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prompt engineering

1655 articles · Page 6 of 17
Code of Duty
Code of Duty
May 24, 2026 · Artificial Intelligence

Getting Started with Codex: How an AI Partner Can Read Code, Fix Bugs, and Add Features

This guide walks beginners through installing and configuring OpenAI's Codex, explains its CLI and cloud modes, compares permission levels, demonstrates effective prompt patterns, outlines a step‑by‑step workflow, and highlights common pitfalls to help developers use the AI assistant safely and productively.

AI programming assistantCLICodex
0 likes · 8 min read
Getting Started with Codex: How an AI Partner Can Read Code, Fix Bugs, and Add Features
CodeNotes
CodeNotes
May 24, 2026 · Artificial Intelligence

Boost Your Coding Speed 10× with GitHub Copilot in VSCode: An Ultimate Practical Guide

This guide walks you through installing, configuring, and mastering GitHub Copilot in VSCode—covering essential settings, comment‑driven development, shortcut keys, Copilot Chat modes, Agent‑based refactoring, team‑wide prompts, common pitfalls, and a quantified efficiency comparison that shows up to ten‑fold productivity gains.

AI codingAgent modeComment-Driven Development
0 likes · 19 min read
Boost Your Coding Speed 10× with GitHub Copilot in VSCode: An Ultimate Practical Guide
ArcThink
ArcThink
May 24, 2026 · Artificial Intelligence

When to Use MCP vs. Skills: A Clear Capability Stack for Building Stable AI Agents

The article explains a four‑layer capability model—Rules, Skills, MCP, and Agents—showing how to decide when to add an MCP server, a Skill, or a Rule, and how combining them yields reliable AI‑powered programming assistants for both personal projects and team‑scale engineering.

AI agentsMCPSkills
0 likes · 23 min read
When to Use MCP vs. Skills: A Clear Capability Stack for Building Stable AI Agents
AI Engineering
AI Engineering
May 24, 2026 · Artificial Intelligence

Build a Local AI Agent from Scratch: A Deep‑Dive, Non‑Fast‑Food Tutorial

This tutorial walks you through the open‑source “AI Agents From Scratch” project, teaching how to build a fully local AI agent without any pre‑made framework by covering core modules, 14 step‑by‑step examples, advanced reasoning architectures, and minimal system requirements.

AI AgentLocal LLMReact
0 likes · 6 min read
Build a Local AI Agent from Scratch: A Deep‑Dive, Non‑Fast‑Food Tutorial
Tech Ocean
Tech Ocean
May 23, 2026 · Artificial Intelligence

Building Self-Evolving AI Skills: A Harness Engineering Case Study with SkillForge

The article explores Harness Engineering as a framework for creating reliable, long‑running AI agents, detailing a hands‑on project called SkillForge that transforms books into executable Skills, and outlines key components, iterative processes, documentation, and best practices for stable, self‑evolving AI workflows.

AI agentsHarness EngineeringSelf-Evolving Skills
0 likes · 20 min read
Building Self-Evolving AI Skills: A Harness Engineering Case Study with SkillForge
Smart Workplace Lab
Smart Workplace Lab
May 23, 2026 · Artificial Intelligence

Why AI Output Still Needs Manual Fixes and How a 3‑Step Automated Test Can Cut Rework by 80%

The article explains why fast AI‑generated drafts still demand tedious manual corrections and presents a three‑step automated testing protocol—format locks, logical validation, and redundancy filtering—that shifts quality checks upstream, reducing manual rework by about 80% and error rates below 2%.

AIautomated testingproductivity
0 likes · 6 min read
Why AI Output Still Needs Manual Fixes and How a 3‑Step Automated Test Can Cut Rework by 80%
IT Services Circle
IT Services Circle
May 23, 2026 · Artificial Intelligence

Why Most People Can’t Benefit from AI Agents – They Don’t Even Know Their Daily Tasks

The author argues that despite the hype around AI agents like OpenClaw, most users fail to improve efficiency because they cannot clearly define their daily work, and proposes an open‑source “Agent Workflow Designer” skill that guides users to map, analyze, and gradually automate their tasks through structured questioning and phased implementation.

AI agentsOpenClawWorkflow Design
0 likes · 10 min read
Why Most People Can’t Benefit from AI Agents – They Don’t Even Know Their Daily Tasks
ZhiKe AI
ZhiKe AI
May 23, 2026 · Artificial Intelligence

Why AI Won’t Follow Your Commands—and How a Simple “Rule” Manual Fixes It

Developers often receive AI‑generated code that ignores their framework, naming, or style preferences, but by creating a concise Rule file (e.g., AGENTS.md) that the assistant reads at startup, they can boost efficiency, enforce consistent standards, and reduce low‑level errors, as shown by recent industry studies.

AGENTS.mdAIDeveloper Tools
0 likes · 11 min read
Why AI Won’t Follow Your Commands—and How a Simple “Rule” Manual Fixes It
ArcThink
ArcThink
May 23, 2026 · Artificial Intelligence

Why a 65‑Line CLAUDE.md Can Put Brakes on AI Coding Assistants

The article dissects the Karpathy‑inspired 65‑line CLAUDE.md file, showing how its four concise constraints—think before coding, simplicity first, surgical changes, and goal‑driven execution—prevent common AI coding agent failures, why the approach works, and its limits.

AI coding assistantAgent SafetyCLAUDE.md
0 likes · 14 min read
Why a 65‑Line CLAUDE.md Can Put Brakes on AI Coding Assistants
AI Architecture Hub
AI Architecture Hub
May 23, 2026 · Artificial Intelligence

Unlock Claude’s Hidden Features Most Users Miss

This guide walks through every hidden Claude capability—from Projects that remember context, to Artifacts that generate runnable tools, Adaptive Thinking for step‑by‑step reasoning, Memory profiles, role‑setting prompts, Chrome extension, desktop Cowork app, scheduled tasks, Skills plugins, Claude.md rules, Claude Code, Claude Design, and Prompt Caching—providing entry points, activation steps, and ready‑to‑paste prompts so you can enable each feature in minutes and reap daily productivity gains.

AIClaudeDeveloper Tools
0 likes · 18 min read
Unlock Claude’s Hidden Features Most Users Miss
IT Services Circle
IT Services Circle
May 22, 2026 · Artificial Intelligence

Interview Question: How Do You Maintain CLAUDE.md in Claude Code? My Honest Reply

The article explains what CLAUDE.md is, why it’s essential for Claude Code, how over‑filling it harms token efficiency, the principles of writing effective, verifiable rules, modular organization with path‑scoped files, and practical commands (/init, /memory) plus a ready‑to‑use template.

