#AI编程
9454 related articles
Claude Code MCP Tasks: A New Paradigm for Long-Running Tasks and Proactive Questioning
Claude Code supports MCP Tasks and elicitations, enabling tool calls to run as long tasks and ask users questions mid-execution. This article explains the conditions, current gaps, and required server changes.
AI Code Documentation Isn't Just Boring Text: The Practice of Visual Interactive Docs
AI-generated code is outpacing static docs. Learn how visual, dynamic, interactive documentation—with Linear/Jira integration and interactive PR review—keeps engineers in sync.
AgentValley: See All Your Claude Code Agents at a Glance in the Mac Notch
AgentValley is a free open-source Mac menu bar tool that displays Claude Code sessions and sub-agent status in the notch, using cards and pixel avatars to visualize agent activity and solve multi-agent management pain points.
kosa8: A Reversible Secure Sandbox for AI Agents
kosa8 provides isolated VM sandboxes for AI agents like Claude Code and Codex, with environment snapshots and ~1-second rollback (including running processes), plus environment forking for parallel testing, reducing the risk of agents operating on your local computer.
Anthropic Open-Sources sandbox-runtime: A Container-Free Sandbox for AI Agents
Anthropic open-sources sandbox-runtime (srt), an OS-level sandbox built on macOS Seatbelt and Linux bubblewrap that restricts file and network access for AI agents, MCP servers, and CLI tools—lightweight isolation without containers.
No Code Required: Building SVG Animation Explainer Videos with Claude Code
Bilibili UP host tests: zero code, using Claude Code to build an SVG animation explainer video tool. Covers environment setup, multimodal references, MCP screenshot self-check, Hooks validation, Skills encapsulation, and Subagent review.
Greptile Uses Multi-Agent Code Verification, a New Review Paradigm for the AI Programming Era
Greptile v5 agent launches multiple sub-agents per PR, combining open-source and frontier models for independent, fast code review, with Together AI providing inference support to reduce cost and latency.
11-Hour Video Course: Building Reasoning Models from Scratch
An 11+ hour video course teaches building reasoning models from scratch with Python and PyTorch, covering evaluation, inference-time scaling, RL, and distillation.
Claude vs Claude Code: What's the Difference and Which Should You Use?
What's the difference between Claude and Claude Code? This article breaks down the positioning: Claude is a general-purpose chat and document app, Claude Code is a coding agent for your codebase. They share the same model family and subscription quota—just route by task type.
Together AI B200 Training Price Cut: $9/GPU-Hour for the First Eight Weeks
Together AI cuts B200 post-training to $9/GPU-hour for the first eight weeks, covering SFT and RL while letting teams keep the training loop in their own code.
AI-Assisted Paper Cites Nonexistent TorrentFreak Article: Academic Integrity Concerns Resurface
An AI-assisted paper on Z-Library cited a nonexistent TorrentFreak article, exposing the hallucinated citation problem in AI writing and gaps in peer review and academic publishing.
Factory Gets Early Access to Beam: Pre-Release Testing of Reflection AI Models to Validate Real-World Coding Agent Workflows
Factory gained early access to Beam through Together, testing Reflection AI models in real coding and agentic workflows before official release—covering tool error recovery, conflict handling, and repository validation, revealing the strategic value of pre-release testing for AI coding products.
Tech FrontiersAI Eliminates Information Asymmetry: Is the Era of Programmers Making Money Through Outsourcing Over?
Can programmers still make money from outsourcing? A Bilibili creator says AI is eliminating information asymmetry and the outsourcing winter has arrived. This article breaks down the underlying logic, analyzes how student and merchant demand is being squeezed by AI, and offers four viable directions for programmers to shift from selling skills to selling judgment.
AI Engineering in Practice: The Complete Workflow of Claude Code and Agent Skill Development
A Bilibili hands-on course analyzes AI engineering: using Claude Code, Codex, and WorkBuddy to develop enterprise-grade Agent Skills, covering WeChat article drafts, quantitative analysis, and automated Xiaohongshu posting, while explaining the paradigm shift of Skill-driven development and tool selection.
LangChain for Beginners: A Practical Guide to Structured Output and Agents
Starting from zero with LangChain: clarify the difference between low-code platforms and large model application development, covering structured output, tool calling, Agent practice, and multi-tenant RAG enterprise deployment—ideal for engineers with development experience looking to transition into AI application development.
MCP Protocol Explained: How a Single Email Can Hijack Your AI Agent
A deep dive into MCP: from the M×N to M+N integration mental model, the 2026 stateless spec and Python code practices, to a full prompt injection attack reproduction and five defenses to help you design and harden your AI Agent's tool layer.
MCP Protocol Explained in One Minute: Let Your AI Agent Actually Call Tools
Understand MCP (Model Context Protocol) in one minute: how Host, Client, and Server collaborate so AI apps can call real tools through a standardized interface, with servers written once and reused by any MCP client.
Building Stateful Engineering Copilots with Letta: Core Memory and Shared State in Practice
A Letta hands-on tutorial analyzing six capabilities of stateful engineering copilots: inspectable core memory, vector semantic retrieval, multi-agent shared state, custom tools, streaming output, and portable workflows, plus applicable scenarios and operational limits.
Chalk and Airplane: A Metaphor Revealing the AI Programming Dilemma
Using the metaphor from the Hacker News post "The Chalk and the Airplane," this article analyzes the capability mismatch of AI programming tools: developers still use chalk thinking to control airplane-level tools. It explores the paradigm shift in AI programming, task selection, and validation mechanisms.
Tech FrontiersPrompt Engineering from Beginner to Practice: Core Concepts and Limitations Explained
Based on the first lesson of a Bilibili prompt engineering tutorial, this article systematically explains the nature and four roles of prompts, the six-step process and four goals of prompt engineering, and key limitations such as capability ceilings, unstable output, hallucinations, and context limits—helping beginners build correct understanding.