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Knowledge Management

205 articles · Page 1 of 3
Data Bricklaying Diary
Data Bricklaying Diary
Sep 28, 2026 · Artificial Intelligence

Will Your Ontology Investment Survive the Next LLM Upgrade? A Portability Checklist

As large language models improve, enterprises must distinguish between obsolete manual ontology tasks and enduring business semantics—definitions, rules, mappings, evidence, and test cases—that should be decoupled from platforms and validated through disengagement drills to avoid vendor lock-in and ensure portable, verifiable knowledge assets.

Knowledge ManagementMigration TestingOWL 2
0 likes · 18 min read
Will Your Ontology Investment Survive the Next LLM Upgrade? A Portability Checklist
PMTalk Product Manager Community
PMTalk Product Manager Community
Sep 27, 2026 · Product Management

Beyond the Demo: Five-Layer Architecture for Production-Ready AI Products

This article argues that moving AI products from demos to reliable B2B production requires a five-layer architecture — model, knowledge, rules, system, and process — rather than just a stronger model, detailing each layer's responsibilities, three collaboration scenarios, a task definition card for requirements, cross-functional team alignment, layered acceptance criteria, and common architectural imbalances to avoid.

AI product architectureB2B AIKnowledge Management
0 likes · 17 min read
Beyond the Demo: Five-Layer Architecture for Production-Ready AI Products
Digital Planet
Digital Planet
Sep 24, 2026 · Industry Insights

AI Isn't Just Stealing Jobs: Four Ways It's Advancing Management Science

The article outlines four concrete contributions of AI to management science: raising decision-quality ceilings by overcoming bounded rationality, accelerating research via intelligent semantic extraction (Tsinghua's AI4S² framework), enabling organizational capability retention through 'one-enterprise-one-model' knowledge precipitation, and fueling indigenous Chinese management theory from local AI implementations at Lenovo, CITIC, China Merchants Bank, and Yunnan Baiyao.

AIAI4S²Chinese management theory
0 likes · 11 min read
AI Isn't Just Stealing Jobs: Four Ways It's Advancing Management Science
Frontline Investigation
Frontline Investigation
Sep 17, 2026 · R&D Management

Why Expanding Knowledge Bases Make Outdated Answers More Convincing

This article explores why updated knowledge bases often still surface outdated answers, explaining how older content's completeness and familiarity outweigh newer, conditional rules, and argues for embedding version context, applicability conditions, and source traceability into AI-generated answers to maintain trustworthiness.

Knowledge ManagementLLMNIST AI RMF
0 likes · 11 min read
Why Expanding Knowledge Bases Make Outdated Answers More Convincing
Su San Talks Tech
Su San Talks Tech
Sep 16, 2026 · Fundamentals

Build a Self-Growing Knowledge Base with WorkBuddy & Obsidian: Step-by-Step Guide

This tutorial demonstrates how to build a self-growing personal knowledge base using WorkBuddy and Obsidian, featuring a three-layer directory structure (raw, wiki, output), AI-driven incremental merging with source tracing, and a verification checklist to ensure knowledge fusion over mere accumulation.

AGENTS.mdAI-assisted note-takingKnowledge Management
0 likes · 12 min read
Build a Self-Growing Knowledge Base with WorkBuddy & Obsidian: Step-by-Step Guide
AI Large-Model Wave and Transformation Guide
AI Large-Model Wave and Transformation Guide
Sep 7, 2026 · Artificial Intelligence

Why Enterprise AI Deployments Fail: Ontologies Are the Missing Semantic Layer

Enterprises mistakenly believe that combining LLMs with RAG over internal documents creates customized AI, but chaotic, unstandardized knowledge bases cause inaccurate answers; ontologies provide the necessary semantic layer to define terms, relationships, and validation rules, making AI reliable for business-critical tasks.

AI DeploymentBusiness KnowledgeKnowledge Management
0 likes · 9 min read
Why Enterprise AI Deployments Fail: Ontologies Are the Missing Semantic Layer
Data Bricklaying Diary
Data Bricklaying Diary
Sep 7, 2026 · R&D Management

Why Enterprise AI Struggles to Adopt Frontline Experience: Build a Knowledge Collaboration Loop First

This article argues that enterprise AI projects fail not from poor ontology modeling but from lacking a knowledge collaboration loop where frontline judgments are captured with context, verified by authorized roles, transformed into testable assets, and continuously refined through operational feedback — without transferring accountability from experts.

Knowledge Managemententerprise AIfeedback loops
0 likes · 25 min read
Why Enterprise AI Struggles to Adopt Frontline Experience: Build a Knowledge Collaboration Loop First
Architects Research Society
Architects Research Society
Sep 5, 2026 · Artificial Intelligence

Why Enterprise Knowledge Isn't Just Documents for LLMs: GNOSIVELA's Knowledge Fabric

The article argues that enterprise knowledge for AI agents requires more than vector retrieval; GNOSIVELA provides a knowledge fabric that unifies documents, data, semantics, rules, and provenance with governance, distinguishing source facts, normalized knowledge, and task-specific projections to ensure explainable, permissioned, and timely knowledge access.

AI agentsAccess ControlKnowledge Management
0 likes · 6 min read
Why Enterprise Knowledge Isn't Just Documents for LLMs: GNOSIVELA's Knowledge Fabric
SpringMeng
SpringMeng
Sep 3, 2026 · Artificial Intelligence

book-to-skill: Compile Books into On-Demand Agent Skills, Cut Tokens 24-51x

The open-source book-to-skill project (12.7K GitHub stars) pre-compiles books from PDF, EPUB, DOCX, and other formats into structured, chapter-loadable Skills for AI agents, reducing context tokens by 24-51x compared to full-book loading and enabling reusable knowledge workflows for repeatedly referenced technical materials.

AI agentsKnowledge ManagementOpen Source Tools
0 likes · 10 min read
book-to-skill: Compile Books into On-Demand Agent Skills, Cut Tokens 24-51x
PMTalk Product Manager Community
PMTalk Product Manager Community
Aug 29, 2026 · Product Management

Why Most AI Products Fail: The Missing Product Architecture

The article explains that AI demos often impress, but real‑world B‑side deployments fail because relying solely on large models ignores essential layers—knowledge, rules, system integration, and workflow—so a five‑layer architecture is needed to deliver verifiable, executable business outcomes.

AI productKnowledge ManagementProduct Architecture
0 likes · 16 min read
Why Most AI Products Fail: The Missing Product Architecture
DataFunTalk
DataFunTalk
Aug 25, 2026 · Artificial Intelligence

Turning Search Tools into Enterprise Cognitive Engines with OpenClaw’s Agentic Search and Memory

The article explains how OpenClaw tackles the bottleneck of information overload in enterprise research by replacing static keyword search with an Agentic Search loop that iteratively understands, plans, executes, and learns, while Agentic Memory captures and reuses findings across sessions, creating a self‑reinforcing research flywheel.

