#Chain-of-Thought reasoning
100 related articles
·3 min
Andrew Ng's AI Prompting Guide: Four Key Gaps Between Beginners and Experts
Andrew Ng's AI prompting methodology reveals four core gaps between beginners and experts: deep thinking, sufficient context, neutral questioning, and iterative writing. Applicable to ChatGPT, Claude, Gemini, and all major AI tools.
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·3 min
OpenAI Codex App In-Depth Review: Streets Parallel Development and Five Core Features Explained
In-depth review of OpenAI Codex App's five core features: Streets parallel development, deep Git integration, Skills system, Automation tasks, and MCP support.
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·2 min
Connect Claude Code to DeepSeek V4: 3-Step Setup in 60 Seconds
Learn how to connect Claude Code to DeepSeek V4 using CC Switch in 60 seconds. Complete guide covering installation, API Key setup, and model switching for lower-cost AI coding.
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·3 min
Trae Agent Deep Dive: Hands-On Review of ByteDance's Open-Source AI Coding CLI Tool
Deep dive into ByteDance's open-source Trae Agent—a free MIT-licensed AI coding CLI tool. Covers installation, core features, run modes, and real-world performance vs Claude Code and Gemini CLI.
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·3 min
LangGraph Core Explained: Its Relationship with LangChain and Multi-Agent Orchestration Principles
Deep dive into LangGraph's core positioning, its relationship with LangChain, practical code comparisons of Chain vs Graph, understanding Agent essentials, and multi-agent orchestration design.
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·4 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Plan from Zero to Production
A systematic AI Agent development learning roadmap covering LLM API calls, ReAct framework, memory mechanisms, and multi-agent collaboration across four stages with timeline and project suggestions.
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·3 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Guide from Beginner to Practitioner
A systematic AI Agent development learning roadmap covering core concepts, ReAct/CoT paradigms, multi-agent collaboration, and hands-on projects across four stages.
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·2 min
Cherry Studio: A Deep Dive into the Open-Source AI Productivity Tool with Unified Access to 300+ LLMs
Deep dive into Cherry Studio, an open-source AI client supporting 300+ LLMs including OpenAI, Claude, and Gemini, with autonomous agents and pre-built assistants. Nearly 47K GitHub Stars.
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·2 min
Claude Has Written 80% of Its Own Code: Anthropic's Internal Data Reveals the State of AI Self-Development
Anthropic's internal data shows Claude writes 80% of its own code, engineers produce 8x more output, and open-ended task success jumped from 26% to 76%. The era of AI developing AI is accelerating.
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·2 min
OpenAI Launches Long-Term Token Discounts: As Compute Scarcity Becomes the Norm, How Should Enterprises Lock In AI Capacity
OpenAI launches 1-3 year Token commitment discounts as compute scarcity becomes the industry norm. Analysis of the compute bottleneck, business logic, and strategic implications for enterprises.
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·3 min
Cursor Auto-Review Mode Explained: Smart Tiered Approval for More Efficient AI Programming
Cursor launches Auto-review mode with smart risk assessment for tiered approval. Low-risk operations auto-approve while high-risk ones need manual confirmation.
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·3 min
Firebase AI Logic in Practice: Using Gemini to Automatically Break Down Tasks into Actionable Subtasks
A hands-on guide to Firebase AI Logic and Gemini integration, showing how to automatically break down large tasks into actionable subtasks with structured output and real-time sync.
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·3 min
Deep Conversation with Gemini's Four Co-Leads: Technical Roadmap, Current State, and Future Direction
Google Gemini's four co-leads — Jeff Dean, Noam Shazeer, and others — discuss Gemini's technical roadmap, multimodal capabilities, Agent direction, and future strategy in a rare joint conversation.
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Tutorials·3 min
From Traditional RAG to Agentic RAG: Core Principles and Implementation Guide
Deep dive into the technical differences between traditional RAG and Agentic RAG, covering offline/online pipeline principles, tool-based autonomous decision mechanisms, and a LangGraph-based Agentic RAG implementation via the ChatBox open-source project.
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Product Reviews·2 min
GPT-5.1 vs Claude Sonnet 4.5 Hands-On Comparison: Coding, Writing, and Creativity Benchmarked
Hands-on comparison of GPT-5.1 vs Claude Sonnet 4.5 across long-form writing, classical poetry, front-end coding, and UI reproduction to help you pick the right AI model.
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Product Reviews·2 min
GPT 5.1 vs Claude Sonnet 4.5 Hands-On Comparison: Who Wins at Reasoning, Writing, and Coding
Hands-on comparison of GPT 5.1 Thinking vs Claude Sonnet 4.5 across story writing, math reasoning, emotional support, instruction following, and coding to help you choose the right AI model.
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Tutorials·2 min
How to Switch to Full-Power Claude 4 in Cursor: Enable Max Mode to Boost Your Coding Efficiency
Learn how to switch to full-power Claude Opus 4 in Cursor, enable Max mode, manage quotas, and optimize prompts to dramatically boost your AI coding efficiency.
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Tutorials·3 min
Getting Started with AI Agent Development: A Complete Learning Path from Concepts to Practice
A comprehensive guide to AI Agent development for beginners, covering core concepts, market outlook, LangChain framework, RAG knowledge bases, and hands-on projects to systematically master intelligent agent development skills.
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Tutorials·3 min
Alibaba Cloud Bailian Platform Hands-On: Complete Tutorial from API Calls to Multi-Turn Conversations
Complete tutorial on Alibaba Cloud Bailian platform covering API Key setup, Qwen model calls, streaming output, multi-turn conversation principles, and prompt engineering with four roles.
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Tutorials·3 min
MCP Protocol Explained: Differences from Function Calling and Agent Tool Development in Practice
Deep dive into MCP (Model Context Protocol): its principles, communication architecture, and practical applications. Compare MCP vs Function Calling, explore client-server communication and security.
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