BestHub
Sign in

All Articles

140714 articles · Page 113 of 7036
Fun with Large Models
Fun with Large Models
Jun 11, 2026 · Artificial Intelligence

Master Claude Code with 6 GitHub Projects: From Multi‑Agent Collaboration to Source‑Code Deep Dive

This guide walks developers through six curated GitHub repositories that enable advanced multi‑agent usage of Claude Code, teach the fundamentals of building a custom code‑agent from scratch, and provide deep source‑code analysis for a complete understanding of AI‑powered programming assistants.

AI programmingClaude CodeDeepAgents
0 likes · 13 min read
Master Claude Code with 6 GitHub Projects: From Multi‑Agent Collaboration to Source‑Code Deep Dive
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 11, 2026 · Artificial Intelligence

Building an AI‑Native Multi‑Agent Digital Human Architecture on Cloud Native

The article details how a cloud‑native platform called AgentTeams enables AI‑Native multi‑agent digital‑human teams to replace manual incident response, automate end‑to‑end development workflows, and securely integrate LLMs and internal services through declarative orchestration and fine‑grained permission models.

AI-nativeAgentTeamsKubernetes
0 likes · 24 min read
Building an AI‑Native Multi‑Agent Digital Human Architecture on Cloud Native
Su San Talks Tech
Su San Talks Tech
Jun 11, 2026 · Artificial Intelligence

Why MarkItDown Is Dominating GitHub Trending: An In‑Depth AI‑Ready Document Converter

MarkItDown, the Microsoft‑backed open‑source tool that converts PDFs, Word, PPT, images and more into LLM‑friendly Markdown, has surged to over 150 k GitHub stars, and this article explains its architecture, installation, advanced features, strengths, limitations, and how it fits into RAG and AI workflows.

AI preprocessingLLMMCP
0 likes · 20 min read
Why MarkItDown Is Dominating GitHub Trending: An In‑Depth AI‑Ready Document Converter
ShiZhen AI
ShiZhen AI
Jun 11, 2026 · Artificial Intelligence

How a Hokkaido Farmer Built a Farm Automation System with ChatGPT and Codex

A Hokkaido farmer named Hiroki Tomiyasu used ChatGPT and Codex to turn greenhouse vents, satellite imagery, and farm records into a low‑cost, self‑built automation platform, demonstrating how AI can bridge the gap between field expertise and engineering implementation.

AI in AgricultureAirtableChatGPT
0 likes · 8 min read
How a Hokkaido Farmer Built a Farm Automation System with ChatGPT and Codex
Deepin Linux
Deepin Linux
Jun 11, 2026 · Fundamentals

12 Essential Embedded Debugging Techniques for One‑Click Issue Diagnosis

The article presents twelve practical embedded debugging methods—from basic software logging and UART prints to hardware tools like logic analyzers, oscilloscopes, and JTAG—organized by core principles, software techniques, hardware assistance, advanced tracing, and common pitfalls, enabling engineers to efficiently locate and resolve firmware and hardware faults.

JTAGUARTdebugging
0 likes · 27 min read
12 Essential Embedded Debugging Techniques for One‑Click Issue Diagnosis
AI Engineer Programming
AI Engineer Programming
Jun 11, 2026 · Artificial Intelligence

How to Build Truly Effective LLM-as-a-Judge Evaluators

The article explains how to construct reliable LLM-as-a-Judge evaluators by combining deterministic code checks for syntactic validation, designing clear semantic evaluation rubrics, choosing appropriate output formats, calibrating with human‑labeled data, mitigating known model biases, and integrating trace‑based monitoring into production workflows.

AI safetyLLM EvaluationLLM-as-a-Judge
0 likes · 15 min read
How to Build Truly Effective LLM-as-a-Judge Evaluators
Linyb Geek Road
Linyb Geek Road
Jun 11, 2026 · Artificial Intelligence

From Reactive to Self‑Evolving: The Four‑Stage Evolution of AI Agents (2023‑2026)

The article maps the 2023‑2026 evolution of AI agents across four distinct stages—reactive ReAct, workflow‑driven, autonomous, and self‑evolving—while dissecting how the six core modules (Prompt, Planning, Memory, Tools, Workflow, Environment) shift from model‑centric to engineered determinism.

AI agentsAgent ArchitectureMemory
0 likes · 10 min read
From Reactive to Self‑Evolving: The Four‑Stage Evolution of AI Agents (2023‑2026)
AI Architecture Path
AI Architecture Path
Jun 11, 2026 · Databases

Why Beekeeper Studio Is the Free, Open‑Source Alternative to Navicat with Built‑In AI SQL Assistant

The article compares paid database clients such as Navicat, DBeaver, TablePlus and DataGrip, highlights their cost and usability issues, and presents Beekeeper Studio—a cross‑platform, open‑source tool with a sleek UI, tab persistence, smart SQL completion, extensive database support, and an AI Shell for automatic query generation—while also outlining its strengths, limitations, and when to choose the free Community edition versus the paid Ultimate edition.

