#React Agent
1470 related articles
The Evolution of Coding Agents: A Para…
·2 min
The Evolution of Coding Agents: A Paradigm Shift from Reactive Response to Proactive Planning
Coding agents are evolving from reactive code completers to proactive planners. Explore the "think ahead of time" paradigm, Plan-and-Execute architecture, and its impact on developer workflows.
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Tutorials·3 min
ReAct vs. CodeAct: Two Core Approaches to Agent Tool Calling
In-depth comparison of ReAct and CodeAct — two core Agent tool-calling architectures. From paper principles to code implementation, learn the trade-offs between reasoning+action and code execution.
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Product Reviews·3 min
OpenSlide: An Open-Source Framework That Lets AI Agents Write React Code to Create Presentations
OpenSlide is an Agent-native open-source slide framework that lets AI Agents write React code to generate professional presentations. Supports Claude Code, Cursor, and other coding Agents.
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Tutorials·3 min
Hermes Agent in Practice: A Complete Breakdown from ReAct Loop to Autonomous Skill Evolution
Deep dive into Hermes Agent's four progressive cases: terminal ReAct loop, Feishu AI assistant, four-layer persistent memory, and three-stage Skill evolution with DeepSeek support.
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Deep Dives·2 min
AI Agent Development Methodology: A Complete Guide from ReAct to Enterprise-Grade Tech Stack
A deep dive into AI Agent development methodology, from the ReAct theoretical framework to a four-layer enterprise tech stack covering model services, Agent types, LangChain, and production deployment.
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Tutorials·3 min
Agent Loop Explained: Solving Code Refactoring Pain Points with the ReAct Pattern
Deep dive into Agent Loop, the core mechanism of AI coding tools. Learn how the ReAct pattern's reason-act-observe cycle enables autonomous multi-step code refactoring.
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Tutorials·2 min
LangChain Agent Executor Architecture: Building a ReAct Agent from Scratch
Deep dive into LangChain Agent Executor internals, covering the ReAct reasoning-action-observation loop, tool choice strategies, and building a custom Agent Executor from scratch.
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Deep Dives·2 min
How AI Agents Work: The Four Core Elements and ReAct Loop Decision-Making Mechanism Explained
Deep dive into AI Agent's four core elements (LLM, Tools, Prompts, Executor) and ReAct loop decision mechanism, with a weather query example walkthrough.
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Deep Dives·4 min
Agent Loop Core Mechanism Explained: Building a ReAct Loop from Scratch (With Debugging War Stories)
Deep dive into Agent Loop, the core mechanism of AI Agents, based on ReAct architecture. Covers Tool Call ID handling, context management, assistant message feedback, with full Python code and common bug fixes.
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Tutorials·1 min
AI Agent Open-Source Course: 36 Chapters from ReAct to Claude Code Full-Stack Practical Guide
Open-source GitHub project agent-study offers 36 chapters covering ReAct loops, Claude Code reverse engineering, MCP protocol, RAG, DSPy, and production observability as runnable Python code.
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·1 min
From Request-Based to Token-Based: What the Billing Model Shift in AI Coding Tools Really Means
AI coding tools are shifting from request-based to token-based billing. This article analyzes how the $75 monthly cap impacts developers and what it signals for the industry.
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·3 min
Orca-Bench: Evaluating Whether AI Agents Can Handle Production Oncall Duties
Orca-Bench is a benchmark for evaluating AI agents' operational capabilities, testing LLMs on fault diagnosis, multi-tool orchestration, and risk decisions in simulated Oncall scenarios.
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·3 min
Practical Guide to Setting Up a Local AI Coding Environment on MacBook Pro M4
Complete guide to setting up a local AI coding environment on MacBook Pro M4, covering Ollama, MLX, Continue, Qwen3-Coder 30B configuration, and performance optimization strategies for 32GB RAM.
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·3 min
AI Modeling of Human Spatial Reasoning: A Breakthrough Path from Cognitive Experiments to Computational Models
Exploring how AI builds cognitive computational models from human spatial reasoning experiments, analyzing LLM spatial cognition gaps and Embodied AI applications.
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·5 min
Customer.io Summer Release Breakdown: Geofencing, Live Notifications, and Multi-Channel Engagement Get a Major Upgrade
Deep dive into Customer.io's major summer release: geofencing triggers, live notifications, flexible SMS providers, notification inbox, and WhatsApp management upgrades for unified multi-channel engagement.
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·3 min
What Kind of GUI Do AI Agents Need? The Evolution from Chat Boxes to Task Consoles
Exploring GUI design for AI Agents: why chat boxes fall short, and how ideal agent interfaces need task visualization, human-in-the-loop intervention, state presentation, and multi-agent orchestration.
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·3 min
Self-Hosted Ticketing Systems: Turning Family Tech Support into a Streamlined Service
Explore how to manage family IT support with a self-hosted ticketing system. Compares osTicket, Zammad, FreeScout and more, with Docker deployment tips and UX advice.
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·3 min
Can Talking Like a Caveman Save 65% on Tokens? An In-Depth Analysis
Can caveman-style minimal prompts save 65% on Tokens? We analyze task quality, hidden cost transfers, and model robustness to reveal the right Token optimization strategies.
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·3 min
Can Talking Like a Caveman Save 65% on Tokens? An In-Depth Analysis
Can caveman-style minimal prompts save 65% on Tokens? We analyze task quality, hidden cost transfers, and model robustness to reveal the right Token optimization strategies.
Read more →
·2 min
GPT-5.6 Released: Redefining the Price-Performance Boundary of AI Models
OpenAI releases GPT-5.6, targeting the price-performance frontier. Analysis of how architectural optimization and inference efficiency reduce costs, and how LLM competition shifts from capability to cost efficiency.
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