AI configurationCLAUDE.mdClaude Code
0 likes · 22 min read
Interview Question: How Do You Maintain CLAUDE.md in Claude Code? My Honest Reply
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
TechVision Expert Circle
TechVision Expert Circle
May 22, 2026 · Artificial Intelligence

Can Enterprise Architecture Still Matter When Model Vendors Can Cut Off Service Overnight?

The article examines real incidents of sudden model price hikes and API shutdowns, explains why traditional architecture fails to protect against such risks, and proposes a model‑agnostic AI architecture with a unified gateway, prompt management layer, and automated evaluation to ensure seamless model replacement.

AI architectureLLM Governancemodel gateway
0 likes · 12 min read
Can Enterprise Architecture Still Matter When Model Vendors Can Cut Off Service Overnight?
FunTester
FunTester
May 22, 2026 · Artificial Intelligence

Why Prompt Tuning Isn’t Enough: Building a Test‑Driven Mindset for AI Products

The article argues that while prompt engineering accelerates early AI product development, it cannot guarantee overall quality, and advocates establishing a systematic evaluation pipeline—including curated datasets, clear benchmarks, regression testing, and automated checks—to make AI product quality visible and reliably improve over time.

AI testingEvaluation PipelineRegression Testing
0 likes · 16 min read
Why Prompt Tuning Isn’t Enough: Building a Test‑Driven Mindset for AI Products
Alibaba Cloud Developer
Alibaba Cloud Developer
May 22, 2026 · Artificial Intelligence

How Core Agent Concepts and Paradigms Have Evolved and the Rationale Behind Them

The article traces the evolution of AI agents from early ReAct‑style models through workflow‑based systems to autonomous and self‑evolving agents, analyzing six core dimensions—Prompt, Planning, Memory, Tools, Workflow, and Environment—and explains why each paradigm shift occurred, citing recent frameworks and research.

AI agentsMemory ManagementSelf-Evolving Systems
0 likes · 25 min read
How Core Agent Concepts and Paradigms Have Evolved and the Rationale Behind Them
Smart Workplace Lab
Smart Workplace Lab
May 21, 2026 · Operations

When AI‑Generated Copy Hits Red Lines: How to Pre‑Screen and Avoid Compliance Violations

The article recounts a real‑world case where AI‑generated marketing copy was blocked for extreme wording and unauthorized comparisons, explains why post‑audit fails at scale, and provides a step‑by‑step pre‑screening framework—including prompt‑based checks, a dynamic replacement library, and routing rules—to dramatically cut violation rates and legal review effort.

AI compliancecontent moderationdynamic word list
0 likes · 7 min read
When AI‑Generated Copy Hits Red Lines: How to Pre‑Screen and Avoid Compliance Violations
Old Zhang's AI Learning
Old Zhang's AI Learning
May 21, 2026 · Artificial Intelligence

Matt Pocock Open‑Sources His Complete .claude Skills Repository

The article reviews Matt Pocock’s newly released mattpocock/skills GitHub repository, explaining its purpose, installation steps, folder structure, core engineering skills, four common failure modes, and how its concise, composable prompts differ from Anthropic’s official skills, while offering practical recommendations for Claude Code and Codex users.

AI agentsClaudeDevOps
0 likes · 12 min read
Matt Pocock Open‑Sources His Complete .claude Skills Repository
大转转FE
大转转FE
May 21, 2026 · Artificial Intelligence

Why AI Buzzwords Multiply Faster Than My Hair Falls

The article maps three generations of AI engineering—Prompt Engineering, Context Engineering, and Harness Engineering—explaining their core capabilities, key terms like LLM, RAG, Agent, and evaluation methods, while offering practical tips, pitfalls, and a concise three‑question checklist to stay grounded amid the rapid influx of new AI jargon.

AIAgentHarness
0 likes · 19 min read
Why AI Buzzwords Multiply Faster Than My Hair Falls
AndroidPub
AndroidPub
May 21, 2026 · Frontend Development

Beyond Opus 4.7: How to Hand Over Coding Tasks to AI Instead of Micromanaging

After trying Opus 4.7, the author shows that the old "pair‑programming" style of feeding AI tiny prompts wastes time, and explains a delegation workflow—clear goals, constraints, acceptance criteria, effort levels, permission handling, and verification loops—that lets AI independently deliver reliable web and mobile features.

AI codingMobile DevelopmentVerification Loop
0 likes · 15 min read
Beyond Opus 4.7: How to Hand Over Coding Tasks to AI Instead of Micromanaging
Linyb Geek Road
Linyb Geek Road
May 21, 2026 · Artificial Intelligence

Understanding Prompt, MCP, and Skill: Three Essential AI Concepts

The article explains how Prompt, Model Context Protocol (MCP), and Skill serve distinct but complementary roles in AI interaction—Prompt provides instant, conversational instructions, MCP connects the model to external tools and data, and Skill offers pre‑packaged expert capabilities, together forming a layered control hierarchy.

AIMCPPrompt
0 likes · 8 min read
Understanding Prompt, MCP, and Skill: Three Essential AI Concepts
AI Architecture Hub
AI Architecture Hub
May 21, 2026 · Artificial Intelligence

Build a Personal Claude AI Workspace Anyone Can Use

The article explains why repeatedly re‑introducing yourself to Claude wastes time and presents a six‑layer, 18‑action framework for creating a personal AI workspace—Project organization, custom instructions, knowledge bases, task clarification, output control, context governance, and feedback—to turn Claude into a dedicated, efficient assistant.

AI productivityAI workspaceClaude
0 likes · 16 min read
Build a Personal Claude AI Workspace Anyone Can Use
Tencent Tech
Tencent Tech
May 20, 2026 · Artificial Intelligence

The Three Evolutions of AI Engineering: Prompt, Context, and Harness

This article analyzes the progressive stages of AI‑driven software engineering—Prompt Engineering, Context Engineering, and Harness Engineering—illustrating how each addresses specific challenges, presenting real‑world experiments from OpenAI and Anthropic, and outlining a roadmap for engineers to master the new paradigm.

AI agentsContext EngineeringHarness Engineering
0 likes · 19 min read
The Three Evolutions of AI Engineering: Prompt, Context, and Harness
Code of Duty
Code of Duty
May 20, 2026 · Artificial Intelligence

Why Large Language Models Aren’t Magic: The Simple AI Principle Everyone Can Understand

The article demystifies large language models by explaining their core task of next‑token prediction, tokenization, vector semantics, Transformer attention, massive training, hallucination risks, prompt design, and tool integration, showing how these mechanisms work together and why verification is essential.