AIBeekeeper StudioComparison
0 likes · 11 min read
Why Beekeeper Studio Is the Free, Open‑Source Alternative to Navicat with Built‑In AI SQL Assistant
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Jun 11, 2026 · Artificial Intelligence

Scaling Automated Formalization of Mathematics: Inside Meta’s AutoformBot and the ATLAS Lean 4 Library

Meta’s recent paper presents AutoformBot, a multi‑agent system that treats formalizing entire mathematics textbooks as a large‑scale software‑engineering project, generating the ATLAS Lean 4 library with over 45,000 declarations and demonstrating a 71 % success rate across 26 open‑access books.

AutoformBotLLM AgentsLean 4
0 likes · 14 min read
Scaling Automated Formalization of Mathematics: Inside Meta’s AutoformBot and the ATLAS Lean 4 Library
Python Crawling & Data Mining
Python Crawling & Data Mining
Jun 11, 2026 · Operations

Real Fan Request: Python Automation for Bulk Bill-of-Lading Watermark Replacement (Part 1)

The article outlines a fan's request to automate the replacement of header watermarks in dozens of foreign‑trade bill‑of‑lading .doc files using Python, explains the inefficiency of manual editing, describes converting .doc to .docx and applying python‑docx, and previews a detailed multi‑part walkthrough of the implementation challenges.

Office AutomationPythonWord
0 likes · 4 min read
Real Fan Request: Python Automation for Bulk Bill-of-Lading Watermark Replacement (Part 1)
AI Architecture Hub
AI Architecture Hub
Jun 11, 2026 · Artificial Intelligence

Why Every AI Engineer Must Master Agent Loops by 2026

The article explains how AI engineers should shift from single‑prompt interactions to designing autonomous agent loops, outlines the token‑cost challenges of open‑ended cycles, presents closed‑loop and multi‑agent architectures, and details six essential components and practical examples for building cost‑effective, scalable automation.

AI agentsLarge language modelsLoop Engineering
0 likes · 18 min read
Why Every AI Engineer Must Master Agent Loops by 2026
Java Architect Essentials
Java Architect Essentials
Jun 10, 2026 · Industry Insights

Why Cursor 3 Makes Traditional IDEs Like VS Code Obsolete

Cursor 3 replaces the classic code editor with an AI‑agent management console, reflecting a market‑driven shift that forces developers to rethink tooling, workflow, and even their role as the industry pivots toward agent orchestration and new pricing models.

AI code editorAI toolingAgent Orchestration
0 likes · 13 min read
Why Cursor 3 Makes Traditional IDEs Like VS Code Obsolete
CodeNotes
CodeNotes
Jun 10, 2026 · Backend Development

After a Decade with Map, Are You Still Using containsKey + get + put?

The article reviews the seven Java 8 Map convenience APIs—getOrDefault, putIfAbsent, computeIfAbsent, computeIfPresent, compute, merge, and forEach—plus replaceAll and Map.of, showing concise code examples, best‑practice recommendations, concurrency considerations, and common pitfalls for modern Java developers.

APICollectionsJava
0 likes · 10 min read
After a Decade with Map, Are You Still Using containsKey + get + put?
LuTiao Programming
LuTiao Programming
Jun 10, 2026 · Backend Development

Why 90% of Developers Misuse Codex for Spring Boot – The Critical First Mistake

Most developers give AI coding tools vague one‑sentence requests for Spring Boot tasks, causing the AI to generate code that violates project conventions, while a detailed engineering task sheet that includes context, constraints, and verification steps dramatically improves the quality and safety of the generated code.

AGENTS.mdCodexJava
0 likes · 16 min read
Why 90% of Developers Misuse Codex for Spring Boot – The Critical First Mistake
Model Perspective
Model Perspective
Jun 10, 2026 · Industry Insights

From Supply Shortage to Cognitive Dissonance: How the ‘Goose Leg Aunt’ Scam Began

The article dissects the rise of the “Goose Leg Aunt” fraud by examining supply constraints, the vendor's substitution decision, cognitive‑dissonance rationalizations, the fraud‑triangle framework, neural adaptation to lying, and how massive online traffic shattered the low‑supervision equilibrium that had kept the deception hidden.

case studycognitive dissonancefraud
0 likes · 10 min read
From Supply Shortage to Cognitive Dissonance: How the ‘Goose Leg Aunt’ Scam Began