Agentic MemoryAgentic SearchKnowledge Management
0 likes · 12 min read
Turning Search Tools into Enterprise Cognitive Engines with OpenClaw’s Agentic Search and Memory
Linyb Geek Road
Linyb Geek Road
Aug 22, 2026 · Artificial Intelligence

A Comprehensive Panorama of AI Agent Enhancement Tools

This article categorizes and reviews dozens of AI Agent enhancement tools—from reasoning assistants and coding helpers to browser automation, DevOps integrations, knowledge management, UI polishing, academic research aids, and security scanners—detailing each tool's core functions, recommended use cases, and repository links.

AI AgentDevOpsKnowledge Management
0 likes · 16 min read
A Comprehensive Panorama of AI Agent Enhancement Tools
Tencent Cloud Developer
Tencent Cloud Developer
Aug 21, 2026 · Artificial Intelligence

12 Unfiltered Observations on Working with AI

The author, an experienced backend developer, shares twelve hard‑earned observations about integrating AI into daily coding, debugging, and review workflows, highlighting the importance of an AI‑first mindset, the shift from ability to willingness, prompt engineering, human judgment, and the broader impact on teams and knowledge management.

AIBackend DevelopmentKnowledge Management
0 likes · 11 min read
12 Unfiltered Observations on Working with AI
Tencent Technical Engineering
Tencent Technical Engineering
Aug 18, 2026 · R&D Management

Never Repeat a Mistake: TencentDB Agent Memory Raises Completion from 60% to 80%

With AI agents expanding individual productivity, the authors identify a bottleneck in collaborative bandwidth and propose a three‑layer AI organization model implemented as TencentDB Agent Memory, which structures team knowledge into four asset types, validates them through extensive session analysis, and demonstrates a rise in task completion from 60% to 80% on SWE‑bench benchmarks.

AI agentsKnowledge ManagementSWE-bench
0 likes · 39 min read
Never Repeat a Mistake: TencentDB Agent Memory Raises Completion from 60% to 80%
AI Engineer Programming
AI Engineer Programming
Aug 17, 2026 · Artificial Intelligence

What Exactly Is an Enterprise Context Layer for AI?

The article analyzes the concept of an enterprise context layer for AI, breaking down its components—knowledge, expertise, and policies—into AI‑ready data, semantics, and reusable skills, and outlines the five capabilities needed to build, govern, and activate this shared corporate brain.

AIContext LayerKnowledge Management
0 likes · 23 min read
What Exactly Is an Enterprise Context Layer for AI?
Amap Tech
Amap Tech
Aug 11, 2026 · Artificial Intelligence

From Simple Q&A to Fact‑Checked Evidence: Building a Content Digital Employee at Gaode

The article details Gaode's engineering practice of creating a content‑focused digital employee that uses a structured business map, LLM‑driven wiki, and multi‑layered evidence collection to turn raw alerts or user complaints into reproducible, audit‑ready root‑cause analyses.

AI AgentBusiness MapKnowledge Management
0 likes · 26 min read
From Simple Q&A to Fact‑Checked Evidence: Building a Content Digital Employee at Gaode
Subtle Storm
Subtle Storm
Aug 10, 2026 · Fundamentals

Building a Personal Knowledge‑Base System That Turns Information Into Output

The article explains how to treat a personal knowledge base as a content‑operating system, outlining a simple folder structure, step‑by‑step workflows for ingesting, processing, and practicing information, and showing how the resulting knowledge, experience, and viewpoints can continuously fuel high‑quality content creation.

AI toolsKnowledge ManagementObsidian
0 likes · 8 min read
Building a Personal Knowledge‑Base System That Turns Information Into Output
Data Bricklaying Diary
Data Bricklaying Diary
Aug 4, 2026 · Artificial Intelligence

Enterprise Agent Experience Reuse: From Knowledge to Governed Capability Packages

This article outlines a four-step framework for converting employee expertise into reusable enterprise agent capabilities: distilling tacit knowledge into organizational knowledge, encapsulating stable task methods as Skills, connecting data and tools via MCP, and packaging them into governed capability bundles with versioning, permissions, and evaluation assets for controlled reuse and continuous improvement.

Agent GovernanceCapability PackagesKnowledge Management
0 likes · 16 min read
Enterprise Agent Experience Reuse: From Knowledge to Governed Capability Packages
Data Bricklaying Diary
Data Bricklaying Diary
Aug 3, 2026 · Artificial Intelligence

Ontology: A Modeling Mindset for Machine-Understandable Business Semantics

The article argues ontology is not a new technology but a modeling mindset that defines business objects, relationships, states, rules, and actions to create a machine-understandable semantic layer, enabling AI agents to act within explicit business constraints rather than just generating responses.

AI agentsKnowledge ManagementMBSE
0 likes · 13 min read
Ontology: A Modeling Mindset for Machine-Understandable Business Semantics
AI Large Model Application Practice
AI Large Model Application Practice
Aug 3, 2026 · Artificial Intelligence

Deep Dive into LLM Wiki Engineering: AI Coding, Obsidian Integration, and RAG Collaboration

This article explains how to build and maintain an LLM‑powered knowledge base (LLM Wiki) for AI coding agents, shows practical workflows using Obsidian and custom agents, and compares the governance‑focused Wiki approach with retrieval‑augmented generation, highlighting trade‑offs, metadata design, and integration patterns.

AI codingAgentKnowledge Management
0 likes · 16 min read
Deep Dive into LLM Wiki Engineering: AI Coding, Obsidian Integration, and RAG Collaboration
Alibaba Cloud Native
Alibaba Cloud Native
Jul 29, 2026 · Artificial Intelligence

Launching a Multi‑Agent AI Platform in One Week with Alibaba Cloud AgentTeams and AI Gateway

In just one week, XinYongZhongHe partnered with Alibaba Cloud to build an enterprise‑grade multi‑agent AI platform using AgentTeams and the AI Gateway, enabling coordinated agents, unified model governance, secure access, cost control, and a range of internal services that move AI from simple Q&A to task execution.

AI GatewayAI GovernanceAgentTeams
0 likes · 10 min read
Launching a Multi‑Agent AI Platform in One Week with Alibaba Cloud AgentTeams and AI Gateway
Big Data and Microservices
Big Data and Microservices
Jul 29, 2026 · Artificial Intelligence

How WorkBuddy + IMA Turn AI into a Real Personal Assistant

The article analyzes why ordinary chat‑based AI falls short for daily work, explains how Tencent’s WorkBuddy (a task‑execution engine) and IMA (a long‑term memory knowledge base) complement each other, and shows step‑by‑step use cases that turn AI into a truly helpful personal assistant.