AI hallucinationAgentAttention
0 likes · 14 min read
Why Large Language Models Aren’t Magic: The Simple AI Principle Everyone Can Understand
SuanNi
SuanNi
May 20, 2026 · Artificial Intelligence

AI‑Powered Research Workflow: When to Trust the Tools and When to Supervise

The article surveys AI‑assisted research across the full lifecycle—creation, writing, validation, and dissemination—detailing the capabilities of prompt engineering, retrieval‑augmented generation, training‑free agents and hybrid methods, reporting benchmark numbers, failure modes, and governance challenges that dictate when human oversight remains essential.

AI research automationLarge Language ModelsRetrieval-Augmented Generation
0 likes · 17 min read
AI‑Powered Research Workflow: When to Trust the Tools and When to Supervise
ZhiKe AI
ZhiKe AI
May 19, 2026 · R&D Management

Why One‑Shot AI Prompts Fail and How 19 Iron Rules Build a Factory‑Style Workflow

The article explains that single‑turn AI chats cannot handle complex tasks, and introduces Harness—a six‑agent AI workflow that organizes AI roles, enforces 19 strict rules, and uses a five‑step setup to turn ad‑hoc prompts into a disciplined, self‑evolving production line for content and software development.

AI agentsAI workflowProcess Automation
0 likes · 14 min read
Why One‑Shot AI Prompts Fail and How 19 Iron Rules Build a Factory‑Style Workflow
Linyb Geek Road
Linyb Geek Road
May 19, 2026 · Artificial Intelligence

Five Best Design Patterns for AI Agent Skills

This article explains five practical design patterns—tool wrapper, generator, reviewer, inversion, and pipeline—for structuring AI agent SKILL.md files, showing when to use each, how they work internally, and how they can be combined for robust, maintainable agent behavior.

AI agentsDesign PatternsLLM
0 likes · 19 min read
Five Best Design Patterns for AI Agent Skills
BirdNest Tech Talk
BirdNest Tech Talk
May 18, 2026 · Artificial Intelligence

Taming AI Coding Agents: A Powerful Development Workflow with Engineering Discipline

The article introduces Matt Pocock's open‑source "skills" collection for AI coding agents, shows how it embeds traditional engineering practices such as alignment, domain modeling, TDD, and architecture governance into reusable command sets, and walks through a complete partial‑refund feature implementation using these skills.

AI coding agentsSoftware engineering workflowTDD
0 likes · 22 min read
Taming AI Coding Agents: A Powerful Development Workflow with Engineering Discipline
Architect
Architect
May 18, 2026 · Artificial Intelligence

18 Essential Actions to Build a Personal Claude AI Workbench

The article explains that effective use of Claude depends on establishing a stable personal work environment rather than merely crafting prompts, and it details 18 concrete actions organized into six layers—projects, personal instructions, fact sources, workflow cards, review loops, and boundaries—to create a reusable AI workbench.

AI workflowClaudeContext Management
0 likes · 31 min read
18 Essential Actions to Build a Personal Claude AI Workbench
DeepHub IMBA
DeepHub IMBA
May 18, 2026 · Artificial Intelligence

Self‑Improving Multi‑Agent RAG System: Architecture, Evaluation, and Human‑Reviewed Prompt Loop

An end‑to‑end multi‑agent Retrieval‑Augmented Generation platform is presented, featuring compositional reasoning, systematic multi‑dimensional evaluation, and a controlled prompt‑improvement loop that automatically identifies weak prompt dimensions, proposes diffs, and requires human approval before deployment, with full observability via SSE and persisted logs.

FastAPIMulti-agentRAG
0 likes · 19 min read
Self‑Improving Multi‑Agent RAG System: Architecture, Evaluation, and Human‑Reviewed Prompt Loop
Shi's AI Notebook
Shi's AI Notebook
May 18, 2026 · Artificial Intelligence

Anthropic’s Practical Approach to Context Engineering for AI Agents

The article explains how Anthropic engineers treat the limited token budget of large language models as a finite resource, detailing static configuration, runtime retrieval, and long‑task strategies such as compaction, structured notes, and sub‑agent architectures to build reliable, efficient AI agents.

AI agentsAnthropicContext Engineering
0 likes · 18 min read
Anthropic’s Practical Approach to Context Engineering for AI Agents
James' Growth Diary
James' Growth Diary
May 18, 2026 · Artificial Intelligence

Turning AI’s Short‑Term Memory into a Persistent Knowledge Base with memdir

This article examines Claude Code’s memdir system, explaining how it transforms fleeting AI conversation context into a durable, file‑based knowledge base by using markdown files as memories, a lightweight index, AI‑driven relevance selection, parallel prefetching, and careful type‑specific guidelines.

AI memoryClaude CodeFile System
0 likes · 17 min read
Turning AI’s Short‑Term Memory into a Persistent Knowledge Base with memdir
Su San Talks Tech
Su San Talks Tech
May 18, 2026 · Artificial Intelligence

How to Guarantee Reliable Function Calling in LLM Agents

The article breaks down the reliability challenges of LLM Function Calling, categorizes five failure modes, and presents concrete engineering safeguards such as precise schema design, tool description, constraint enforcement, few‑shot calibration, structured output, validation‑feedback loops, monitoring, and risk‑aware trade‑offs.

Function CallingJSON SchemaLLM
0 likes · 17 min read
How to Guarantee Reliable Function Calling in LLM Agents
AI Code to Success
AI Code to Success
May 18, 2026 · Artificial Intelligence

Redefining Skill Development: A Complete Tutorial and One‑Stop Dev Assistant

This guide explains the concept of AI Agent Skills, walks through creating, installing, and managing a Skill—including file structure, YAML metadata, progressive loading, platform-specific considerations—and introduces a one‑stop development assistant that streamlines Skill development and deployment.

AI agentsDevOpsSkill Development
0 likes · 27 min read
Redefining Skill Development: A Complete Tutorial and One‑Stop Dev Assistant
Alibaba Cloud Developer
Alibaba Cloud Developer
May 18, 2026 · Artificial Intelligence

Redefining Skill Development: A Hands‑On Guide and One‑Stop Development Assistant

This article walks you through the concept of AI Agent Skills, showing how to design, write, install, publish, and manage a Skill—from the underlying three‑level loading mechanism and cross‑platform considerations to best‑practice guidelines, versioning strategies, automated testing, and even self‑improving loops—so you can turn repetitive tasks into reusable, shareable automation assets.

