#LLM memory
2302 related articles
Tutorials·3 min
VSCode + Claude Code + DeepSeek: Complete Guide to Setting Up an AI Programming Environment
Complete guide to setting up a VSCode + Claude Code + DeepSeek AI programming environment from scratch, covering Git installation, Claude Code configuration, CC Switch multi-model management, and VSCode plugin integration for embedded developers.
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Tutorials·3 min
Complete Guide to Installing Hermes Agent on Windows: WSL Setup and Troubleshooting Common Issues
Complete guide to installing Hermes Agent on Windows, covering WSL setup, Ubuntu initialization, API configuration, Web UI installation, and solutions for DNS, virtualization, and other common issues.
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Tutorials·3 min
Java Developers Transitioning to AI Engineers: New Interview Trends and Learning Roadmap
Deep analysis of interview trends for Java developers transitioning to AI engineers, covering LLM integration, RAG, Spring AI framework practice, with a complete learning roadmap.
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Tutorials·3 min
AnythingLLM Installation & Configuration Guide: Building a Local Knowledge Base with API Integration
Complete guide to AnythingLLM local knowledge base setup: installation tips, Ollama model configuration, document vectorization, recall optimization, and API integration.
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Tutorials·3 min
Learn AI Agents in 30 Days: A Four-Stage Learning Roadmap from Zero to Production
A systematic breakdown of the AI Agent learning roadmap covering core architecture, ReAct/CoT paradigms, multi-agent collaboration, and Prompt optimization across four stages with quality resource recommendations.
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Product Reviews·4 min
BeMAD Open-Source Framework Hands-On: A 6-Hour Zero-to-Launch AI Full-Stack Development Experience
Deep dive into BeMAD, a GitHub open-source framework with 50+ guided workflows and 21 AI Agents that compressed WeChat Mini Program development from idea to launch into just 6 hours.
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Tutorials·1 min
AI Large Language Model Learning Roadmap: Six Stages from Zero to Engineer
A systematic LLM engineer learning roadmap covering Transformer basics, prompt engineering, RAG, Agent development, API integration, fine-tuning, deployment, and project practice across six stages.
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Tutorials·3 min
Complete Learning Roadmap for Java Developers Transitioning to AI Engineering
A detailed five-phase learning roadmap for Java developers transitioning to AI engineering, covering Spring AI, LangChain4j, RAG core technology, and Agent development.
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Tutorials·3 min
Andrew Ng's Agent AI Course Fully Explained: Why It's Taking the Tech World by Storm
Deep dive into why Andrew Ng's Agent AI course went viral, covering the five-module agent architecture breakdown, course highlights, target audience, and learning tips for developers.
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Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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Industry Insights·3 min
AI Conversational Programming vs. RPA: Revolution or Complementary? A Deep Dive into Capability Boundaries
Can AI conversational programming replace RPA? Deep analysis of AI's strengths in simple tasks vs. limitations in complex workflows, user return-to-RPA trends, and the future of AI+RPA hybrid automation.
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Deep Dives·4 min
AI Agents 101: Core Concepts, Technical Architecture, and How They Work
A beginner's guide to AI Agents: understand core concepts, the perception-decision-action loop, LLM, tool calling, memory systems, and RAG architecture explained from scratch.
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Deep Dives·3 min
DeepSeek V4 Deep Technical Breakdown: Million-Token Context and Extreme Cost Efficiency
Deep analysis of DeepSeek V4's core architecture: Hybrid Compressed Attention, Manifold-Constrained Hyperconnection, and MUON optimizer—how they cut inference costs by 10x and enable million-token context processing.
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Tutorials·4 min
Semi-AI Mode: A Pragmatic Approach to API Automation Testing Frameworks
Explore the semi-AI approach to API automation testing: why pure AI fails, framework design principles, technology choices, and clear human-AI division of labor for practical implementation.
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Tutorials·3 min
Getting Started with Spring AI Alibaba: The Go-To Framework for Java Developers Integrating LLMs
A deep dive into Spring AI Alibaba's core positioning and advantages, helping Java developers quickly understand how to integrate LLMs through this framework.
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Tutorials·4 min
New API in Practice: Complete Tutorial for Building Your Own AI API Relay Station
Complete tutorial on building an AI API relay station using the New API open-source project, covering Docker deployment, server configuration, channel management, token distribution, and client verification.
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Tutorials·3 min
Andrew Ng's New Course: A Complete Guide to Building Database Agents
Deep dive into Andrew Ng's Building Your Own Database Agent course with Microsoft, covering LLM-SQL interaction, LangChain Agents, Function Calling, and RAG for tabular data.
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Product Reviews·3 min
Hertzman: A Free, No-Install Local LLM Deployment Tool Review
Detailed review of Hertzman local inference engine covering one-click deployment, smart hardware recommendations, OpenAI-compatible API, and performance comparison with LM Studio.
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Tutorials·2 min
Complete Guide to Configuring Local DeepSeek Model in PyCharm for AI-Assisted Programming
Learn how to configure a local DeepSeek model in PyCharm via Ollama for free, privacy-safe AI-assisted programming. Includes installation steps, plugin setup, usage tips, and hardware recommendations.
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Tutorials·4 min
The Complete Guide to Claude Code's Extension System: A Five-Layer Architecture That Doubles Development Efficiency
Deep dive into Claude Code's five-layer extension architecture: Claude.md memory, Skills, MCP services, Subagents, and Hooks. Master the Rule of Three and golden combinations to systematically boost AI coding efficiency.
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