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MaGe Linux Operations
MaGe Linux Operations
May 22, 2026 · Operations

30 Essential Linux Commands Every New Ops Engineer Must Know

This guide walks Linux operations engineers through the 30 most frequently used commands, organized into seven categories, and shows real‑world scenarios, common options, safety warnings, and step‑by‑step examples so newcomers can confidently manage files, monitor systems, troubleshoot networks, handle users, and control services on production servers.

Command LineSystem AdministrationUser Management
0 likes · 58 min read
30 Essential Linux Commands Every New Ops Engineer Must Know
MaGe Linux Operations
MaGe Linux Operations
May 22, 2026 · Fundamentals

Why Knowing TCP’s Three‑Way Handshake and Four‑Way Teardown Isn’t Enough

The article explains TCP’s three‑way handshake and four‑way termination in depth, describes each state and flag, shows how kernel parameters affect behavior, and provides practical commands and troubleshooting steps for common issues such as TIME_WAIT overload, CLOSE_WAIT accumulation, SYN floods, and connection resets.

Four-way terminationLinux networkingTCP troubleshooting
0 likes · 26 min read
Why Knowing TCP’s Three‑Way Handshake and Four‑Way Teardown Isn’t Enough
Data Party THU
Data Party THU
May 22, 2026 · Artificial Intelligence

First Survey of Agent Harnesses: What Powers Agents Beyond the Model?

The article surveys recent research on Agent Harness engineering, showing that real‑world agent instability stems from system‑level factors beyond model capability, introduces the seven‑layer ETCLOVG architecture, presents benchmark gains from harness tweaks, maps open‑source projects to the framework, and outlines five key open research directions.

AIAgent HarnessArchitecture
0 likes · 12 min read
First Survey of Agent Harnesses: What Powers Agents Beyond the Model?
Su San Talks Tech
Su San Talks Tech
May 22, 2026 · Artificial Intelligence

Understanding the Core Mechanics Behind Claude Agent Skills

This article provides a detailed, step‑by‑step analysis of Claude's Agent Skills system, explaining how skills are discovered, structured in SKILL.md files, progressively disclosed, and executed through prompt expansion and context modification, complete with code snippets, design patterns, and workflow examples.

AI agentsAgent SkillsClaude
0 likes · 24 min read
Understanding the Core Mechanics Behind Claude Agent Skills
Golang Shines
Golang Shines
May 22, 2026 · Industry Insights

Meta Cuts 7,800 Jobs and Moves 7,000 Employees to AI Projects – What It Means

Meta announced a new round of layoffs affecting roughly 7,800 staff (about 10% of its workforce) and plans to reassign 7,000 workers to AI‑focused projects, while cancelling 6,000 open positions and flattening its management structure, sparking widespread employee anxiety and morale decline.

AI transformationEmployee MoraleMeta
0 likes · 6 min read
Meta Cuts 7,800 Jobs and Moves 7,000 Employees to AI Projects – What It Means
Golang Shines
Golang Shines
May 22, 2026 · Backend Development

Stop Learning Go Blindly: A Roadmap That Saves Six Months of Mistakes

This article presents a systematic Go learning roadmap—covering beginner, intermediate, and advanced topics such as language basics, tooling, design philosophy, embedded systems, AI, cloud native, and more—to help developers study efficiently and improve their job prospects.

Backend DevelopmentGoGolang
0 likes · 3 min read
Stop Learning Go Blindly: A Roadmap That Saves Six Months of Mistakes
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
May 22, 2026 · Fundamentals

Upgrade from Java 8: 8 Powerful Features in Java 21 You Should Know

The article examines why many projects still cling to Java 8 and demonstrates eight transformative Java 21 features—including records, sealed classes, pattern‑matching for instanceof, switch expressions, text blocks, virtual threads, structured concurrency, and enhanced APIs—showing code examples and the benefits they bring to performance, readability, and maintainability.

JavaJava 21Records
0 likes · 11 min read
Upgrade from Java 8: 8 Powerful Features in Java 21 You Should Know
Java Architect Handbook
Java Architect Handbook
May 22, 2026 · Backend Development

How Does RabbitMQ Ensure No Message Loss? Producer Confirms, Persistence, and Manual ACK Explained

The article breaks down RabbitMQ's three‑stage message flow—producer to broker, broker persistence, and broker to consumer—detailing how Publisher Confirm, durable exchanges/queues/messages, and manual consumer acknowledgments together guarantee reliability while discussing performance trade‑offs, high‑availability clustering, and common interview follow‑up questions.

Dead Letter QueueMessage reliabilityQuorum Queue
0 likes · 14 min read
How Does RabbitMQ Ensure No Message Loss? Producer Confirms, Persistence, and Manual ACK Explained
PaperAgent
PaperAgent
May 22, 2026 · Artificial Intelligence

A Systematic Review of the Latest Auto‑Research Landscape

The article presents a four‑phase, eight‑stage systematic analysis of AI‑driven auto‑research, exposing reliability gaps, bottlenecks, and best‑practice deployment through human‑governed collaboration, while detailing benchmarks, failure modes, and architectural families.