AI AgentDevOpsSkill Development
0 likes · 27 min read
Redefining Skill Development: A Hands‑On Guide and One‑Stop Development Assistant
Linyb Geek Road
Linyb Geek Road
May 18, 2026 · Artificial Intelligence

Building High‑Availability Claude Skills: From Core Mechanics to Production‑Ready Development

This article explains why a perfectly written Claude Skill may never be invoked, reveals the underlying meta‑tool architecture, demonstrates the three‑level progressive loading model that saves up to 80% of token usage, and provides a step‑by‑step guide, code samples, debugging checklists, and best‑practice patterns for creating robust, production‑grade Claude Skills.

AI toolsClaudeSkill
0 likes · 30 min read
Building High‑Availability Claude Skills: From Core Mechanics to Production‑Ready Development
Java Architect Essentials
Java Architect Essentials
May 17, 2026 · Artificial Intelligence

When Is GPT‑5.5 Worth Upgrading? A Practical Guide to Plus vs Pro

The article explains how GPT‑5.5 can boost daily productivity, advises evaluating personal workflows before subscribing, compares ChatGPT Plus and Pro based on task intensity, and offers concrete prompting tips and a usage‑scenario table to help users choose the right tier without blind upgrades.

AI productivityChatGPTGPT-5.5
0 likes · 6 min read
When Is GPT‑5.5 Worth Upgrading? A Practical Guide to Plus vs Pro
LuTiao Programming
LuTiao Programming
May 17, 2026 · Artificial Intelligence

Why Your AI Keeps Going Off‑Track: The 4 Essential CLAUDE.md Directives

The article analyzes why AI coding assistants often stray from intended requirements, exposing a core judgment deficit, and shows how a concise four‑line CLAUDE.md file—detailing assumptions, minimal code, scoped changes, and verifiable success criteria—can dramatically improve AI behavior, reduce over‑design, and lower review costs.

AI codingCLAUDE.mdLLM agents
0 likes · 11 min read
Why Your AI Keeps Going Off‑Track: The 4 Essential CLAUDE.md Directives
Smart Workplace Lab
Smart Workplace Lab
May 17, 2026 · Artificial Intelligence

How to Break AI Prompt Homogenization and Boost Workplace Value

The article explains why standard AI prompts produce bland, generic output, shares the author's experience of value erosion after over‑standardizing prompts, and presents a three‑step protocol that injects asymmetric, anti‑consensus material to create distinctive, high‑impact AI responses in professional settings.

AIAnti‑ConsensusDifferentiation
0 likes · 5 min read
How to Break AI Prompt Homogenization and Boost Workplace Value
IT Services Circle
IT Services Circle
May 17, 2026 · Artificial Intelligence

60 Essential AI Terms Every Programmer Should Master

This article walks programmers through 60 core AI concepts—from the basics of large language models and tokens to advanced topics like prompt engineering, retrieval‑augmented generation, fine‑tuning, and inference optimization—organized into progressive skill levels and illustrated with concrete examples and code snippets.

AIFine-tuningInference Optimization
0 likes · 25 min read
60 Essential AI Terms Every Programmer Should Master
FunTester
FunTester
May 17, 2026 · Artificial Intelligence

How a Rubric‑Driven Agent Achieves More Stable Outputs

The article explains why vague expectations cause unstable Agent results, introduces Rubric as a concrete, pre‑written scoring standard for Generator‑Critic workflows, details how to design clear Yes/No criteria, organize them into Must/Should/Nice‑to‑have layers, and iteratively refine the Rubric for reliable AI output.

AI evaluationAgentCritic
0 likes · 8 min read
How a Rubric‑Driven Agent Achieves More Stable Outputs
ZhiKe AI
ZhiKe AI
May 17, 2026 · Artificial Intelligence

Harness Engineering: How 8 AI Agents Collaborate to Write Wuxia Novels

The article details Harness Engineering’s deterministic multi‑agent workflow that splits novel writing into seven staged phases, enforced by strict rule files and verification scripts, enabling eight specialized AI agents to collaboratively produce complete wuxia novels with consistent characters, martial arts systems, and quality guarantees.

AI OrchestrationSoftware Engineeringdeterministic workflow
0 likes · 22 min read
Harness Engineering: How 8 AI Agents Collaborate to Write Wuxia Novels
Java Architect Essentials
Java Architect Essentials
May 16, 2026 · Industry Insights

Why Prompting Skills Outshine Templates After GPT‑5.5

The article explains that after GPT‑5.5 the key to getting value is mastering prompt techniques, compares ChatGPT Plus and Pro for different user scenarios, and offers practical guidance on choosing and using the appropriate tier effectively.

ChatGPTChatGPT PlusChatGPT Pro
0 likes · 5 min read
Why Prompting Skills Outshine Templates After GPT‑5.5
James' Growth Diary
James' Growth Diary
May 16, 2026 · Artificial Intelligence

Dynamic Tool Selection Unpacked: Let the Agent Choose the Right Tool with Three Strategies

The article analyzes why binding all tools to an LLM agent is costly and error‑prone, presents benchmark data showing token usage dropping six‑fold and error rates falling by up to five times with dynamic selection, and details three practical strategies—vector retrieval, LLM routing, and rule‑semantic hybrid—along with implementation tips, description engineering, multi‑turn handling, and common pitfalls.

AgentLLMLangGraph
0 likes · 17 min read
Dynamic Tool Selection Unpacked: Let the Agent Choose the Right Tool with Three Strategies
Senior Tony
Senior Tony
May 16, 2026 · Artificial Intelligence

Why Claiming LLM MCP Is Dead and Skills Are Supreme Reveals Beginner Thinking

The article argues that declaring LLM MCP obsolete while praising Skills as the ultimate capability reflects a beginner’s misunderstanding, explaining that MCP is a low‑level tool‑connection protocol akin to USB/HTTP, whereas Skills are high‑level business‑logic wrappers, and the real engineering challenges lie elsewhere.

AI agentsLLMMCP
0 likes · 5 min read
Why Claiming LLM MCP Is Dead and Skills Are Supreme Reveals Beginner Thinking
DataFunTalk
DataFunTalk
May 16, 2026 · Artificial Intelligence

How to Turn AI into an S‑Level Employee: Practical Skill Training for Reliable Web Testing

The article explains why smart AI still fails at complex tasks, introduces the concept of engineering‑focused Skills that embed business SOPs, and shares four hard‑learned pitfalls plus a step‑by‑step, checklist‑driven training loop that turns a generic model into a dependable, self‑checking web‑testing assistant.

AI automationChecklistgate rules
0 likes · 19 min read
How to Turn AI into an S‑Level Employee: Practical Skill Training for Reliable Web Testing
AI Architecture Hub
AI Architecture Hub
May 16, 2026 · Artificial Intelligence

9 Claude Agents That Work While You Sleep

The article presents nine night‑time Claude agents that automate tasks normally done by a chief of staff, analyst, inbox manager, engineer, finance analyst, admin, competitor analyst, content creator, and researcher, showing how to install, configure, and integrate them into a morning workflow for founders, freelancers, and managers.