AI assistantIMAKnowledge Management
0 likes · 12 min read
How WorkBuddy + IMA Turn AI into a Real Personal Assistant
IT Learning Made Simple
IT Learning Made Simple
Jul 28, 2026 · Fundamentals

Why a Mistake Notebook Beats Pure Practice for System Architecture Designers

The article explains why maintaining a mistake notebook is more effective than simply solving many questions for system‑architecture exam preparation, detailing its benefits, recommended digital and paper tools, record formats, classification schemes, step‑by‑step analysis, review schedules, and practical study techniques.

Knowledge Managementexam preparationmistake notebook
0 likes · 9 min read
Why a Mistake Notebook Beats Pure Practice for System Architecture Designers
AI Large Model Application Practice
AI Large Model Application Practice
Jul 27, 2026 · Artificial Intelligence

Deep Dive: Building Reliable Enterprise Agent Knowledge Bases with LLM Wiki & Google OKF

The article analyzes why traditional RAG pipelines struggle with reliable, exploratory queries, introduces LLM Wiki as a method for structuring raw materials into a navigable knowledge map, explains Google’s Open Knowledge Format (OKF) as an interoperable markdown specification, and outlines a six‑step agent workflow for creating and maintaining enterprise knowledge bundles.

AgentGoogle OKFKnowledge Management
0 likes · 12 min read
Deep Dive: Building Reliable Enterprise Agent Knowledge Bases with LLM Wiki & Google OKF
PMTalk Product Manager Community
PMTalk Product Manager Community
Jul 19, 2026 · Artificial Intelligence

Three Practical Ways to Turn Your Experience into Reusable AI Skills

The article explains why repeating prompts is inefficient, defines a Skill as a reusable SOP for AI, and presents three concrete methods—reverse‑engineering from results, completing a task then summarising, and writing a work‑instruction for AI optimisation—along with templates, storage tips, and real‑world Skill examples.

AI WorkflowAI toolsCodex
0 likes · 13 min read
Three Practical Ways to Turn Your Experience into Reusable AI Skills
IT Services Circle
IT Services Circle
Jul 11, 2026 · Industry Insights

Why Does AI‑Generated Code Still Leave Enterprise R&D Efficiency Stagnant?

Although AI can produce up to 60% of the code, the article explains that coding is only a small part of the software development lifecycle, and the real bottlenecks—requirements gathering, design, testing, and maintenance—prevent AI from dramatically boosting overall R&D efficiency.

AI code generationGitHub studyKnowledge Management
0 likes · 6 min read
Why Does AI‑Generated Code Still Leave Enterprise R&D Efficiency Stagnant?
AI Tech Publishing
AI Tech Publishing
Jul 10, 2026 · Artificial Intelligence

How I Collaborate with AI at Work: 5 Practical Principles

The article outlines a systematic approach to working with AI by treating context as infrastructure, encoding preferences in configuration files, front‑loading validation, progressively delegating larger tasks, and closing the feedback loop, with concrete examples of directory organization, CLAUDE.md onboarding, skill files, hooks, and session monitoring.

AI collaborationClaudeKnowledge Management
0 likes · 18 min read
How I Collaborate with AI at Work: 5 Practical Principles
Architect
Architect
Jul 9, 2026 · Artificial Intelligence

How to Capture Expert Knowledge When AI Coding Joins Your Team

When AI‑assisted coding is introduced, teams often struggle to preserve the hidden engineering expertise of top performers, so the article proposes turning that tacit know‑how into reusable, inspectable, and trim‑able Agent processes that can be documented, run, and continuously improved.

AIAgentKnowledge Management
0 likes · 22 min read
How to Capture Expert Knowledge When AI Coding Joins Your Team
Kuaishou Tech
Kuaishou Tech
Jul 8, 2026 · Artificial Intelligence

Four-Stage Evolution of Intelligent UI Test Case Generation and Execution

This article analyzes the growing pressure on software testing caused by rapid product iteration and complex business rules, then details a four‑stage evolution—from prompt‑engineered V1 to multi‑agent V2, knowledge‑enhanced V3, and agentic self‑evolving V4—showing how each stage improves generation rate, adoption, and defect coverage while outlining practical lessons for teams adopting AI‑driven testing.

AIKnowledge Managementmulti-agent systems
0 likes · 19 min read
Four-Stage Evolution of Intelligent UI Test Case Generation and Execution
Shuge Unlimited
Shuge Unlimited
Jul 3, 2026 · Artificial Intelligence

Building Karpathy’s LLM Wiki with Obsidian: Three‑Layer Architecture and Three Core Operations

This tutorial explains how to implement Andrej Karpathy’s LLM Wiki method using Obsidian, detailing a three‑layer schema‑raw‑wiki architecture, the Ingest‑Query‑Lint workflow, automatic bookkeeping that drives knowledge accumulation, and practical setup steps for personal or team use.

AI agentsGitKnowledge Management
0 likes · 23 min read
Building Karpathy’s LLM Wiki with Obsidian: Three‑Layer Architecture and Three Core Operations
Geek Labs
Geek Labs
Jul 1, 2026 · Artificial Intelligence

How AI Turns Your Obsidian Notes into a Living Second Brain

The article introduces obsidian-second-brain, an open‑source project that adds AI capabilities to Obsidian, offering 43 commands for knowledge management, code documentation, scheduling, and self‑rewriting notes, and explains how to install and use it across Claude Code, Codex, Gemini, and OpenCode.

AI IntegrationCLI toolKnowledge Management
0 likes · 7 min read
How AI Turns Your Obsidian Notes into a Living Second Brain
ZhiKe AI
ZhiKe AI
Jun 24, 2026 · R&D Management

Why Knowledge Stays Dormant? A 4‑Step Guide to Internalizing What You’ve Learned

The article explains why amassed courses, books, and articles often remain unusable, introduces the SECI model’s four knowledge‑conversion modes, illustrates each with real‑world examples—including a Panasonic bread‑maker case—and offers practical steps to turn tacit insights into actionable expertise.

Knowledge ManagementSECI modelexplicit knowledge
0 likes · 8 min read
Why Knowledge Stays Dormant? A 4‑Step Guide to Internalizing What You’ve Learned
Machine Heart
Machine Heart
Jun 24, 2026 · Industry Insights

Karpathy Backs Engram: AI Memory Startup Aiming for Persistent Enterprise Knowledge

Engram, a newly announced AI memory startup backed by investors such as General Catalyst, Kleiner Perkins, Sequoia and advisors including Andrej Karpathy, aims to move beyond temporary context retrieval by building a continuous‑learning memory layer that lets models absorb and recall enterprise‑specific knowledge, contrasting with typical RAG or long‑context methods.

