#ReAct CoT paradigm
130 related articles
·3 min
From RAG to Agent Tuning: A Complete Guide to Deploying LLM Agents
A deep dive into LLM Agent frameworks covering RAG, Agent core components (tools, memory, planning), and Agent Tuning workflows with cost considerations for production deployment.
Read more →
·5 min
The Complete Guide to AI Agent Development: A Four-Stage Progressive Roadmap
A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.
Read more →
Alibaba Open-Sources Code Review Tool …
·5 min
Alibaba Open-Sources Code Review Tool open-code-review: Deterministic Pipeline + LLM Dual-Engine Analysis
Alibaba open-sources code review tool open-code-review, using a hybrid architecture of deterministic rule pipelines and LLM Agents. Supports line-level comments, OpenAI/Anthropic APIs, battle-tested at Alibaba scale, written in Go, fully free and open-source.
Read more →
·6 min
Making Money with AI Coding Gigs: A Sober Breakdown and Honest Assessment of the Four-Week Learning Path
Can beginners really earn over 10,000 yuan in their first month with AI coding gigs? This article breaks down the four-week AI coding learning path week by week and objectively assesses the real monetization barriers.
Read more →
·7 min
Getting Started with Claude Code: Five Dimensions to Understand Why It Outperforms Regular AI
Claude Code isn't just a chat AI—it can directly read projects, modify code, and run commands. This article compares Claude Code with regular AI across five dimensions to help you decide if it's worth trying.
Read more →
·7 min
Getting Started with Claude Code: Five Dimensions That Show Why It Outperforms Ordinary AI
Claude Code isn't just a chat AI—it can directly read projects, modify code, and run commands. This article compares Claude Code with ordinary AI across five dimensions: interaction, context, execution, memory, and tool calling.
Read more →
·4 min
Beyond Vibe Coding: A Complete Guide to Enterprise-Grade AI Engineering
Hit the Vibe Coding ceiling? This guide covers the three-stage AI coding progression path, Claude Code vs. Codex, SuperPower SDD, and how to go from vibe coding to enterprise-grade AI engineering.
Read more →
·3 min
Vibe Coding for Beginners: Build Your First Project with AI from Scratch
What is Vibe Coding? Learn this new AI programming paradigm from scratch — no CS degree needed. Use Claude Code, Cursor, and more to build real projects by describing your ideas.
Read more →
·6 min
The Complete Guide to Using Claude in China: In-Depth Comparison of 4 Solutions and How to Choose
How can users in China use Claude? This article deeply compares four solutions: official subscription, proxy subscription (WildCard), relay platforms (2233/0011.ai), and API aggregation (OpenRouter).
Read more →
·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
Read more →
·6 min
The AI Builder's Handbook: A Complete Guide to LLM Principles, RAG Architecture, and Agent Design
From the autocomplete nature of LLMs, tokens, and context windows to RAG vector databases, the MCP protocol, and AI agent loop design — this article uses vivid analogies to unpack the reality of AI engineering.
Read more →
·7 min
From Chat to Agent Platform: A Practical Guide to Engineering AI Applications
A deep dive into engineering AI applications: from a simple chat page to a multi-layer Agent platform, covering RAG knowledge bases, Workflow scheduling, multi-model management, and run tracing.
Read more →
·5 min
DeepSeek V4 Enters Grayscale Testing, Grok 5.0 Ready to Launch | Latest AI Model Developments
This AI Daily covers five sectors: DeepSeek V4 reportedly enters grayscale testing with improved chain-of-thought; Musk previews Grok 4.6 and 5.0 with 2T parameters; Intern-S2 open-source model beats Claude Opus 4.8; xAI builds 2000MW Colossus cluster; NVIDIA RoboTTT breaks long-horizon robotics barriers.
Read more →
·2 min
OpenAI's New Voice Assistant Tested: It Interrupts, Simultaneous Interprets, and Gets Flustered
OpenAI's upgraded voice assistant can speak dialects, do real-time simultaneous interpretation, teach English, and even get flustered. Here's what changed.
Read more →
·3 min
OpenCode In-Depth Review: Can This Open-Source Coding Agent Replace Claude Code?
OpenCode is an open-source terminal coding agent with 180K+ GitHub stars, supporting hundreds of models and a dual-layer agent architecture — completely free. See how it compares to Claude Code.
Read more →
·3 min
AI Agent 4-Week Learning Roadmap: A Complete Guide from Zero to Independent Development
A structured 4-week AI Agent learning roadmap: Week 1 covers LLMs & Prompt engineering, Week 2 ReAct paradigms, Week 3 RAG memory systems, Week 4 multi-agent architectures.
Read more →
·3 min
Getting Started with LangChain 1.3: Building Intelligent Agent Applications with Deep Agent
Learn LangChain 1.3 core concepts including LLM model abstraction, RAG retrieval-augmented generation, and Agent orchestration. Build a Deep Agent with planners, tools, and reflection modules.
Read more →
·3 min
SJTU Professors Open-Source Agent Tutorial: A Four-Stage Path from Zero to AI Engineer
SJTU professors open-source a 4-stage Agent tutorial on GitHub, covering LLM basics, ReAct, multi-agent systems, and real-world projects — a practical path to AI engineering.
Read more →
Agentic Loop Explained: The Three-Loop…
·2 min
Agentic Loop Explained: The Three-Loop Architecture of Reasoning, Tool Use, and Orchestration
A deep dive into the Agentic Loop — breaking down the three-layer architecture of reasoning, tool use, and orchestration to help developers build and debug reliable AI agent systems.
Read more →
·3 min
Complete AI Agent Development Learning Path: From Core Principles to Enterprise Deployment
A structured AI Agent learning path covering core principles, prompt engineering, tool use, multi-agent systems, and frameworks like LangChain, CrewAI, and Dify for enterprise deployment.
Read more →