AI agentsClaudeagent configuration
0 likes · 24 min read
9 Claude Agents That Work While You Sleep
Su San Talks Tech
Su San Talks Tech
May 15, 2026 · Artificial Intelligence

Step-by-Step Beginner’s Guide to Getting Started with Codex

This article walks readers through why many users are switching from Claude Code to Codex, explains the two Codex product forms, details installation, account setup, UI navigation, permission choices, and demonstrates practical tasks such as generating reports, PPTs, web searches, automation, and building a snake game via the CLI, while also offering tips to avoid common pitfalls.

AI assistantAppCLI
0 likes · 16 min read
Step-by-Step Beginner’s Guide to Getting Started with Codex
ZhiKe AI
ZhiKe AI
May 15, 2026 · Artificial Intelligence

How to Build Effective Claude Skills: Step‑by‑Step Guide, Limits, and Real Examples

This guide walks you through creating custom Claude skills—from defining a precise problem and naming conventions to crafting detailed descriptions, writing structured instructions, uploading via the UI or API, testing with realistic scenarios, iterating based on usage, and applying best‑practice tips with concrete skill examples.

AIAPIClaude
0 likes · 22 min read
How to Build Effective Claude Skills: Step‑by‑Step Guide, Limits, and Real Examples
AI Architecture Hub
AI Architecture Hub
May 15, 2026 · Artificial Intelligence

Unlock Claude's Full Potential: 18 Essential Steps

Most Claude users only tap 10% of its capabilities; this guide walks you through 18 concrete steps—creating persistent projects, crafting custom instructions, treating Claude as a thinking partner, controlling token usage, and more—to transform it into a personalized, high‑performance assistant.

AI assistantAI productivityClaude
0 likes · 15 min read
Unlock Claude's Full Potential: 18 Essential Steps
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 14, 2026 · Artificial Intelligence

How a Multi‑Agent Team Built an HTML Page in One Take (No More “Continue” Prompts)

The author used MiniMax’s new Mavis Agent Team to generate a complete, interactive HTML showcase in 28 minutes with a single prompt, illustrating how Leader‑Worker‑Verifier coordination and a Team Engine overcome the laziness, context anxiety, and silent‑agent problems of single‑agent workflows while discussing token costs and referencing the “Cost of Consensus” study.

AI agentsAgent TeamTeam Engine
0 likes · 14 min read
How a Multi‑Agent Team Built an HTML Page in One Take (No More “Continue” Prompts)
Woodpecker Software Testing
Woodpecker Software Testing
May 14, 2026 · Artificial Intelligence

From Beginner to Expert: AI‑Driven Testing of a Telecom Settlement System – Full‑Process Guide

This article analyzes the pain points of traditional manual testing for a telecom settlement system, demonstrates how AI transforms testing from passive to predictive, presents a four‑layer AI testing architecture with Git‑driven impact analysis, and compares AI‑assisted analysis with manual methods using concrete code, prompts, and risk assessments.

AI testingGit-integrationLLM
0 likes · 29 min read
From Beginner to Expert: AI‑Driven Testing of a Telecom Settlement System – Full‑Process Guide
Spring Full-Stack Practical Cases
Spring Full-Stack Practical Cases
May 14, 2026 · Artificial Intelligence

7 Advanced CLAUDE.md Tricks to Double Claude Code’s Effectiveness

This article presents seven advanced techniques for writing CLAUDE.md files—keeping them under 200 lines, optimizing the first 30 lines, separating hard rules from preferences, adding anti‑patterns, defining quality criteria, using progressive imports, and recursively scoping files—to maximize Claude Code’s productivity and reduce AI drift.

AI codingCLAUDE.mdClaude
0 likes · 7 min read
7 Advanced CLAUDE.md Tricks to Double Claude Code’s Effectiveness
High Availability Architecture
High Availability Architecture
May 14, 2026 · Artificial Intelligence

Build a 4‑Agent Claude‑Powered AI Team in One Weekend

This step‑by‑step guide shows how to create a specialized four‑agent system—research, production, quality, and distribution—coordinated by an orchestrator, using Claude and Claude Code, with detailed folder structures, prompt templates, CLI commands, and workflow automation to achieve high‑quality content output in a weekend.

AI agentsClaudeContent Workflow
0 likes · 24 min read
Build a 4‑Agent Claude‑Powered AI Team in One Weekend
Subtle Storm
Subtle Storm
May 14, 2026 · Artificial Intelligence

Boost Architecture Paper Quality Fast with AI: A Practical Step‑by‑Step Guide

The article explains why many architects struggle to turn technical ideas into well‑written papers, how AI can translate those ideas into examiner‑friendly language without replacing critical thinking, and provides a detailed, three‑step workflow—including material preparation, precise prompt engineering, and iterative refinement—to dramatically improve paper quality and efficiency.

AIexam preparationprompt engineering
0 likes · 11 min read
Boost Architecture Paper Quality Fast with AI: A Practical Step‑by‑Step Guide
AI Architecture Hub
AI Architecture Hub
May 14, 2026 · Artificial Intelligence

25 Prompt Templates to Boost Productivity with Claude, ChatGPT, and Gemini

The article provides 25 ready‑to‑copy markdown prompt templates for Claude, ChatGPT and Gemini, covering tasks such as structured note generation, exam creation, learning roadmaps, concept explanation, academic paper drafting, flashcard creation, study planning, email writing, meeting note organization, resume optimization, presentation prep, research synthesis, source validation, knowledge structuring, competitive analysis, video scripting, hook generation, flowchart building, code documentation, unit‑test generation, debugging assistance, regex building, conventional commit creation, and workflow automation.

AIChatGPTClaude
0 likes · 40 min read
25 Prompt Templates to Boost Productivity with Claude, ChatGPT, and Gemini
FunTester
FunTester
May 13, 2026 · Artificial Intelligence

Becoming an AI Collaboration Engineer: Skills, Roles, and Market Outlook

The article explains the difference between merely using AI tools and orchestrating AI systems, outlines three core responsibilities—prompt engineering for testing, AI output quality verification, and AI agent orchestration—while citing market premium data, ISTQB certification, and Gartner forecasts to illustrate the growing demand for AI collaboration engineers.