AI memoryContinuous LearningKarpathy
0 likes · 6 min read
Karpathy Backs Engram: AI Memory Startup Aiming for Persistent Enterprise Knowledge
FunTester
FunTester
Jun 24, 2026 · Artificial Intelligence

What Should Claude‑mem Remember? Practical Guidelines for Effective Long‑Term Memory

The article explains that Claude‑mem’s long‑term memory should store high‑value, decision‑impacting knowledge rather than raw chat logs, outlines six categories of information worth remembering, three types to avoid, and provides concrete formats and cleanup practices to keep the memory useful for future AI‑assisted development.

AI memoryClaudeClaude-Mem
0 likes · 14 min read
What Should Claude‑mem Remember? Practical Guidelines for Effective Long‑Term Memory
DataFunSummit
DataFunSummit
Jun 22, 2026 · Industry Insights

From Old Wine to AI‑Native Teams: The Truth of Ontology Governance in AI

During a DataFunTalk roundtable, industry veterans from Huawei, Ping An and a startup dissected ontology as a management challenge, exposed the paradox that modeling pains business more than IT, warned of hidden technical debt in flashy AI projects, and shared hard‑won lessons on building AI‑Native organizations from the ground up.

AI GovernanceAI-Native OrganizationKnowledge Management
0 likes · 17 min read
From Old Wine to AI‑Native Teams: The Truth of Ontology Governance in AI
AI Tech Publishing
AI Tech Publishing
Jun 22, 2026 · Product Management

Why Product Managers Should Master Loop Engineering After Prompt Engineering

The article explains how product managers must move beyond writing better prompts to building repeatable, evidence‑driven loops that continuously improve long‑term assets such as PRD review rules, interview summarizers, and release checklists, outlining the five loop components, practical examples, and common pitfalls.

AI agentsKnowledge ManagementLoop Engineering
0 likes · 13 min read
Why Product Managers Should Master Loop Engineering After Prompt Engineering
Architect Practice
Architect Practice
Jun 21, 2026 · Fundamentals

Boost Your Learning Speed 10× with AI: A Structured Methodology

The article presents a six‑step AI‑driven system that transforms casual queries into a disciplined learning process by defining a learning path, testing knowledge, compressing material into quick reference sheets, curating high‑impact resources, and applying the Feynman loop for deep mastery.

AIEducationFeynman Technique
0 likes · 17 min read
Boost Your Learning Speed 10× with AI: A Structured Methodology
DataFunTalk
DataFunTalk
Jun 20, 2026 · Artificial Intelligence

From “New Bottle, Old Wine” to AI‑Native Organizations: What Ontology Governance Really Means for Enterprise AI

In a candid round‑table, industry veterans dissect ontology as both a technical and managerial challenge, expose the paradox of AI modeling, reveal why many AI projects become costly “highlight engineering,” compare legacy versus AI‑native organizational models, and argue that despite no silver bullet, enterprises must start their AI journey now.

AI GovernanceAI-Native OrganizationKnowledge Management
0 likes · 16 min read
From “New Bottle, Old Wine” to AI‑Native Organizations: What Ontology Governance Really Means for Enterprise AI
Alibaba Cloud Native
Alibaba Cloud Native
Jun 18, 2026 · Artificial Intelligence

A Self‑Iterating LLM Knowledge Engine Tailored for Software Engineering

The article analyzes the limitations of generic knowledge‑management tools for code, proposes a two‑step "compile‑style" knowledge pipeline (Knowledge Card → RepoWiki) that continuously self‑updates via commit‑driven and conversation‑driven flywheels, and demonstrates its superiority over LLM Wiki and GBrain through benchmark comparisons and practical integration details.

AIKnowledge ManagementLLM
0 likes · 11 min read
A Self‑Iterating LLM Knowledge Engine Tailored for Software Engineering
IoT Full-Stack Technology
IoT Full-Stack Technology
Jun 15, 2026 · Artificial Intelligence

Step‑by‑Step Guide to Building an AI‑Powered Knowledge Base with Obsidian, Claude Code, and Claudian

This article walks you through installing Obsidian, Claude Code, and the Claudian plugin, then shows how to let a large language model automatically ingest, compile, query, and maintain a markdown‑based knowledge vault, comparing the AI‑driven workflow with traditional manual methods and highlighting concrete time‑saving benefits.

AIClaudeKnowledge Management
0 likes · 10 min read
Step‑by‑Step Guide to Building an AI‑Powered Knowledge Base with Obsidian, Claude Code, and Claudian
AI Architecture Path
AI Architecture Path
Jun 15, 2026 · Artificial Intelligence

How the Open‑Source “book‑to‑skill” Tool Eliminates PDF‑AI Hallucinations and Cuts Token Costs

The article analyzes the shortcomings of feeding whole PDFs or using RAG for AI‑assisted document lookup, introduces the open‑source book‑to‑skill tool that compiles books into structured AI Skills, compares performance, token consumption and hallucination rates, and provides step‑by‑step deployment guidance.

AI DocumentationClaude CodeDocling
0 likes · 15 min read
How the Open‑Source “book‑to‑skill” Tool Eliminates PDF‑AI Hallucinations and Cuts Token Costs
ThinkingAgent
ThinkingAgent
Jun 14, 2026 · Artificial Intelligence

Ontology: The Overlooked Knowledge Infrastructure Driving AI Understanding

The article explains how ontology—a 2,500‑year‑old philosophical concept—provides the structured knowledge backbone that large language models lack, detailing its definition, differences from databases and knowledge graphs, its role in reducing hallucinations, defining knowledge boundaries, enabling reasoning, and four practical AI application scenarios.

AI agentsKnowledge ManagementRAG
0 likes · 17 min read
Ontology: The Overlooked Knowledge Infrastructure Driving AI Understanding
DataFunTalk
DataFunTalk
Jun 9, 2026 · Artificial Intelligence

Anthropic’s Internal Claude Code Skills: 9 Types, Key Practices, and Writing Tips

Anthropic reveals how its teams use Claude Code Skills, classifying them into nine functional categories, emphasizing verification and focus, and sharing concrete guidelines for structuring SKILL.md, progressive disclosure, memory, scripts, hooks, distribution, composition, and usage measurement.

AI automationClaude CodeKnowledge Management
0 likes · 15 min read
Anthropic’s Internal Claude Code Skills: 9 Types, Key Practices, and Writing Tips
Old Zhang's AI Learning
Old Zhang's AI Learning
Jun 6, 2026 · Artificial Intelligence

How to Build a Personal Knowledge Base with My Custom web‑pack Skill

This article explains how to construct a personal knowledge base using the author’s open‑source web‑pack Skill, which automates raw material collection, image localization, link expansion, and structured output, addressing the limitations of Obsidian’s Web Clipper and aligning with Karpathy’s LLM Wiki three‑layer architecture.

