25 related articles
TutorialsDeep dive into Claude Code Hooks: why CLAUDE.md rules fail, and how PreCommand blocking, PostCommand reminders, and Stop Hooks form a reliable AI behavior constraint system.
TutorialsDeep dive into Claude Code Hooks: why CLAUDE.md rules fail and how PreCommand, PostCommand, and Stop Hooks provide a reliable safety net through on-demand context injection.
TutorialsDeep analysis of Prompt Engineering core methodology: from LLM principles to the three key principles of specific, rich, and unambiguous prompts, plus programming advantages in the AI era.
TutorialsHow Hooks+Skills+Commands+Agents work together in Claude Code to boost AI skill activation from 25% to 90%, with core config files and deployment guide.
TutorialsAI answers always off-track? The problem isn't the model — it's your input. Learn how context compilation scripts transform scattered materials into structured task context, boosting AI output quality from 2 to 90 points.
TutorialsWhy does AI always give irrelevant answers? This article explains prompt engineering fundamentals from the probabilistic prediction principles of LLMs, teaching you how to communicate effectively with AI.
Expert OpinionsAs AI coding tools take center stage, natural language skills are replacing hand-written code as the core developer competency. Here's why English is now the most important programming language.
TutorialsLearn how to use OpenCode with DeepSeek LLM and System Prompts to automate JS reverse engineering environment patching for Taobao, Xiaohongshu, and more.
TutorialsLearn how to use AI LLMs like DeepSeek with System Prompts to auto-patch JS browser environments for reverse engineering, covering major platforms with 10x efficiency gains.
Deep DivesDeep dive into Harness Engineering methodology: Agent=Model+Harness formula, the Prompt→Context→Harness evolution path, and a developer implementation guide.
TutorialsA deep dive into the Harness Engineering four-step closed-loop principle (Goal, Action, Verification, Memory), clarifying its relationship with Prompt Engineering, Context Engineering, and MCP.
TutorialsA detailed guide to Harness Engineering's three-layer architecture for controlling AI Agent code generation quality, covering the Information, Constraint, and Automation layers with practical setup and pitfall avoidance tips.
TutorialsA complete guide to AI Agent development evolution: from API First principles to multi-Agent collaboration, covering prompt optimization, context engineering, and memory mechanisms to build reliable enterprise Agent systems.
Deep DivesDeep dive into Harness Engineering: its definition, six core components, and production practices. Learn why Prompt and Context Engineering aren't enough for production-grade AI Agent systems.
TutorialsA practical guide to AI Agent prompt engineering using a three-layer architecture: System Layer, Input Layer, and Action Layer — with n8n examples.
Deep DivesA clear breakdown of five core AI programming concepts — Prompt Engineering, Context Engineering, Agent, Skill, and Harness Engineering — with real-world use cases and advice for indie developers.
TutorialsAndrew Ng's 2026 AI prompting course: master 4 core principles from context-giving and deep thinking to overcoming sycophancy and iterative workflows.
Deep DivesAI Agent getting dumber over time? Context Rot has two root causes: Distraction (attention dilution) and Poisoning (causal chain contamination). Learn symptoms, mechanisms, and remediation strategies.
Deep DivesDeep dive into Context Engineering: its core principles and practices. From Prompt Engineering to context design, orchestration, and optimization—exploring how Karpathy's new AI paradigm reshapes LLM app development and AI Agent construction.
TutorialsDeep dive into the open-source project system-prompts-and-models-of-ai-tools: 7000+ lines of system prompts from ChatGPT, Claude & more, covering prompt engineering best practices and safety design.