#three-layer memory system
108 related articles
·7 min
The Complete Guide to OpenCode: Installing, Configuring, and Using the Terminal AI Coding Assistant
An in-depth guide to installing, configuring, and extending OpenCode, the terminal AI coding assistant. Covers desktop and WSL installation, model config, MCP integration, and custom Agents.
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·7 min
Engineering Vibe Coding in Practice: Taming AI Programming with Superpowers and gstack
A deep dive into engineering Vibe Coding: using Superpowers for project-level decomposition and gstack for module layering and constraints to tame AI coding assistants like Codex and Claude Code.
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·7 min
Claude Sonnet 5 Released: The Most Powerful Agent-Capable Mid-Tier AI Model
Anthropic releases Claude Sonnet 5, its most agentic mid-tier model with planning, browser/terminal tool use, and autonomous execution—bringing flagship Agent capabilities at significantly lower cost.
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·7 min
Claude Sonnet 5 Released: The Most Capable Agent Model at Mid-Tier Pricing
Anthropic releases Claude Sonnet 5, its most agentic Sonnet model yet. With planning, browser/terminal tool use, and autonomous execution, it brings flagship Agent capabilities to mid-tier pricing.
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AI Coding Addiction: The Hidden Price …
·2 min
AI Coding Addiction: The Hidden Price Engineers Are Paying
AI coding tools trigger dopamine-driven addiction loops, but skill atrophy, code comprehension gaps, and dulled judgment are quietly accumulating. A deep dive into the hidden costs.
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·4 min
Coze for Beginners: A Complete Guide to ByteDance's AI Application Development Platform
A complete guide to ByteDance's Coze platform: agents, AI apps, workflows, nodes, and plugins explained. Build AI applications with no coding required.
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·3 min
Liang Wenfeng and DeepSeek: How an Idealist Is Disrupting Global AI with Algorithmic Efficiency
Why did DeepSeek go open-source? How does a 300-person team beat tech giants? A deep dive into Liang Wenfeng's logic: flat org, algorithmic efficiency, and open-source disruption.
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·7 min
Agent Loop Explained: The Core Runtime Mechanism and Think-Act Cycle of AI Agents
Deep dive into Agent Loop mechanics: the think-act cycle, how agents differ from LLMs, termination conditions, and design principles for building autonomous AI Agent systems.
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·3 min
Cursor & Claude Code Enterprise Training: AI Coding Tool Division of Labor and Practical Methodology
How can R&D teams truly leverage AI coding tools? This article breaks down Cursor vs. Claude Code division of labor, an eight-step framework, and how to build reusable AI collaboration assets.
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·4 min
Deep Dive into Hermes Agent Architecture: Loop Mechanism, Memory System, and Gateway Design
Deep dive into Hermes Agent's core architecture: Agent Loop mechanism, three-layer memory system (Markdown/SQLite/external), Gateway multi-platform integration, context compression, and Cron jobs.
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·3 min
The Complete Guide to n8n: An Open-Source Automation Platform with 400+ Integrations That Combines Code and Visual Workflows
Deep dive into n8n, the open-source workflow automation platform: 400+ integrations, native AI capabilities, and dual code/visual modes. Covers deployment, AI Agents, community templates, and more.
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·3 min
AI Agent Development: A Three-Stage Learning Roadmap from Zero to One
A systematic three-stage AI Agent development roadmap: from Python basics and LLM fundamentals, through five core capabilities like planning and tool use, to hands-on RAG projects for real-world deployment.
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·3 min
AI Skills System: A Practical Guide to On-Demand Capability Loading for Agents
Deep dive into the AI Skills system architecture and execution flow, covering Skill.md dual-layer design, skill scanning and matching, on-demand loading, and practical integration methods.
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·3 min
Agent Skills Architecture Explained: A New Paradigm for Modular AI Agent Development
A deep dive into Agent Skills architecture: core concepts, components, and how it works. Clarifies common misconceptions about Skills vs. MCP, and compares Skills with Multi-Agent architecture.
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·3 min
MiniMax Code Hands-On Review: How AI Development Team Mode Redefines Programming Collaboration
In-depth review of MiniMax Code (MCode) Agent Team collaboration through Starbucks financial visualization and Next.js website development cases.
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·4 min
From Vibe Coding to Enterprise-Grade AI Programming: A Complete Progression Path with Practical Analysis
Deep analysis of Vibe Coding's limitations, comparison of Claude Code vs Codex, and a three-layer AI engineering methodology for progressing from casual AI coding to enterprise-grade development.
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·4 min
Building a Tide App Mini Program with Codex in 4 Sessions: A Hands-On AI Coding Agent Tutorial
Learn how to build a Tide App WeChat Mini Program in 4 sessions using OpenAI Codex AI coding Agent, covering agents.md setup, Plan Mode, domain config, and more.
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·2 min
Three Essential Claude Code Configuration Techniques: A Practical Guide to CLAUDE.md, Memory & MCP
Master three Claude Code configuration techniques: use CLAUDE.md for project rules, Memory for auto-learning preferences, and MCP for connecting GitHub and external tools.
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·3 min
Karpathy's Advanced Claude Code Methodology: Building a Self-Evolving AI Work Environment
Karpathy's Claude Code methodology: build a self-evolving AI environment using CLAUDE.md, knowledge bases, Skills, and Hook guardrails for compounding efficiency.
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·2 min
The Era of Managed Agents: Anthropic vs. Google's Two Diverging Approaches
Deep analysis of Anthropic vs Google's Managed Agent architectures, pricing strategies, and selection guidance. Managed Agents are emerging as a new AI infrastructure product category.
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