AI agentsKnowledge ManagementLLM
0 likes · 9 min read
How to Build a Personal Knowledge Base with My Custom web‑pack Skill
Yunqi AI+
Yunqi AI+
Jun 4, 2026 · Industry Insights

How AI Adoption Is Redefining Middle Management: From Experience to Capability Building

The article analyzes how enterprise AI rollout transforms middle managers from traditional experience‑based overseers into architects of reusable organizational capabilities such as Skills and Agents, reshaping responsibilities, decision‑making and the overall structure of the company.

AI AdoptionAgent engineerKnowledge Management
0 likes · 11 min read
How AI Adoption Is Redefining Middle Management: From Experience to Capability Building
AI Engineering
AI Engineering
Jun 2, 2026 · Artificial Intelligence

Why Your Enterprise AI Looks Impressive Yet Produces Garbage Results

Even with the world’s best large language models, chaotic internal notes, calls, and processes turn enterprise AI output into junk; a five‑layer architecture—capture, retrieval, source‑truth, permission, and feedback—plus a six‑question test can turn a noisy "company brain" into a useful tool, as shown by Single Grain’s dramatic time‑saving results.

AI architectureFeedback LoopKnowledge Management
0 likes · 7 min read
Why Your Enterprise AI Looks Impressive Yet Produces Garbage Results
Linyb Geek Road
Linyb Geek Road
Jun 1, 2026 · Artificial Intelligence

Why Knowledge, Not Harness, Is the Real Moat: Designing a Layered Knowledge Architecture for AI Engineering Teams

The article explains how an AI engineering team turned the hype around Harness Engineering into a sustainable competitive edge by building a multi‑layered, Git‑backed knowledge repository, defining knowledge types and maturity, integrating it with a 16‑stage workflow, and solving human‑machine interaction bottlenecks with remote‑control tools.

AI EngineeringGitHarness Engineering
0 likes · 32 min read
Why Knowledge, Not Harness, Is the Real Moat: Designing a Layered Knowledge Architecture for AI Engineering Teams
SuanNi
SuanNi
May 27, 2026 · Artificial Intelligence

Key Use Cases and Deployment Guide for OpenClaw Autonomous Agents

The article outlines the core application scenarios of OpenClaw autonomous agents—from personal productivity tools and DevOps assistants to business operations, research workflows, and industry‑specific solutions—provides detailed case studies, step‑by‑step deployment instructions, security configurations, and best‑practice recommendations for effective implementation.

AI automationDevOpsKnowledge Management
0 likes · 14 min read
Key Use Cases and Deployment Guide for OpenClaw Autonomous Agents
Code Mala Tang
Code Mala Tang
May 26, 2026 · Industry Insights

Turning Your Company into an AI Operating System: Insights from YC’s Two Videos

The article analyzes YC’s two videos on AI‑native companies, showing how AI can be re‑engineered as a company‑wide operating system with four layered components, recursive self‑improving loops, and practical steps for founders to transform workflows, decision‑making and organizational structure.

AI-nativeKnowledge ManagementYC
0 likes · 24 min read
Turning Your Company into an AI Operating System: Insights from YC’s Two Videos
James' Growth Diary
James' Growth Diary
May 25, 2026 · Artificial Intelligence

How Agents Turn a Single Success into a Reusable Skill

The article explains how Hermes separates memory from skills, automatically creates structured SKILL.md files from successful interactions, prioritizes updates over new creations, manages supporting files, tracks usage, and compares its approach with other agent frameworks, offering a detailed, code‑driven walkthrough of the entire skill‑generation pipeline.

AIAgentHermes
0 likes · 16 min read
How Agents Turn a Single Success into a Reusable Skill
Ubiquitous Tech
Ubiquitous Tech
May 24, 2026 · Operations

Generate AI‑Friendly Project Wiki Docs with Zread: A Practical Guide

This article explains why large codebases are hard to understand, introduces Zread CLI as a tool that converts a repository into searchable, AI‑readable wiki documentation, and walks through installation, configuration, and real‑world usage with step‑by‑step examples.

AI DocumentationAI codingCLI
0 likes · 13 min read
Generate AI‑Friendly Project Wiki Docs with Zread: A Practical Guide
AI Waka
AI Waka
May 22, 2026 · Artificial Intelligence

How Powerful Is Karpathy’s LLM Wiki? An Ontology and VSM Analysis

The article examines how the ease of building AI systems shifts the challenge from construction to defining what is built, using ontology’s five perspectives and the Viable System Model to diagnose Karpathy’s LLM Wiki, revealing strengths in entity‑level design and gaps in process and purpose.

Knowledge ManagementLLM WikiVSM
0 likes · 10 min read
How Powerful Is Karpathy’s LLM Wiki? An Ontology and VSM Analysis
Tech Ocean
Tech Ocean
May 18, 2026 · Artificial Intelligence

Create Your Own AI Skill: Turn Business Processes into Reusable Instruction Templates

The article explains why teams should codify recurring workflows as Claude Code Skills, outlines three guiding principles, provides a detailed four‑step creation guide with concrete examples, shares a real‑world case, warns about common pitfalls, and shows how Skills become a version‑controlled knowledge asset.

AIClaude CodeKnowledge Management
0 likes · 9 min read
Create Your Own AI Skill: Turn Business Processes into Reusable Instruction Templates
Wuming AI
Wuming AI
May 17, 2026 · Industry Insights

Beyond Prompts: Building Real AI‑Powered Competitive Barriers

The article reflects on an Alibaba Cloud AI productivity roundtable, summarizing speakers' insights on how AI can expand personal capability, automate expert workflows, and create lasting competitive advantages that depend on integrating industry knowledge, judgment, and execution rather than merely using tools.

AI IntegrationAI productivityKnowledge Management
0 likes · 12 min read
Beyond Prompts: Building Real AI‑Powered Competitive Barriers
Java Tech Enthusiast
Java Tech Enthusiast
May 17, 2026 · Industry Insights

Which Note‑Taking Apps Do Top Developers and Teams Prefer?

This article reviews a wide range of note‑taking applications, categorising them for team knowledge bases, personal long‑term knowledge management and quick‑capture scenarios, and summarises each tool’s core features, strengths, weaknesses and the types of users it best serves.

Knowledge Managementnote-takingproductivity
0 likes · 12 min read
Which Note‑Taking Apps Do Top Developers and Teams Prefer?
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
DeepNoMind
DeepNoMind
May 1, 2026 · Artificial Intelligence

Accelerate Any Topic Learning with AI: 6 Practical Workflows

The article explains how to combine AI tools such as Perplexity, NotebookLM, ChatGPT, and Gemini into six concrete workflows—resource discovery, video‑to‑notes conversion, deep research, guided learning, visualisation, and active recall—to study faster, retain longer, and turn information into usable knowledge.