AI agent orchestrationAI collaboration engineerAI testing
0 likes · 11 min read
Becoming an AI Collaboration Engineer: Skills, Roles, and Market Outlook
Shuge Unlimited
Shuge Unlimited
May 13, 2026 · Artificial Intelligence

Karpathy’s 4 AI Coding Guidelines: 65‑Line Markdown to Eliminate Over‑Engineering

The article analyzes Karpathy’s three common LLM coding pitfalls, presents four concrete guidelines—Think Before Coding, Simplicity First, Surgical Changes, and Goal‑Driven Execution—implemented in a 65‑line Markdown file, and shows how to install and validate them across Claude Code and Cursor.

AI codingClaude CodeLLM guidelines
0 likes · 21 min read
Karpathy’s 4 AI Coding Guidelines: 65‑Line Markdown to Eliminate Over‑Engineering
Data Party THU
Data Party THU
May 13, 2026 · Artificial Intelligence

The Ultimate Anthropic Engineer’s Guide to Claude Code Skills

This guide explains what Claude Code skills are, categorizes common skill types, provides concrete examples for each category, and offers detailed best‑practice recommendations for building, testing, sharing, and managing skills within Claude’s AI ecosystem.

AI pluginsClaude CodeSkill Development
0 likes · 15 min read
The Ultimate Anthropic Engineer’s Guide to Claude Code Skills
MeowKitty Programming
MeowKitty Programming
May 12, 2026 · Backend Development

Why AI Prompt Tricks Matter Less Than a Structured Java Development Workflow

The article outlines a step‑by‑step AI‑assisted workflow for Java backend developers, emphasizing early requirement translation, using AI to map existing code, breaking implementation into tiny, well‑scoped tasks, generating risk‑focused tests, and performing a reverse review before submitting a PR, all while keeping human verification at each stage.

AIBackendcode review
0 likes · 8 min read
Why AI Prompt Tricks Matter Less Than a Structured Java Development Workflow
Linyb Geek Road
Linyb Geek Road
May 12, 2026 · Artificial Intelligence

A Comprehensive Guide to Designing Structured Prompts for AI Agents

This article explains why structured prompts are essential for AI agents, outlines their six core components, compares major frameworks such as R‑C‑S‑W‑O, Zeng Yingjie three‑stage and CRISPE, offers five optimization techniques, and provides detailed case studies on building personal prompt libraries and enterprise‑level IT policy assistants.

AI agentsCRISPECoze platform
0 likes · 35 min read
A Comprehensive Guide to Designing Structured Prompts for AI Agents
Java Architect Essentials
Java Architect Essentials
May 11, 2026 · Artificial Intelligence

How to Use GPT‑5.5: Clear Methods and Tips

The article guides newcomers on effectively using GPT‑5.5 by breaking tasks into input‑process‑output steps, comparing ChatGPT Plus and Pro, offering prompt‑crafting techniques, and outlining scenarios to consider before subscribing, all illustrated with examples and a usage‑scenario table.

AI productivityChatGPT PlusChatGPT Pro
0 likes · 6 min read
How to Use GPT‑5.5: Clear Methods and Tips
AI Step-by-Step
AI Step-by-Step
May 11, 2026 · R&D Management

Why AI‑Driven Development Must Be Spec‑Driven to Reach Production

The article explains how Spec‑Driven Development (SDD) transforms AI‑generated code from risky demos into production‑ready features by defining executable specifications, enforcing review, injecting context, and automating verification, illustrated with a concrete order‑export example.

AI codingSoftware EngineeringSpec-Driven Development
0 likes · 17 min read
Why AI‑Driven Development Must Be Spec‑Driven to Reach Production
Goodme Frontend Team
Goodme Frontend Team
May 11, 2026 · Artificial Intelligence

How Agent Skills Accelerate Backend Page Development with Claude

The article explains the concept of Agent Skills, compares them with the Model Context Protocol (MCP), and details a step‑by‑step workflow for creating and optimizing skills to generate middle‑office pages, highlighting challenges such as token consumption, code redundancy, and component matching, and presenting concrete solutions that halve generation time while improving code quality and maintainability.

AI code generationAgent SkillsBackend Development
0 likes · 16 min read
How Agent Skills Accelerate Backend Page Development with Claude
Frontend AI Walk
Frontend AI Walk
May 11, 2026 · Artificial Intelligence

From Personal Prompts to a Team Production Line: A 0‑to‑1 Guide for Skill Engineering

This article presents a step‑by‑step method for turning scattered personal prompt knowledge into versioned, testable, and shareable AI workflow assets, covering directory conventions, description design, test case creation, Bad Case feedback loops, Git management, team sharing mechanisms, and a 30‑day rollout plan.

AI workflowGitSkill Engineering
0 likes · 22 min read
From Personal Prompts to a Team Production Line: A 0‑to‑1 Guide for Skill Engineering
AI Architecture Hub
AI Architecture Hub
May 11, 2026 · Operations

Why HTML Beats Markdown for Claude Code Outputs

The article explains how using HTML instead of Markdown with Claude Code delivers richer information density, better readability, easy sharing, interactive capabilities, and deeper data ingestion despite higher token usage and longer generation time, making it a more effective format for AI‑driven documentation and workflows.

AI agentsClaude CodeHTML
0 likes · 14 min read
Why HTML Beats Markdown for Claude Code Outputs
Linyb Geek Road
Linyb Geek Road
May 11, 2026 · Artificial Intelligence

14 Reusable Agent Skill Design Patterns from Anthropic’s Official Best Practices

The article distills Anthropic’s official skill‑authoring guide into fourteen reusable design patterns—grouped into discovery, context economy, instruction calibration, workflow control, and executable code—detailing their purpose, concrete examples, applicability, and trade‑offs for building effective Claude Agent Skills.

AI AgentAgent SkillsAnthropic
0 likes · 17 min read
14 Reusable Agent Skill Design Patterns from Anthropic’s Official Best Practices
AI Architect Hub
AI Architect Hub
May 10, 2026 · Artificial Intelligence

RAG Series Recap: From Chunking to Prompt – A Complete Technical Roadmap

This article systematically reviews the nine‑stage RAG pipeline—from data cleaning and text chunking through embedding, vector indexing, retrieval, reranking, and finally prompt assembly—highlighting core concepts, practical code snippets, common pitfalls, and optimization tips for building production‑grade systems.

AILLMRAG
0 likes · 22 min read
RAG Series Recap: From Chunking to Prompt – A Complete Technical Roadmap
phodal
phodal
May 10, 2026 · Artificial Intelligence

From /goal to Long‑Running Asynchronous Agents: Making AI Sustainably Deliver Complex Tasks

By experimenting with OpenAI’s /goal feature, the author shows how to turn ad‑hoc AI prompts into a structured, long‑running loop that records progress in Git, README and test artifacts, enabling agents to handle complex engineering tasks across multiple sessions with clear checkpoints and human‑in‑the‑loop control.

