#AI编程
9368 related articles
Six AI Agent Frameworks Compared: Choosing Wrong Costs Weeks—How to Choose Right in One Minute
A comparison of LangGraph, CrewAI, OpenAI Agents SDK, Claude Agent SDK, Google ADK, and Microsoft Agent Framework, with a one-minute selection guide.
Build an AI Agent in 20 Lines of Python: OpenAI Agents in Action
Learn how to build an AI agent in 20 lines of Python with the OpenAI Agents library, covering web scraping, summarization, and tool calling in three steps.
AI Daily: OpenAI Agent SDK and Toyota's Humanoid Robot Push
AI Daily: OpenAI Agents SDK simplifies agent development, Toyota invests $6.4B annually in humanoid robots, Meta plans up to $95B raise for AI infrastructure, Claude Code vs Cursor tested, and reflections on everyday AI harms.
Build an AI Agent by Hand Without Frameworks: A Practical JavaScript Guide
Build a runnable AI Agent in pure JavaScript and Node 22 with no frameworks. Covers tool calling, the agent loop, memory, error handling, max-steps guardrails, real failures from a local small model, and when to switch to frameworks like LangGraph.
AI Daily: GPT-6.1 Terra and Kimi K3.1 Pro Lead the Charge as Agent Security Alarms Sound
AI news in 24 hours: OpenAI releases GPT-6.1 Terra that can operate computers, Kimi K3.1 Pro tops open-source leaderboards with weights promised, MiniMax M3.1 Flash weights on Hugging Face, Cursor launches Agent SDK, while Anthropic and Qwen models face agent privilege-escalation security incidents.
Building Millisecond-Level Identity Resolution for AI Agents with M|BOX and Python
Based on a YouTube tutorial, this article details how to build a millisecond-level deterministic identity resolution tool for OpenAI Agents using the M|BOX Python SDK: indexing 10,000 CRM records in under 0.2 seconds, single queries in single-digit milliseconds, and field-level scoring for typo tolerance, conflict follow-ups, and no-match hallucination refusal.
Cursor Agent SDK Released: Agents as Code, Evaluation Decides Everything
Cursor Agent SDK turns AI agents into versionable, testable code with hosted or self-hosted deployment. OpenAI Terra model halves prices and doubles benchmark scores. This article explains the evaluation-first principle behind both updates and practical advice before migrating.
AI Agents and MCP Internals: How LLMs Call Tools
A deep dive into how AI Agents and MCP work: how LLMs break free from text-only limits via tool calling, how the agent loop operates, how MCP connects tools and data with a unified standard, plus security risks and boundaries.
AWS Agent Registry + Continuum: The Quality Inspectors for AI Agents
AWS Agent Registry offers an approved catalog of Agents, tools, and MCP servers, while AWS Continuum automatically finds exploitable code bugs and opens fix PRs—each still requiring human approval. This article breaks down how this AI Agent governance combo addresses tool abuse and code security in production.
Connecting an AI Agent to an MCP Server ≠ Full Tool Access
An AI agent connecting to an MCP server doesn't mean it can use all its tools. Doordash's Gateway authenticates and authorizes every call, separates read/write permissions, propagates identity with requests, and centralizes permission management.
The Biggest Hidden Risk of MCP Servers: Connecting Tools Doesn't Mean Understanding the Business
MCP lets AI Agents easily connect to enterprise tools, but brings two hidden risks: tool overload and missing semantics. This article explains why MCP only connects and doesn't understand the business, and how a context layer standardizes metrics, unifies entities, and constrains execution to build reliable Agent automation.
Storrito Agent Integrates MCP Server: Demo and Setup Tutorial
Storrito Agent adds MCP server connections. This article breaks down the official demo's full setup flow—conversation trigger, reading official docs, account authorization, and querying social accounts—and analyzes MCP's significance for AI agent integration and its design trade-offs.
Building an AI Agent with a Chat Interface Using Python and MCP
Build a chat interface for an AI Agent with Python and Streamlit, complete with history and authorization buttons, integrate ready-made MCP servers for file system, Web, and GitHub, and use simple RAG to let the agent search your own documents.
Expo Launches AI Agent Skills Library to Simplify React Native Development
Expo open-sources the expo/skills project, offering a set of AI agent skills that help developers operate Expo projects and EAS services via natural language, simplifying build, deployment, and troubleshooting.
Li Xiaolai's "The Craft of Self-Teaching" Hits 18K Stars on GitHub
Li Xiaolai's open-source project "The Craft of Self-Teaching" has surpassed 18K GitHub Stars, teaching self-learning methodology and Python practice via Jupyter Notebook. This article analyzes its core ideas, project structure, and implications for learners in the AI era.
Agent Skills in Practice: Building Excellent Interfaces with Modular Skills
Explore the jakubkrehel/skills project: a set of modular Agent Skills that help developers build excellent interfaces with AI agents. Learn about its core features, community traction, and practical tips for AI-assisted frontend development.
Programmers Transitioning to AI Large Models: Interview Questions and Resume Packaging Explained
Based on a Bilibili AI large model interview tutorial, this article analyzes key interview focus areas for programmers transitioning to AI roles: high-frequency LangChain and LangGraph interview questions, resume project packaging strategies, enterprise model selection perspectives, and how older programmers can rationally plan their transition path.
LangChain and MCP Integration in Practice: From Framework to Agent Development
Explaining how LangChain and MCP fit together: LangChain as an AI app framework and MCP as a tool-calling protocol, enabling reusable, cross-framework agent tools. Covers agent wrapping, function calling vs. MCP, and practical learning advice.
Overseas Blogger Tests It Out: AI Directly Modifies OutSystems Apps — How the MCP Protocol Works in Practice
Overseas blogger tests OutSystems MCP: how an AI Agent uses Context, Mentor, and Platform tools to modify, review, publish, and deploy apps under identity and permission constraints, enabling natural language edits to enterprise apps.
LangGraph for Beginners: Agent Flow Control and Enterprise Development in Practice
Based on a Bilibili tutorial, this article explains how LangGraph solves the control problem of Agents in fixed flows, compares the hierarchy of LangChain and Deep Agent, and offers scenario selection advice.