AI learning workflowChatGPTGemini
0 likes · 12 min read
Accelerate Any Topic Learning with AI: 6 Practical Workflows
Yunqi AI+
Yunqi AI+
Apr 29, 2026 · R&D Management

How to Reverse Engineer Legacy Systems for Reliable AI Coding

The article outlines a systematic reverse‑engineering process for legacy systems that extracts factual system knowledge, organizes it into AI‑consumable context, and integrates the workflow into a continuous delivery loop to improve AI draft accuracy and team cognition.

AI codingKnowledge Managementlegacy systems
0 likes · 14 min read
How to Reverse Engineer Legacy Systems for Reliable AI Coding
Kuaishou Tech
Kuaishou Tech
Apr 29, 2026 · Operations

Boosting Oncall Interception from 15% to 55%: KOncall’s AI‑Driven Evolution at Kuaishou

Kuaishou’s R&D efficiency team built the KOncall intelligent on‑call platform, integrating LLM‑based retrieval‑augmented generation, Redis Pub/Sub streaming, OCR multimodal parsing, FAQ knowledge ops, and custom reranking, which raised automated query interception from 15% to 55% and processed over 116 000 requests, turning on‑call from a bottleneck into a capability starter.

AI operationsKnowledge ManagementLLM
0 likes · 26 min read
Boosting Oncall Interception from 15% to 55%: KOncall’s AI‑Driven Evolution at Kuaishou
Geek Labs
Geek Labs
Apr 29, 2026 · Industry Insights

Practical Open‑Source Projects: Book‑to‑Skill Conversion, Markdown Visualization, and Modern CLI Tools

This article reviews five open‑source projects—cangjie‑skill, mdv, MD‑This‑Page, awesome‑modern‑cli, and OpenAI Codex—detailing their core features, typical use cases, and quick‑start commands to help developers streamline knowledge management, data visualization, web‑to‑Markdown conversion, command‑line productivity, and AI‑assisted coding.

AI SkillsCLIKnowledge Management
0 likes · 10 min read
Practical Open‑Source Projects: Book‑to‑Skill Conversion, Markdown Visualization, and Modern CLI Tools
SuanNi
SuanNi
Apr 28, 2026 · Artificial Intelligence

Why Your AI Agent Fails and How Skills Can Fix It

The article argues that monolithic AI agents suffer from stability, extensibility, and knowledge‑retention problems, and proposes a modular "Skills" architecture—analogous to a microkernel OS—that turns expertise into reusable, version‑controlled assets, enabling cross‑platform deployment, better human‑AI collaboration, and reshaping the labor market.

AI agentsKnowledge Managementcross‑platform AI
0 likes · 8 min read
Why Your AI Agent Fails and How Skills Can Fix It
AI Cyberspace
AI Cyberspace
Apr 28, 2026 · Artificial Intelligence

How Karpathy’s LLM‑Wiki Turns LLMs into a Self‑Growing Personal Knowledge Base

The article critiques traditional RAG‑based knowledge bases for lacking persistence, then details Karpathy’s LLM‑wiki approach that incrementally builds a structured, cross‑linked Markdown wiki through three layers, three core operations, and lightweight indexing, enabling continuous, low‑cost knowledge accumulation.

AI agentsKnowledge ManagementLLM
0 likes · 18 min read
How Karpathy’s LLM‑Wiki Turns LLMs into a Self‑Growing Personal Knowledge Base
Node.js Tech Stack
Node.js Tech Stack
Apr 28, 2026 · Artificial Intelligence

Turn Your Article Collection into an LLM‑Powered Wiki with a Single Skill

This article walks through using the youdaonote‑llm‑wiki skill to automatically ingest a set of Markdown articles into a cloud‑synced Youdao Note knowledge base, generate structured Wiki pages, perform cross‑document queries with citations, and keep the repository up‑to‑date, while comparing it to Karpathy's original script‑based approach.

AI agentsKnowledge ManagementLLM Wiki
0 likes · 14 min read
Turn Your Article Collection into an LLM‑Powered Wiki with a Single Skill
Tech Architecture Stories
Tech Architecture Stories
Apr 23, 2026 · R&D Management

How I Built My Own Local LLM Wiki Inspired by Karpathy’s Idea

The article details a five‑layer architecture for a sustainable local knowledge vault—Inbox, Raw Sources, Extracted Text, Distilled, and Archive—explaining each layer’s purpose, the import workflow from tools like Evernote, and the supporting Python scripts that automate ingestion, extraction, and governance.

AI automationKnowledge ManagementLLM Wiki
0 likes · 14 min read
How I Built My Own Local LLM Wiki Inspired by Karpathy’s Idea
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Apr 22, 2026 · Artificial Intelligence

Hands‑On Kimi K2.6 + Hermes: A Karpathy‑Style Step‑by‑Step Guide

This article presents a detailed, hands‑on tutorial for deploying Kimi K2.6 with Hermes and Obsidian, showcases multi‑modal video note‑taking, skill creation, self‑evolving LLM‑driven knowledge bases, large‑scale agent clusters, and discusses both the strengths and current limitations of the system.

Agent SystemsHermesKimi K2.6
0 likes · 10 min read
Hands‑On Kimi K2.6 + Hermes: A Karpathy‑Style Step‑by‑Step Guide
AI Illustrated Series
AI Illustrated Series
Apr 22, 2026 · Artificial Intelligence

Mastering AI Agent Skills: From Concept to Hands‑On Implementation

This guide explains what Agent Skills are, how they differ from traditional prompts, the three core design mechanisms, step‑by‑step creation of a Skill—including file structure, YAML metadata, and markdown instructions—plus advanced tips, real‑world use cases, and troubleshooting advice.

AI agentsAgent SkillsKnowledge Management
0 likes · 30 min read
Mastering AI Agent Skills: From Concept to Hands‑On Implementation
DeepNoMind
DeepNoMind
Apr 19, 2026 · Industry Insights

How to Thrive in the AI Era: 5 Must‑Have Skills for 2026

The article outlines five core AI competencies needed in 2026—workflow automation, agent‑based systems, AI safety, self‑augmentation, and AI system evaluation—explaining why they matter, how to acquire them with tools like Zapier, n8n, Claude Cowork and custom GPTs, and how they keep professionals competitive.

AIAI safetyAgent Systems
0 likes · 10 min read
How to Thrive in the AI Era: 5 Must‑Have Skills for 2026
AI Architecture Hub
AI Architecture Hub
Apr 18, 2026 · Artificial Intelligence

Build a Dual‑Layer AI Knowledge Base in 20 Minutes and Supercharge Your LLM Agents

This article explains how to create a two‑layer AI knowledge system— a dynamic Knowledge Base Layer and a static Brand Foundation Layer— in about 20 minutes, detailing its architecture, advantages over traditional RAG, step‑by‑step deployment, and real‑world use cases for creators, teams, and personal productivity.