AI research automationauto-researchevaluation benchmarks
0 likes · 11 min read
A Systematic Review of the Latest Auto‑Research Landscape
Qunhe Technology Quality Tech
Qunhe Technology Quality Tech
May 22, 2026 · Artificial Intelligence

Cut Costs and Boost Efficiency: Deploying an MCP‑Workflow AI Customer Service Tool

The article details a step‑by‑step case study of building an AI‑powered customer‑service assistant on an MCP workflow, showing how the team reduced average ticket handling time from 5.3 hours to 10 minutes, cut over 500 tickets, and improved processing efficiency by 97 % through low‑code MVP development, iterative rollout, and operation‑level governance.

AICost ReductionEfficiency
0 likes · 13 min read
Cut Costs and Boost Efficiency: Deploying an MCP‑Workflow AI Customer Service Tool
Architecture Musings
Architecture Musings
May 22, 2026 · Industry Insights

Deep Dive into ThoughtWorks Tech Radar Vol. 34: Engineering Practices and Cognitive Re‑construction in the Agent Era

The article analyzes ThoughtWorks Technology Radar Vol. 34, highlighting how the rise of AI‑driven agents reshapes software engineering evaluation, introduces semantic diffusion and cognitive debt, and forces a return to classic practices while spotlighting newly adopted tools like Kafbat UI and Typer and warning about emerging anti‑patterns.

AIAgentic SystemsSecurity
0 likes · 34 min read
Deep Dive into ThoughtWorks Tech Radar Vol. 34: Engineering Practices and Cognitive Re‑construction in the Agent Era
Meituan Technology Team
Meituan Technology Team
May 22, 2026 · Artificial Intelligence

From High-Fidelity to Real-World Use: LongCat Video Avatar 1.5 Open‑Source Release

LongCat Video Avatar 1.5 is now open‑source, delivering commercial‑grade lip sync, physical realism, long‑video stability, multi‑person interaction and 15× faster inference through Whisper‑large audio encoding, DMD 8‑step distillation and LoRA adapters, and it outperforms leading closed‑source models in extensive human‑rated benchmarks.

AIDistillationLongCat-Video-Avatar
0 likes · 9 min read
From High-Fidelity to Real-World Use: LongCat Video Avatar 1.5 Open‑Source Release
DataFunTalk
DataFunTalk
May 22, 2026 · Big Data

How Xiaohongshu Cut Data Architecture Complexity and Cost by One‑Third in the Big AI Data Era

The article details Xiaohongshu's evolution from a simple ClickHouse‑based analytics layer to a Lambda‑enabled 2.0 stack and finally a Lakehouse‑based 3.0 architecture, showing how each iteration reduced infrastructure complexity, resource consumption and development effort by roughly one‑third while supporting trillions of daily events and AI‑driven use cases.

Big DataClickHouseData Architecture
0 likes · 21 min read
How Xiaohongshu Cut Data Architecture Complexity and Cost by One‑Third in the Big AI Data Era
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
May 22, 2026 · Artificial Intelligence

Why Complex Intelligent Decisions Must Be Decomposed (and How)

The article explains why complex intelligent decisions—such as those in autonomous driving—must be decomposed, outlines five key challenges, presents four classic decomposition paradigms, discusses interface design principles, and identifies scenarios where splitting may be counterproductive.

AI decision decompositionautonomous drivingfunctional modularization
0 likes · 10 min read
Why Complex Intelligent Decisions Must Be Decomposed (and How)
Baobao Algorithm Notes
Baobao Algorithm Notes
May 22, 2026 · Artificial Intelligence

How LiteScale Cuts Wait Times in Large‑Model Post‑Training with Gradient Accumulation

The article examines the bottleneck of synchronous rollout in large‑model post‑training, proposes an asynchronous design using gradient accumulation and a global micro‑batch count to preserve loss equivalence, and introduces LogitsExpress for efficient top‑K knowledge‑distillation communication, all implemented in the lightweight LiteScale framework.

Distributed TrainingPost-Trainingasynchronous rollout
0 likes · 16 min read
How LiteScale Cuts Wait Times in Large‑Model Post‑Training with Gradient Accumulation
AntTech
AntTech
May 22, 2026 · Cloud Native

From Computer Use to Datacenter Use: Enabling AI Agents to Drive Data Centers Like Function Calls

The article analyzes how AI agents require datacenter‑scale compute beyond a single virtual machine, explains why existing cloud‑native stacks cannot meet this demand, and details Ant Group's AKernel and openYuanrong solution—including three technical pillars, performance benchmarks, a tiny development team, and a streamlined deployment workflow that turns any developer into a "Build Your Own Cluster" operator.

AI agentsAKernelcloud native
0 likes · 16 min read
From Computer Use to Datacenter Use: Enabling AI Agents to Drive Data Centers Like Function Calls
SuanNi
SuanNi
May 22, 2026 · Artificial Intelligence

All‑In‑One Image & Video: ByteDance’s Deployable Native Multimodal Model Lance

Lance, ByteDance’s newly open‑sourced 3‑billion‑parameter multimodal model, runs on a single 40 GB GPU, tops HuggingFace trend charts, and achieves leading scores on DPG Bench, GenEval, and video generation benchmarks while surpassing several state‑of‑the‑art single‑modal models.

AI researchByteDanceLance
0 likes · 3 min read
All‑In‑One Image & Video: ByteDance’s Deployable Native Multimodal Model Lance