#LLM coding paradigm
1284 related articles
Deep Dives·4 min
Harness Engineering Explained: The Third-Generation Development Paradigm for Taming AI Agents
Deep dive into Harness Engineering: the third-gen AI development paradigm. Learn its three-layer architecture for effectively harnessing AI Agents to complete complex development tasks.
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Tutorials·4 min
A Practical Guide for Java Developers Transitioning to AI Agent Development: Technology Selection, Architecture Design & Resume Positioning
A systematic guide for Java developers entering AI Agent development, covering core concepts, Workflow vs. Agent architecture comparison, Spring AI Alibaba selection, and resume positioning strategies.
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Expert Opinions·3 min
Sam Altman in Conversation with Garry Tan: How OpenAI and YC Are Co-Shaping the AI Startup Ecosystem
Sam Altman and YC President Garry Tan discuss the convergence of OpenAI's foundation models and YC's startup ecosystem, revealing key signals about the next phase of AI entrepreneurship.
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Tutorials·4 min
A Practical Guide for QA Engineers: Building 18 AI Agents with 5 Essential Tools
Learn how QA engineers can build 18 AI Agents using Coze, LangChain, Dify, Cursor, and Skills — covering requirements analysis, test case generation, script writing, and regression testing with up to 10x efficiency gains.
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Product Reviews·3 min
How to Choose an AI Agent Framework in 2026? Pros and Cons of Four Leading Solutions
Compare four leading AI Agent frameworks in 2026: Coze, AutoGen, CrewAI, LangChain, and AutoGen Studio — covering coding requirements, private deployment, and commercialization.
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Product Reviews·4 min
AI Agent Framework Selection in 2025: Pros and Cons of Coze, AutoGPT, LangChain, and AutoGen
2025 comparison of four major AI Agent frameworks: Coze for beginners, AutoGPT/LangChain/MetaGPT for developers, Microsoft AutoGen for enterprise self-hosted deployment. A practical selection guide.
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Tutorials·3 min
TierCraft AI: A Practical Deep Dive into Auto-Generating SaaS Pricing Plans with LangGraph + OpenAI
Deep dive into the TierCraft AI open-source project: using LangGraph to orchestrate AI Agent workflows with OpenAI o4-mini to auto-generate three-tier SaaS pricing plans, featuring Reality-Check loops and context-aware pricing.
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Product Reviews·3 min
awesome-LLM-resources: A Comprehensive Analysis of the 8,200-Star LLM Learning Resource Repository on GitHub
In-depth analysis of the 8,200-star GitHub project awesome-LLM-resources, covering multimodal generation, Agents, model training, MCP protocol, and more — a one-stop LLM learning guide.
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Tech Frontiers·3 min
Cursor's Parent Company Anysphere Uses Composer to Train Next-Gen AI: How Bootstrapped Iteration Is Changing Code Generation
Anysphere uses previous-gen Composer to build RL training environments for next-gen Cursor AI. Explore how bootstrapped AI training reshapes code generation and the competitive landscape.
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Deep Dives·4 min
Hugging Face Transformers: Deep Dive into the 160K-Star Open Source AI Framework
Deep dive into Hugging Face Transformers: the 160K-Star open-source framework covering Pipeline API, Auto Classes, multi-modal models, and the full HF ecosystem for AI inference and training.
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Deep Dives·4 min
Context Engineering Explained: The AI Paradigm Shift from Prompt to Context Engineering
Deep dive into Context Engineering: its core principles and practices. From Prompt Engineering to context design, orchestration, and optimization—exploring how Karpathy's new AI paradigm reshapes LLM app development and AI Agent construction.
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Tutorials·3 min
GitHub 8K Stars: Deep Dive into the Most Comprehensive LLM Resource Repository
Deep analysis of the GitHub project awesome-LLM-resources with 8,200+ Stars, covering multimodal AI, Agents, MCP protocol, model training, inference optimization, and coding assistants.
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Tutorials·3 min
Phone + Claude Code: Building an iNaturalist Observation Display Tool While Camping
Simon Willison built a complete iNaturalist observation display tool using only his phone and Claude Code while camping. A breakdown of the three-layer architecture: Python CLI, Git Scraping automation, and pure frontend display.
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Expert Opinions·2 min
In the Vibe Coding Era, Using RSS to Share and Discover Personal Apps
AI-assisted programming makes building tools as easy as blogging, but how are these personal apps discovered? Matt Webb proposes RSS for vibe-coded apps, and Simon Willison quickly validates the idea.
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Expert Opinions·2 min
The Vibe Coding Era: Why We Need RSS to Share Personal Micro-Apps
Vibe coding makes AI programming as simple as blogging, driving an explosion of personal micro-apps. Matt Webb proposes RSS for sharing micro-apps, and Simon Willison has already implemented it.
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Tutorials·3 min
Phone + Claude Code: Building an iNaturalist Observation Tool with Zero Servers — Full Workflow
Simon Willison built a complete iNaturalist observation tool during camping using his phone and Claude Code. A deep dive into the three-layer architecture: Python CLI, Git Scraping, and AI-generated frontend — all on GitHub with zero servers.
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Product Reviews·4 min
ComfyUI-Copilot: An AI Assistant for Building Stable Diffusion Workflows with Natural Language
ComfyUI-Copilot is an open-source AI assistant plugin supporting natural language workflow building, smart node recommendations, and parameter optimization. With 5,100+ GitHub stars, it dramatically lowers the barrier to Stable Diffusion workflow creation.
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Product Reviews·3 min
awesome-LLM-resources: A Deep Dive into GitHub's 8K-Star Comprehensive LLM Learning Resource Repository
Deep dive into awesome-LLM-resources, a GitHub 8K-star project covering multimodal AI, AI Agents, MCP protocol, model training/inference, and AI coding tools — a one-stop LLM learning guide.
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Deep Dives·4 min
Agent, MCP, and Function Calling: A Complete Guide to Their Differences and Relationships
A deep dive into the relationships between AI Agent, MCP protocol, Function Calling, and Prompt. From basics to full architecture, build a clear cognitive framework for AI app development.
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Industry Insights·3 min
AI-Native Engineering Transformation: Real Emotions and Coping Strategies from 218 Technical Leaders
Based on research with 218 engineering leaders, this deep dive explores the contradictory emotions in AI-native transformation — excitement and anxiety coexisting — and how leaders navigate successful change.
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