blueprints guide enterprise IT systems, ensuring stability, efficiency, and scalability for sustainable growth.
Tech Notes
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When Data Exceeds Memory: Choosing Between Pandas, Dask, and DuckDB for Efficient Analytics
As data grows beyond memory limits, traditional Pandas workflows can fail. Learn how Pandas, Dask, and DuckDB differ for medium-scale data analysis, their strengths, limitations.
Tech Notes
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2025: From Data Analytics to Intelligent Decision-Making — The Next Digital Transformation Turning Point
Explore how businesses in 2025 are evolving from data analytics to intelligent decision-making. Learn how AI, automation, and decision intelligence platforms drive faster, smarter, and more connected enterprise transformation.
Tech Notes
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Free HTTPS Certificate Setup: A Complete Guide for CentOS 7 + Nginx + Let’s Encrypt
This comprehensive guide teaches you how to set up free HTTPS with CentOS 7 and Nginx using Let’s Encrypt and Certbot. Learn to configure multi-site deployments, DNS, and auto-renewal easily.
Tech Notes
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Understanding Architecture Evolution: Monolith, Microservices, and PBC
In this article, we explore three major architectural paradigms—Monolithic, Microservices, and Packaged Business Capabilities (PBCs)—and how they reflect the maturity and complexity of modern software architecture and businesses.
Tech Notes
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A Comprehensive Guide to AI Agents: Definition, Role, Examples, and Future Prospects
Learn how AI Agents work, their applications, and future potential. Discover an AI email assistant example showing the practical impact of AI Agents on productivity and communication.
Tech Notes
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The History of Artificial Intelligence (AI): From Turing to ChatGPT
Explore the history of artificial intelligence through each decade—from early theories and expert systems to deep learning and generative AI. Discover how AI evolved to become today’s transformative force.
Tech Notes
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Clone a WordPress with ASP.NET and React Part 2: Create ASP.NET Projects Code Files with AI
In Part 2 of the WordPress clone tutorial, we’ll use AI to generate code files for the ASP.NET Core backend. Starting with the WordPress.NET.Domain project, we’ll create, validate, and compile the code step-by-step.