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Vibecoding is an emerging AI-driven programming paradigm that shifts focus from syntax to intent expression, enabling developers to generate code through natural language interaction with LLMs. This approach transforms developers from code writers to product thinkers and AI collaborators, significantly lowering programming barriers and accelerating development cycles while introducing new challenges in code quality and security. (Vibecoding是一种以AI为核心的新兴编程范式，将编程重点从语法细节转向意图表达，开发者通过自然语言与大型语言模型交互生成代码。这种模式将开发者角色从代码编写者转变为产品思维引导者和AI协作者，大幅降低编程门槛并加速开发周期，同时带来代码质量和安全方面的新挑战。)

Vibe Coding represents a fundamental shift in software development where developers focus on intent and user experience rather than syntax, using AI tools to generate and iterate code through natural language prompts. (Vibe Coding代表了软件开发的根本性转变，开发者专注于意图和用户体验而非语法，通过自然语言提示使用AI工具生成和迭代代码。)

Vibecoding is a revolutionary programming paradigm that shifts focus from implementation details to desired outcomes, leveraging AI to generate and refine code based on iterative feedback. This approach enables developers to immerse themselves in a 'prompt-result-adjust' loop, dramatically boosting productivity and lowering barriers to entry. (Vibecoding是一种革命性的编程范式，将关注点从实现细节转向预期结果，利用AI根据迭代反馈生成和优化代码。这种方法让开发者沉浸在“提示-结果-调整”的循环中，显著提升生产力并降低入门门槛。)

English Summary: This article traces the evolution of AI programming from Andrej Karpathy's initial Vibe Coding concept to the more systematic Context Coding methodology that emerged in 2025. It analyzes the tool ecosystem, compares three programming paradigms, and provides practical implementation strategies while forecasting 2026 trends including Agentic AI and standardized MCP protocols. (中文摘要翻译：本文追溯了从Andrej Karpathy提出的Vibe Coding概念到2025年形成的更系统化的Context Coding方法论的演进历程。分析了工具生态系统，对比了三种编程模式，提供了实践建议，并展望了2026年包括Agentic AI和标准化MCP协议在内的技术趋势。)

This article explores innovative strategies to overcome key design bottlenecks in large-scale AI agent systems, focusing on scalability, efficiency, and reliability. (本文探讨了突破大规模AI代理系统设计瓶颈的创新策略，重点关注可扩展性、效率和可靠性。)

Vibecoding is an emerging AI-driven programming paradigm that enables developers to describe requirements in natural language while AI generates code, focusing on rapid MVP development and modern tech stacks like Next.js and TypeScript. (Vibecoding是一种新兴的AI驱动编程范式，允许开发者用自然语言描述需求，由AI生成代码，专注于快速MVP开发和现代技术栈如Next.js和TypeScript的应用。)

This article provides a step-by-step guide on how to send emails using QQ Mail, covering the process from accessing the email interface to verifying successful delivery, with practical tips for handling attachments and troubleshooting common issues. (本文详细介绍了使用QQ邮箱发送邮件的完整步骤，从进入邮箱界面到验证邮件成功投递，涵盖了附件处理和常见问题排查的实用技巧。)

Gas Town proxy pattern is a specialized architectural design in AI systems that manages resource allocation and computational flow through intermediary agents, optimizing performance and scalability. (Gas Town代理模式是AI系统中一种专门的架构设计，通过中介代理管理资源分配和计算流程，优化性能和可扩展性。)

Gas Town代理模式是一种在AI系统中模拟加油站资源分配机制的智能代理架构，通过动态调度和优化计算资源，提高系统效率并降低能耗。 Gas Town代理模式是一种模拟加油站资源分配机制的智能代理架构，通过动态调度和优化AI系统的计算资源，显著提升处理效率并降低能源消耗。