AI agentsGitRalph Loop
0 likes · 12 min read
From /goal to Long‑Running Asynchronous Agents: Making AI Sustainably Deliver Complex Tasks
James' Growth Diary
James' Growth Diary
May 9, 2026 · Artificial Intelligence

Agentic RAG Deep Dive: Letting the Agent Decide When and How Often to Retrieve

The article analyzes the shortcomings of traditional one‑shot RAG pipelines, introduces four Agentic RAG patterns that let an LLM‑driven agent control retrieval strategy, source selection, query rewriting and retry limits, and provides concrete TypeScript implementations with LangGraph, code snippets, and practical pitfalls.

Agentic RAGLLMLangGraph
0 likes · 16 min read
Agentic RAG Deep Dive: Letting the Agent Decide When and How Often to Retrieve
AgentGuide
AgentGuide
May 9, 2026 · Artificial Intelligence

Interview Question: What Is Harness Engineering and How to Answer It

The article defines Harness Engineering—also called "驾驭工程"—as a set of engineering methods that create a structured environment for AI agents, addressing issues like missing context, tool access, feedback loops, and security, and contrasts it with prompt engineering while providing concrete implementation steps.

AI AgentAgent EnvironmentHarness Engineering
0 likes · 8 min read
Interview Question: What Is Harness Engineering and How to Answer It
ZhiKe AI
ZhiKe AI
May 9, 2026 · Artificial Intelligence

Why Agent Loops Matter More Than Raw Model Power

The article explains how AI agents that operate in a reasoning‑action‑observation loop outperform single‑shot LLM inference by continuously observing, planning, and correcting errors, illustrated through a ticket‑booking example and detailed analyses of ReAct, Plan‑Execute, OODA, and Steering Loop architectures.

AI agentsAgent LoopLLM
0 likes · 15 min read
Why Agent Loops Matter More Than Raw Model Power
Linyb Geek Road
Linyb Geek Road
May 9, 2026 · Artificial Intelligence

Why Overly Long Context Files Reduce AI Agent Success by 3% and Raise Token Cost 20%

The article shows that adding redundant context to AI agents like Claude harms efficiency: each extra 50 lines dilutes attention, lowers task success by about 3 % and inflates token usage by roughly 20 %, because the model’s instruction budget is capped at 150‑200 tokens, so context files must be concise and focused on non‑derivable information.

AGENTS.mdAI agentsCLAUDE.md
0 likes · 17 min read
Why Overly Long Context Files Reduce AI Agent Success by 3% and Raise Token Cost 20%
Machine Heart
Machine Heart
May 8, 2026 · Artificial Intelligence

OpenAI Launches Official CLI, Ditch the Complex SDK

The article explains how OpenAI's new openai‑cli brings AI model interaction to the terminal, eliminating the need for cumbersome SDK scripts, and details its features, workflow advantages, and broader impact on AI tooling and developer productivity.

AI automationCommand Line Interfacedeveloper workflow
0 likes · 6 min read
OpenAI Launches Official CLI, Ditch the Complex SDK
Machine Heart
Machine Heart
May 8, 2026 · Artificial Intelligence

Why ChatGPT Repeats ‘I’ll Steadily Catch You’ – Mode Collapse & Sycophancy

The article examines why ChatGPT frequently uses the phrase “I’ll steadily catch you,” linking it to mode collapse, post‑training feedback loops, and AI sycophancy, while citing WIRED coverage, a Science‑cover paper, and examples of meme propagation and a developer’s open‑source “Jiezhu” tool.

AI sycophancyChatGPTLarge Language Models
0 likes · 9 min read
Why ChatGPT Repeats ‘I’ll Steadily Catch You’ – Mode Collapse & Sycophancy
AI Architecture Hub
AI Architecture Hub
May 8, 2026 · Artificial Intelligence

Mastering Codex Commands: A Complete Beginner‑to‑Pro Guide

This guide explains how to efficiently control the Codex AI programming assistant by distinguishing its command types, presenting a step‑by‑step onboarding workflow, detailing the ten core slash commands, introducing advanced commands, and answering common questions to help developers avoid pitfalls and boost productivity.

AGENTS.mdAI programming assistantCLI workflow
0 likes · 36 min read
Mastering Codex Commands: A Complete Beginner‑to‑Pro Guide
Woodpecker Software Testing
Woodpecker Software Testing
May 7, 2026 · Artificial Intelligence

How Prompt Testing Opens a New Dimension of AI Application Performance

The article explains why prompts, now treated as a measurable software interface, become a performance bottleneck in AI-native apps, and presents a four‑quadrant methodology—including observability, quantification, attribution, and governance—plus five concrete optimization tactics backed by real‑world case studies.

A/B testingCI/CDLLM performance
0 likes · 8 min read
How Prompt Testing Opens a New Dimension of AI Application Performance
DataFunSummit
DataFunSummit
May 6, 2026 · Artificial Intelligence

Inside 1688’s Inference‑Based Recommendation System: Architecture, Challenges, and Future Directions

This article details how Alibaba 1688 tackles the “information cocoon” problem by deploying large‑model inference‑based recommendation, describing its three‑layer architecture, multi‑stage user demand analysis, long‑cycle behavior compression, prompt engineering, trend mining, near‑line serving, and future enhancements.

Multimodalbehavior compressione-commerce
0 likes · 23 min read
Inside 1688’s Inference‑Based Recommendation System: Architecture, Challenges, and Future Directions
Su San Talks Tech
Su San Talks Tech
May 6, 2026 · Information Security

What Is Prompt Injection? Attack Vectors and Defense Strategies

The article explains that Prompt injection is a new LLM security threat where attackers blur the line between instruction and data, outlines direct and indirect injection techniques—including command overriding, role‑play jailbreaks, encoding obfuscation, and multi‑turn attacks—and proposes a defense‑in‑depth framework with input filtering, prompt design, output validation, least‑privilege architecture, and specialized safeguards for RAG and agent scenarios.

AI safetyAgentLLM security
0 likes · 15 min read
What Is Prompt Injection? Attack Vectors and Defense Strategies
AI Architecture Hub
AI Architecture Hub
May 6, 2026 · Artificial Intelligence

Google’s Five Core Agent Skill Design Patterns: Elevating Agent Skills to a New Design Paradigm

The article explains how, after format standardization removed the bottleneck for enterprise AI agents, the real challenge shifted to internal logic design, and presents five reusable Agent Skill design patterns—Tool Wrapper, Generator, Reviewer, Inversion, and Pipeline—complete with code samples, typical use cases, and best‑practice guidelines for combining and selecting them.

