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AI Large Model Application Practice
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AI Large Model Application Practice

Focused on deep research and development of large-model applications. Authors of "RAG Application Development and Optimization Based on Large Models" and "MCP Principles Unveiled and Development Guide". Primarily B2B, with B2C as a supplement.

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Recent Articles

Latest from AI Large Model Application Practice

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AI Large Model Application Practice
AI Large Model Application Practice
Apr 1, 2026 · Artificial Intelligence

What the Claude Code Leak Reveals About Anthropic’s AI Agent Architecture

An accidental front‑end misconfiguration exposed 512,000 lines of Claude Code’s TypeScript source, unveiling Anthropic’s modular AI agent architecture, hidden “Buddy” pet system, the KAIROS autonomous mode, undercover stealth features, anti‑distillation defenses, and risky YOLO permissions, offering a rare, detailed glimpse into cutting‑edge generative‑AI engineering.

AI agentAnthropicArchitecture
0 likes · 13 min read
What the Claude Code Leak Reveals About Anthropic’s AI Agent Architecture
AI Large Model Application Practice
AI Large Model Application Practice
Mar 30, 2026 · Artificial Intelligence

Why Agent Harnesses Are the Key to Production‑Ready AI Agents

The article analyzes the emerging concept of Agent Harnesses, explaining how they transform unruly large‑model agents into controllable, production‑grade systems by addressing long‑running tasks, legacy code complexity, execution‑delivery gaps, and safety concerns through systematic engineering practices.

AI engineeringAutomationagent harness
0 likes · 18 min read
Why Agent Harnesses Are the Key to Production‑Ready AI Agents
AI Large Model Application Practice
AI Large Model Application Practice
Mar 23, 2026 · Artificial Intelligence

Turning OpenClaw into a Secure, Scalable Enterprise AI Platform

This article explores how to engineer OpenClaw from a personal desktop assistant into a controllable, enterprise‑grade AI productivity platform by addressing multi‑tenant architecture, security safeguards, application integration, skill asset management, cost governance, and operational monitoring.

Cost ManagementEnterprise AIOpenClaw
0 likes · 16 min read
Turning OpenClaw into a Secure, Scalable Enterprise AI Platform
AI Large Model Application Practice
AI Large Model Application Practice
Mar 2, 2026 · Artificial Intelligence

How to Build Your First Business Ontology for AI Agents – A Step‑by‑Step Guide

This article walks you through why enterprise AI agents need a semantic ontology, explains TBox and ABox concepts, outlines a general modeling workflow, introduces RDF/OWL standards and tools like Protégé and reasoners, and provides a hands‑on example—including Python code with Owlready2—to create and test a business ontology for order‑expedition rules.

Knowledge GraphOWLOntology
0 likes · 18 min read
How to Build Your First Business Ontology for AI Agents – A Step‑by‑Step Guide
AI Large Model Application Practice
AI Large Model Application Practice
Feb 19, 2026 · Artificial Intelligence

When Should You Add a Knowledge Graph? 6 Practical Decision Criteria

This article outlines six concrete criteria—relationship‑centric data, reproducible reasoning, evolving schemas, multi‑hop queries, explainable decisions, and cross‑system data integration—to help engineers decide whether a knowledge graph is the right solution or if a relational database will suffice.

AI engineeringKnowledge Graphdata integration
0 likes · 15 min read
When Should You Add a Knowledge Graph? 6 Practical Decision Criteria
AI Large Model Application Practice
AI Large Model Application Practice
Feb 10, 2026 · Artificial Intelligence

How OpenClaw Secures Production‑Grade AI Agents with Zero‑Trust Tool Policies

This article dissects OpenClaw’s engineering techniques for building robust, production‑level AI agents, covering zero‑trust tool policies for security, markdown‑based memory management, cost‑aware reasoning levels, and controlled sub‑agent collaboration to ensure safety, efficiency, and reliability.

AI AgentsMemory ManagementSecurity
0 likes · 12 min read
How OpenClaw Secures Production‑Grade AI Agents with Zero‑Trust Tool Policies
AI Large Model Application Practice
AI Large Model Application Practice
Jan 26, 2026 · Artificial Intelligence

Why Enterprise AI Agents Fail and How Ontology Can Fix Them

This article examines why most enterprise AI agents stumble—due to hallucinations, semantic mismatches, and lack of explainability—then introduces ontology as a semantic layer that structures business concepts, rules, and constraints to enable reliable reasoning, centralized rule management, and transparent AI behavior.

AgentOntologyenterprise-ai
0 likes · 17 min read
Why Enterprise AI Agents Fail and How Ontology Can Fix Them