320 related articles

A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.
GitHub Daily · July 22: Financial Foun…
GitHub Trending July 22: Kronos brings the foundation model paradigm to finance, awesome-claude-skills tops with 70K stars, plus LikeC4 architecture-as-code and Rust-based Pumpkin.

Google's Addy Osmani at AI Engineer conference: as AI agents outpace human review, engineers' core value lies in the "verdict" — deciding what's worth building and owning outcomes.

Always burning through your AI coding quota? This guide breaks down a brain-vs-hands multi-agent strategy: use strong models only for planning, and cheap models like DeepSeek for execution.

A deep dive into the 7 core components for building long-running AI Agents: Goal, Evaluator, Verifier, Loop, Orchestration, Observability, and Memory.

A practical guide to Claude Code covering installation, Chinese LLM switching, project analysis, key commands, and conversational Git workflow automation for developers.

A deep dive into LangChain, LangGraph, MCP, and enterprise AI Agent development: covering Streamable HTTP updates, DeepSeek R1 Function Calling limits, and Qwen3 agent capabilities.

A complete guide to Claude Code: environment setup, switching to domestic LLMs, CLI commands, Git workflows, MCP, Subagents, and enterprise project walkthroughs.

A deep dive comparing Vibe Coding vs AI Engineering, with hands-on analysis of Claude Code and Codex, two real projects, and the role of Skills in enterprise AI development.

Pi is a minimalist open-source Agent framework with just 4 default tools and under 1,000 tokens in its system prompt, with 70K GitHub stars. Deep dive into its 4 core advantages vs. Claude Code and Codex.

Learn how to use Trae, ByteDance's free AI coding tool, to build a Flask-based visual database query system (EasyQuery) in just 20 minutes. Full walkthrough included.

Deep dive into GPT-5.6 (Sol/Terra/Luna) and OpenAI's Super App: Loop Engineering, Parallel Agents, and Computer Use — unpacking the shift from prompt to loop engineering with real test cases and a startup framework.

Codex vs Fable in an open-ended problem space: Codex delivers flawless execution but plays it safe; Fable shows sharp strategic vision but lands too narrow. Here's how to combine both.

OpenAI launches GPT-5.6, Apple rebuilds Siri, China's AI companionship regulations take effect, Google labels AI images — your one-stop global AI industry roundup.

A four-stage AI Agent development roadmap: from core theory and ReAct paradigm to multi-agent collaboration and production deployment. Covers DeepSeek, Coze, Dify, and more.

Altman warned of possible GPT-5.6 service disruptions at launch, highlighting compute capacity as the true bottleneck for LLMs. Here's what it means for users.

How AirOps replaced traditional workflow builders with the Claude Agent SDK to build an AI agent platform for content marketers — covering three architectural iterations, harness engineering, and sub-agent context management.

Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.

A practical guide to OpenAI Codex: core features, Codex vs. Claude Code comparison, and why the Codex+DeepSeek combo doesn't work. Avoid common pitfalls and boost your coding productivity.

How can frontend engineers transition into AI development? This guide covers four agent development directions: RAG, workflow agents, vertical agents, and general-purpose agents — with framework picks like LangChain.js.