AI Knowledge BaseGitKnowledge Management
0 likes · 16 min read
Build a Dual‑Layer AI Knowledge Base in 20 Minutes and Supercharge Your LLM Agents
Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 17, 2026 · Artificial Intelligence

Four Powerful Projects to Supercharge Your Claude Code

This article reviews four high‑quality open‑source Claude Code ecosystem projects—Everything Claude Code, GacUI CLAUDE.md, Waza, and Ars Contexta—detailing their core capabilities, installation steps, unique workflows, and practical recommendations for different developer needs.

AI AgentClaude CodeKnowledge Management
0 likes · 13 min read
Four Powerful Projects to Supercharge Your Claude Code
AI Waka
AI Waka
Apr 16, 2026 · Artificial Intelligence

Why Modern AI Systems Should Compile Knowledge Instead of Just Retrieving It

Traditional RAG pipelines forget everything after each query, but the LLM Wiki mode proposed by Andrej Karpathy compiles source material into a version‑controlled, cross‑referenced Markdown wiki, enabling knowledge to compound over time, reduce query costs, and provide a transparent, human‑readable knowledge base for AI engineers.

AI EngineeringKnowledge ManagementLLM
0 likes · 23 min read
Why Modern AI Systems Should Compile Knowledge Instead of Just Retrieving It
AI Software Product Manager
AI Software Product Manager
Apr 16, 2026 · Artificial Intelligence

How to Leverage Google NotebookLM for Efficient Research and Summaries

Google NotebookLM, powered by Gemini, lets you upload PDFs, web pages, and other documents, automatically extracts their content, and answers questions with citations, while also generating audio overviews and PPTs, making research, report writing, and exam preparation faster and more reliable.

AI research toolArtificial IntelligenceAudio Overview
0 likes · 11 min read
How to Leverage Google NotebookLM for Efficient Research and Summaries
Frontend AI Walk
Frontend AI Walk
Apr 14, 2026 · Artificial Intelligence

Connecting Claude and Obsidian: Two Integration Paths for a Reusable Writing Workflow

This guide details two ways to integrate Claude with Obsidian—direct MCP connection (about 30 minutes to set up) and a Karpathy‑inspired LLM Wiki workflow (raw→wiki→drafts)—including full configuration steps, a CLAUDE.md template, three core commands, and tips for turning raw notes into structured, publishable drafts.

AI writingClaudeKnowledge Management
0 likes · 17 min read
Connecting Claude and Obsidian: Two Integration Paths for a Reusable Writing Workflow
AI Architecture Hub
AI Architecture Hub
Apr 12, 2026 · Product Management

How One PM Can Power a 20‑Person Team with an AI‑Driven Collaboration System

This article analyzes a PM‑centric AI collaboration framework that consolidates scattered knowledge, reduces repetitive interruptions, and enables a single product manager to efficiently support a twenty‑person team by structuring context, optimizing prompt usage, and standardizing workflows across product, engineering, design, and operations.

AI collaborationKnowledge ManagementProduct Management
0 likes · 9 min read
How One PM Can Power a 20‑Person Team with an AI‑Driven Collaboration System
inShocking
inShocking
Apr 8, 2026 · Artificial Intelligence

Build Your Own Personal LLM Wiki (No RAG) – A Step‑by‑Step Guide

This article walks through how to assemble a personal LLM‑driven wiki using Claude Code, Obsidian, and the open‑source qmd search engine, detailing the directory layout, CLAUDE.md workflow spec, ingestion/query/health‑check cycles, and how the approach can be extended for enterprise knowledge bases.

AI agentsClaude CodeEnterprise Wiki
0 likes · 12 min read
Build Your Own Personal LLM Wiki (No RAG) – A Step‑by‑Step Guide
AI Software Product Manager
AI Software Product Manager
Apr 7, 2026 · Fundamentals

Master Obsidian: A Complete Guide to Local Knowledge Management and Plugins

This article provides a comprehensive overview of Obsidian, covering its core features, use cases, installation steps, essential concepts like vaults and backlinks, a range of useful plugins, skill imports, and practical workflows such as AI‑driven newsletter automation and turning ideas into actionable projects.

Bidirectional linksKnowledge ManagementObsidian
0 likes · 8 min read
Master Obsidian: A Complete Guide to Local Knowledge Management and Plugins
Smart Workplace Lab
Smart Workplace Lab
Apr 7, 2026 · Industry Insights

Boost Workplace Efficiency with AI Agents: 10 Real-World SECI Use Cases

This guide outlines ten practical SECI‑based workflows that combine human expertise with AI agents and tools such as CrewAI, Claude 3.5, LangGraph, and AutoGen to dramatically cut task time, improve accuracy, and embed tacit knowledge across functions from competitive analysis to risk management.

AI agentsKnowledge ManagementSECI process
0 likes · 9 min read
Boost Workplace Efficiency with AI Agents: 10 Real-World SECI Use Cases
Youzan Coder
Youzan Coder
Apr 7, 2026 · Industry Insights

How a Structured Knowledge Wiki Supercharges AI Coding Efficiency

This article analyzes why building a layered knowledge wiki tied to workspace and Git submodules dramatically reduces context entropy for AI coding, outlines the five knowledge categories, progressive disclosure design, multi‑agent initialization workflow, and the measurable productivity gains and governance benefits achieved in practice.

AI codingKnowledge ManagementWiki
0 likes · 24 min read
How a Structured Knowledge Wiki Supercharges AI Coding Efficiency
AI Programming Lab
AI Programming Lab
Apr 7, 2026 · R&D Management

How I Built a One‑Stop Content Creation Engine with Claude Code and Obsidian

The author describes a step‑by‑step workflow that combines Claude Code and Obsidian—using Canvas for topic planning, defuddle for research, a Git‑backed vault for version control, Base views for article tracking, and custom Skills for drafting—to dramatically cut research time, avoid duplicate content, and create a self‑reinforcing knowledge base.

AI writingClaude CodeContent Workflow
0 likes · 10 min read
How I Built a One‑Stop Content Creation Engine with Claude Code and Obsidian
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Apr 5, 2026 · Artificial Intelligence

Why Karpathy’s LLM Wiki Is Sparking a New Way to Build Knowledge

Karpathy’s LLM Wiki proposes a meta‑framework that lets large language models continuously compile, update, and query a structured Markdown wiki, moving beyond traditional RAG by treating ideas as reusable assets that agents can automatically materialize into personal knowledge bases.

AI agentsKnowledge ManagementLLM
0 likes · 11 min read
Why Karpathy’s LLM Wiki Is Sparking a New Way to Build Knowledge
Machine Heart
Machine Heart
Apr 5, 2026 · Artificial Intelligence

Why Karpathy’s LLM Wiki Is Sparking a New Knowledge‑Building Approach

Karpathy’s recently released LLM Wiki, shared as a gist, demonstrates a meta‑framework where raw documents are ingested, an LLM compiles a structured, cross‑linked Markdown wiki, and agents continuously update, query, and health‑check it, offering a scalable alternative to traditional RAG pipelines.

