ReAct
8 articles tagged with this topic
How AI Really Operates Your Files — Function Calling Dissected to the Code
A developer dissects an AI Agent's tool-call lifecycle to the code level: registration, schema, execution, circuit breaking. Baseline for judging AI a
AI Agents Have No Magic: Open the Core Loop and You Find a Trial-and-Error Worker
A code breakdown reveals: AI Agents are just 'read→think→act→check→repeat' loops with error handling. Your subscription dollars buy real intelligence—
14,000 Lines of Python Expose AI Code Agent's Black Box
A developer built a 14K-line Python code agent without LangChain, exposing CLI, dependency assembly, and ReAct loop. The black box is opening.
AI Interviews Now Ask 'How to Handle Agent Failures'—Engineering Beats Jargon
Interviews now probe failure recovery over definitions. This signals Agent dev is in deep engineering—jargon isn't enough; you need real crash experie
LangChain Agent Teardown: LLM Deployment Demands Control, Not Just Convenience
LangChain dissects Agent graph internals and ReAct reasoning loops. Dev shifts from high-level APIs to graph orchestration—control trumps convenience
Agent 的推理方式不 止一种，但大多数人搞混了它们 的层级关系
ReAct, Reflexion, and Router aren't alternatives —they operate at different layers. Picking the wrong level means costly rebuilds.
AI 助手「自己会 想下一步」背后，藏着三层架构——读 懂它，你才知道它什么时候会失控
Most AI coding assistants run on a three-layer nested architecture. Understanding it tells you exactly when and why AI loses control.
Agentic AI Bottleneck Shifts from Code to Deployment Operations
Andrew Ng says agentic AI's bott leneck is no longer writing code but production deployment and problem definition.