AI agentsAgent SkillDesign Patterns
0 likes · 18 min read
Google’s Five Core Agent Skill Design Patterns: Elevating Agent Skills to a New Design Paradigm
Old Meng AI Explorer
Old Meng AI Explorer
May 5, 2026 · Artificial Intelligence

Free AI APIs That Won’t Break Your Budget: A Complete Global Guide

This article compiles a comprehensive list of free AI APIs from China and abroad, explains the three hard truths about free tiers, details each provider’s token limits, rate limits, and ideal use cases, and offers practical tips for handling rate‑limiting, key management, and fallback strategies.

AICloud AIFree API
0 likes · 21 min read
Free AI APIs That Won’t Break Your Budget: A Complete Global Guide
Architect
Architect
May 5, 2026 · Artificial Intelligence

From Anthropic to Google: Agent Skills Enter the Design‑Pattern Era

Google Cloud Tech’s recent article outlines five Agent Skill design patterns, building on Anthropic’s earlier work that standardized Skill format and loading, and shows how the community is shifting from merely defining Skill syntax to engineering robust, reusable workflow structures for AI agents.

AI EngineeringAgent SkillsDesign Patterns
0 likes · 25 min read
From Anthropic to Google: Agent Skills Enter the Design‑Pattern Era
Java Architect Essentials
Java Architect Essentials
May 5, 2026 · Artificial Intelligence

Can GPT‑5.5 Really Do Your Work? My Hands‑On Test Shows It Can

After a colleague handed me an error log, I used GPT‑5.5 to trace the problem, discovered it clarifies the troubleshooting path, and then compared ChatGPT Plus and Pro, showing how clear prompts and task intensity determine which tier truly boosts daily productivity.

AI productivityChatGPT PlusChatGPT Pro
0 likes · 6 min read
Can GPT‑5.5 Really Do Your Work? My Hands‑On Test Shows It Can
inShocking
inShocking
May 4, 2026 · Artificial Intelligence

When Claude’s Bad Schedule Made Me Laugh, I Built My First No‑Code Skill

After Claude Code produced a ridiculous daily plan, I dissected its flaws, derived five planning principles, designed a nine‑stage workflow, and created the smart‑planner skill that automatically checks weather, asks for personal constraints, breaks tasks, and delivers a human‑friendly schedule.

AI planningClaudeGitHub
0 likes · 9 min read
When Claude’s Bad Schedule Made Me Laugh, I Built My First No‑Code Skill
CodeNotes
CodeNotes
May 4, 2026 · Artificial Intelligence

What Is a Token? The Key to Understanding AI’s Billing Unit

This article explains what a token is, how it differs from characters or words, its role in AI model costs, speed, context limits, and quality, and offers practical tips for managing tokens through context engineering to control expenses and improve performance.

AITokencontext window
0 likes · 11 min read
What Is a Token? The Key to Understanding AI’s Billing Unit
DataFunTalk
DataFunTalk
May 4, 2026 · Artificial Intelligence

Engineering and Algorithm Innovations for RAG Engines in Office Applications

This article analyzes the challenges and practical solutions of building a Retrieval‑Augmented Generation (RAG) system for office scenarios, covering background issues, modular architecture, offline and online pipelines, hybrid retrieval, ranking models, knowledge filtering, prompt design, and two‑stage generation techniques.

AIKnowledge FilteringRAG
0 likes · 22 min read
Engineering and Algorithm Innovations for RAG Engines in Office Applications
AI Engineer Programming
AI Engineer Programming
May 4, 2026 · Artificial Intelligence

RAG in the Long-Context Era: Challenges, Benchmarks, and Context Engineering

The article analyzes how expanding LLM context windows to millions of tokens reshape Retrieval‑Augmented Generation, detailing chunking trade‑offs, embedding retrieval limits, attention U‑shaped distribution, benchmark results, and the emerging practice of Context Engineering for optimal end‑to‑end pipelines.

Embedding RetrievalLLMRAG
0 likes · 10 min read
RAG in the Long-Context Era: Challenges, Benchmarks, and Context Engineering
Linyb Geek Road
Linyb Geek Road
May 4, 2026 · Artificial Intelligence

Agent Principles, Architecture, and Engineering Practices for Stable AI Systems

The article breaks down the core loop of AI agents, distinguishes agents from static workflows, and presents engineering practices—such as harness testing, context management, skill loading, tool design, memory handling, multi‑agent coordination, evaluation reliability, and security—that are essential for building robust, cost‑effective agents.

AI agentsAgent ArchitectureMemory Management
0 likes · 20 min read
Agent Principles, Architecture, and Engineering Practices for Stable AI Systems
AI Explorer
AI Explorer
May 3, 2026 · Artificial Intelligence

Why a 55k‑Star Open‑Source ‘Skills’ Repo Is a Must‑Have for Engineers Working with AI

The article analyzes Matt Pocock’s highly starred open‑source “skills” repository, explaining how its lightweight Markdown‑based protocols solve common AI coding tool problems—misunderstanding intent and verbosity—by enforcing clear communication, context sharing, and a quick three‑step setup for developers.

AI codingTypeScriptdeveloper workflow
0 likes · 5 min read
Why a 55k‑Star Open‑Source ‘Skills’ Repo Is a Must‑Have for Engineers Working with AI
AI Architecture Path
AI Architecture Path
May 3, 2026 · Artificial Intelligence

How Matt Pocock’s Open‑Source ‘Skills’ Turns AI Coding from Vibe to Engineer‑Level Precision

Matt Pocock’s open‑source ‘Skills’ framework tackles four common AI‑coding pitfalls—misaligned requirements, verbose output, non‑runnable code, and architectural decay—by providing lightweight, composable skills such as deep‑questioning, domain‑language generation, test‑driven development, and architecture‑guardrails, enabling engineers to guide AI with disciplined, reproducible workflows.

AI codingMatt PocockSkills
0 likes · 15 min read
How Matt Pocock’s Open‑Source ‘Skills’ Turns AI Coding from Vibe to Engineer‑Level Precision
Smart Workplace Lab
Smart Workplace Lab
May 2, 2026 · Industry Insights

Prompt Engineer Layoffs: How to Re‑Engineer Your Career Path

As large language models mature, prompt‑writing roles are disappearing, prompting engineers to shift from crafting prompts to designing end‑to‑end AI workflows; this article outlines a three‑step system‑reconstruction protocol, common pitfalls, and practical guidelines for transitioning into workflow architecture.

AI workflowCareer TransitionLLM
0 likes · 6 min read
Prompt Engineer Layoffs: How to Re‑Engineer Your Career Path