AgentKnowledge ManagementLLM
0 likes · 11 min read
Why Karpathy’s LLM Wiki Is Sparking a New Knowledge‑Building Approach
Old Zhang's AI Learning
Old Zhang's AI Learning
Apr 5, 2026 · Artificial Intelligence

LLM‑Powered Knowledge Management: Insights from Karpathy, Lex Fridman, and kepano

The article analyzes three leading AI experts' approaches to personal knowledge management—Karpathy’s five‑module LLM pipeline, Lex Fridman’s interactive voice‑driven consumption, and kepano’s cautionary separation of AI‑generated content—while detailing the author’s own downstream content‑production workflow that turns raw material into articles, videos, and social posts.

AI agentsContent ProductionKnowledge Management
0 likes · 13 min read
LLM‑Powered Knowledge Management: Insights from Karpathy, Lex Fridman, and kepano
ShiZhen AI
ShiZhen AI
Apr 4, 2026 · Artificial Intelligence

Why Sharing Ideas Beats Sharing Code: Karpathy’s LLM‑Powered Wiki Workflow

Karpathy demonstrates a three‑layer LLM‑driven Wiki that ingests raw papers, code and datasets, automatically maintains structured markdown, and continuously improves through ingest, query and lint cycles, offering a compounding knowledge base that differs fundamentally from traditional RAG retrieval.

AI agentsKnowledge ManagementLLM
0 likes · 10 min read
Why Sharing Ideas Beats Sharing Code: Karpathy’s LLM‑Powered Wiki Workflow
o-ai.tech
o-ai.tech
Apr 1, 2026 · Artificial Intelligence

How CE Turns Engineering Experience into a Compound, Reusable System

CE proposes that instead of storing experience only in chat logs, an agent system should convert it into consumable, maintainable, refreshable, and discoverable assets, organized into three durable artifact layers—brainstorms, plans, and solutions—so that future tasks become easier, faster, and less error‑prone.

AI agentsCompound EngineeringKnowledge Management
0 likes · 19 min read
How CE Turns Engineering Experience into a Compound, Reusable System
Wuming AI
Wuming AI
Mar 29, 2026 · Industry Insights

Turning Docs into AI‑Callable Skills: A Practical Shift to AI‑First Workflows

The article argues that merely sharing AI prompts and tool lists is insufficient; instead, documentation and tools must be transformed into AI‑friendly, callable skills, illustrating the shift with concrete OpenClaw and CoPaw examples that enable self‑healing, redundancy, and truly automated workflows.

AI WorkflowKnowledge Managementautomation
0 likes · 8 min read
Turning Docs into AI‑Callable Skills: A Practical Shift to AI‑First Workflows
AI Code to Success
AI Code to Success
Mar 26, 2026 · R&D Management

Turn Obsidian + Claude Code into a Cross‑Project Knowledge Engine

This guide explains how to overcome single‑project memory limits by combining Obsidian as a second brain with Claude Code's project‑level memory and a custom PM workspace, providing a structured, automated system for storing, syncing, and reusing knowledge across multiple development projects.

Claude CodeKnowledge ManagementObsidian
0 likes · 11 min read
Turn Obsidian + Claude Code into a Cross‑Project Knowledge Engine
Tencent Tech
Tencent Tech
Mar 24, 2026 · Artificial Intelligence

Unlocking AI Power: How Skill Packages Transform Large Language Models

This article provides a comprehensive technical guide to Skill packages—standardized knowledge containers that give large language models expert-level execution capabilities—covering their definition, architecture, integration with the Model Context Protocol (MCP), creation workflow, best‑practice tips, collaborative patterns, debugging strategies, philosophical implications, and future directions.

AI toolingKnowledge ManagementLLM
0 likes · 18 min read
Unlocking AI Power: How Skill Packages Transform Large Language Models
AI Step-by-Step
AI Step-by-Step
Mar 22, 2026 · Artificial Intelligence

Why Harness Engineering Is the Key to Stable Agent Loops

The article explains that while an Agent Loop can execute tasks, long‑running stability depends on a well‑designed Harness engineering layer that organizes knowledge, enforces rules, provides verification, and automates cleanup, turning a functional prototype into a reliable production system.

AI agentsAgent LoopHarness Engineering
0 likes · 10 min read
Why Harness Engineering Is the Key to Stable Agent Loops
LouZai
LouZai
Mar 20, 2026 · Artificial Intelligence

How I Built a Multi‑Agent Personal AI System with OpenClaw

The article walks through the author's step‑by‑step design and deployment of a layered, multi‑agent personal AI system using OpenClaw, covering problem motivation, role decomposition, implementation pitfalls, and concrete examples such as health tracking and knowledge management.

Agent ArchitectureKnowledge ManagementOpenClaw
0 likes · 7 min read
How I Built a Multi‑Agent Personal AI System with OpenClaw
Old Zhang's AI Learning
Old Zhang's AI Learning
Mar 15, 2026 · Artificial Intelligence

How Claude Code + Obsidian Automate Your Knowledge Management

Claude Code can read your project’s code, git history, and structure, then automatically create or update Obsidian notes, generate dev logs, and even produce architecture Canvas files with a single /obsidian command, offering a local‑first, plugin‑free workflow for AI‑driven knowledge management.

AI automationCanvasClaude Code
0 likes · 10 min read
How Claude Code + Obsidian Automate Your Knowledge Management
Yunqi AI+
Yunqi AI+
Mar 14, 2026 · Industry Insights

Why Building an AI Knowledge Base Becomes an All‑Hands Initiative Once AI Goes Deep

The article explains how scaling AI agents reveals fragmented, inconsistent internal documentation, and argues that high‑quality production knowledge bases require a company‑wide, role‑based process, concrete writing rules, continuous inspection, and cross‑department ownership to ensure AI answers remain accurate and user‑focused.

AI DeploymentAI Knowledge BaseData Quality
0 likes · 14 min read
Why Building an AI Knowledge Base Becomes an All‑Hands Initiative Once AI Goes Deep
FunTester
FunTester
Mar 12, 2026 · R&D Management

From Service Desk to Coach: Turning Support into Sustainable Knowledge Assets

The article explains how shifting from a reactive, ticket‑based support role to a proactive coaching model reduces repetitive issues by identifying patterns, structuring knowledge, building reusable rules, and allocating dedicated time for systematic improvement, ultimately turning support work into lasting assets.

Knowledge Managementcoachingprocess-improvement
0 likes · 12 min read
From Service Desk to Coach: Turning Support into Sustainable Knowledge Assets