#LLM augmented development
1093 related articles
Tutorials·3 min
Can You Really Transition to AI/LLM in Three Months? A Deep Dive into the Learning Roadmap
Deep dive into a popular 3-month AI/LLM transition roadmap: from Python basics and Prompt engineering to LangChain, RAG, Agents, and hands-on projects, with realistic time estimates and pitfall warnings.
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Product Reviews·3 min
Mavis Hands-On Review: Multi-Agent Collaboration vs. Single Agent — A Comprehensive Comparison in Academic Research and Web Development
In-depth review of Mavis multi-agent platform across academic retrieval, literature review, and web development. Multi-agent mode significantly outperforms single agents in accuracy and reliability.
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Deep Dives·3 min
CodeRAG Technical Deep Dive: Four Core Components That Help AI Truly Understand Your Codebase
Deep dive into CodeRAG's four core technologies: vector similarity search, file system tools, Code Knowledge Graph (CKG), and DeepWiki — how they work together to help AI coding assistants truly understand enterprise codebases and eliminate hallucinations.
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Product Reviews·2 min
Agent Memory: Giving AI Coding Agents Persistent Memory Across Sessions
Agent Memory is an open-source local memory layer providing persistent, cross-session, cross-tool long-term memory for AI coding agents like Claude Code, Cursor, and Codex.
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Tutorials·3 min
Build a Claude Code Agentic OS in 3 Steps — Stop Using AI Like a Slot Machine
Learn how to transform Claude Code from a random prompting tool into a systematic Agentic OS through three layers: architecture, Obsidian memory, and an observability dashboard.
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Product Reviews·3 min
Zion No-Code Platform Hands-On: Building a Production-Ready E-commerce Mini Program from Scratch Without Writing a Single Line of Code
Hands-on review of Zion no-code platform: building a production-ready e-commerce mini program from scratch with visual design, built-in database, workflow orchestration, AI Agent integration, and one-click multi-platform publishing.
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Tutorials·2 min
CLAUDE.md Configuration Guide: Write Your Project Spec Using a Six-Section Structure
A detailed guide to configuring CLAUDE.md with a six-section structure covering project overview, features, tech stack, directory structure, code conventions, and constraints to boost AI coding efficiency.
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Tutorials·3 min
Claude Code Hidden Configurations Fully Explained: From Chat Assistant to Semi-Automated Programming Workflow
Explore Claude Code's source code to unlock hidden configurations like Hooks, Agents, Permissions, and Memories. Transform your AI assistant into a customizable semi-automated development workflow.
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Industry Insights·3 min
Deep Dive into Three Major LLM Career Paths: Requirements, Tech Stacks, and Career Prospects
Deep analysis of three core LLM roles—Application Engineer, Development Engineer, and Algorithm Engineer—covering technical requirements, salary thresholds, and career prospects including RAG, fine-tuning, and inference deployment.
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Tutorials·2 min
Dify 1.8.0 Hands-On Tutorial: Complete Guide from Deployment to Building AI Applications
A detailed guide to Dify 1.8.0 Docker deployment, environment setup, and AI app building. Covers five app types, comparisons with Coze, workflow creation, and more for this open-source AI platform.
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Tutorials·3 min
AI Agent Practical Development: A Complete Guide from Concept to Building Production-Grade Intelligent Agents
A deep dive into AI Agent core principles and practical development paths, covering perception-decision-execution capabilities, MCP protocol tool integration, and analysis of Manus and AutoGLM.
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Deep Dives·3 min
memU Memory Framework Explained: Unifying Multi-Modal Agent Memory with a File System
Deep dive into the memU open-source memory framework: how it organizes Agent memory as a file system with three-layer semantic abstraction, dual-loop collaboration, and two retrieval modes.
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Tutorials·3 min
AI Programming in Practice: A Complete Breakdown of Building a Website from Scratch in 7 Days
A developer used Claude Code and DeepSeek to build and deploy a complete website from scratch in 7 days. 99% AI-written code, AI-generated data, with full process breakdown and cost analysis.
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Tutorials·3 min
The Complete Guide to Spring AI: A Full Learning Path for Java Engineers Building AI Applications
A comprehensive guide to Spring AI covering LLM integration, prompt engineering, RAG knowledge bases, and five AI Agent patterns, with three enterprise projects for Java engineers.
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Tutorials·3 min
AI Agent Learning Roadmap: From Beginner to Enterprise-Level Development in Three Months
A detailed three-month AI Agent learning roadmap covering LLM basics, ReAct paradigm, LangChain, memory mechanisms, tool calling, and multi-agent collaboration with practical project suggestions.
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Tutorials·3 min
Harness Engineering: A Practical Guide to AI Programming — From Prompts to Mastery
Explore the three stages of AI programming evolution: from Prompt Engineering to Context Engineering to Harness Engineering. Master enterprise-grade AI coding with Cloud Code + VS Code.
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Industry Insights·2 min
Cisco Partners with OpenAI Codex: Three Core Scenarios for Enterprise AI Engineering
Cisco partners with OpenAI to bring Codex into enterprise engineering, covering AI-native development, AI Defense security acceleration, and automated bug fixing.
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Tutorials·3 min
Cursor Multi-Agent Workflow: A Practical Guide to Main Thread & Grunt Collaboration
Learn the Cursor "Main Thread & Grunt" multi-agent workflow: use a high-tier model for complex tasks and a low-tier model for simple tasks in parallel to maximize AI coding efficiency.
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Industry Insights·3 min
How Jane Street Built a Custom AI Programming Toolchain for OCaml
Jane Street's AI team details how they built a custom LLM toolchain for OCaml, covering workspace snapshot training data, RL with code evaluation, and the AID editor architecture.
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Tutorials·2 min
PyCharm AI Assistant Deep Dive: Local Completion, Edit Mode & Practical Tips
Explore PyCharm AI Assistant's new features: free local AI completion, cloud-powered generation, Chat & Edit modes, and context management tips for Python developers.
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