#Plan-and-Execute Agent
131 related articles
·7 min
Spring AI 2.0 in Practice: A Beginner's Guide for Java Developers Building AI Agents
A complete Spring AI 2.0 guide for Java developers covering unified API abstraction, RAG, tool calling, MCP protocol, and enterprise projects to build AI Agents.
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·4 min
Enterprise AI Agent Development Guide: Multi-Task Recognition and Dynamic Tool Calling in Practice
A deep dive into AI Agent architecture and enterprise deployment. From LangChain and ReAct design to dynamic tool calling and multi-task recognition — build autonomous enterprise AI assistants.
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·7 min
Claude Sonnet 5 Released: The Most Powerful Agent-Capable Mid-Tier AI Model
Anthropic releases Claude Sonnet 5, its most agentic mid-tier model with planning, browser/terminal tool use, and autonomous execution—bringing flagship Agent capabilities at significantly lower cost.
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·7 min
Claude Sonnet 5 Released: The Most Capable Agent Model at Mid-Tier Pricing
Anthropic releases Claude Sonnet 5, its most agentic Sonnet model yet. With planning, browser/terminal tool use, and autonomous execution, it brings flagship Agent capabilities to mid-tier pricing.
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·3 min
Hermes Agent Setup in Practice: Run a Complete AI Agent Workflow in 3 Minutes
Step-by-step guide to installing Hermes Agent: no sudo required, single-command deployment, supports Ollama, Anthropic, OpenRouter and more. Includes verification steps, key commands, and beginner tips.
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·7 min
Agent Loop Explained: The Core Runtime Mechanism and Think-Act Cycle of AI Agents
Deep dive into Agent Loop mechanics: the think-act cycle, how agents differ from LLMs, termination conditions, and design principles for building autonomous AI Agent systems.
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·7 min
AI Agent Practical Guide: The Complete Path from Building to Production Deployment
A deep dive into AI Agent architecture and engineering practices, covering tool design, ReAct execution patterns, Vercel deployment, and production considerations to bridge the prototype-to-production gap.
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·4 min
Deep Dive into Alibaba's AgentScope 2.0: Six Core Upgrades and Agent Design Patterns Explained
Deep analysis of Alibaba's AgentScope 2.0 multi-agent framework: six core upgrades including event systems, security interception, HITL, and workspace systems, plus ReAct vs Plan-and-Execute agent design patterns.
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·3 min
6-Week AI Agent Development Learning Roadmap: A Complete Guide from Zero to Project Deployment
A systematic 6-week AI Agent development roadmap covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and deployment for beginners to build production-ready agents.
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·3 min
Java AI Framework Comparison: A Selection Guide for Spring AI, LangChain4J, and More
In-depth comparison of four Java AI frameworks — Spring AI, LangChain4J, DJL, and JBot AI — covering features, use cases, and ecosystem compatibility to guide your selection.
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·3 min
Getting Started with AI Agent Development: Core Concepts, Architecture, and Practical Essentials
A comprehensive guide to AI Agent development covering core concepts, the Perception-Brain-Action architecture, key differences from chatbots, four essential components, and mainstream framework selection.
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·4 min
AI Large Language Model Career Transition Roadmap: A Three-Phase Learning Guide from Zero to Enterprise-Ready
A systematic three-phase AI LLM career transition roadmap: from Transformer fundamentals to RAG, Agent & LangChain development, to LoRA fine-tuning. Build enterprise-ready skills in two months.
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·3 min
Four Core Modules of AI Agent Development: An Architecture Guide from Failure to Stable Deployment
Deep dive into four core AI Agent modules: system prompts, tool calling, RAG memory, and ReAct workflow orchestration. Solve hallucinations, loops, and build reliable agents.
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·4 min
Spring AI Alibaba Agent in Practice: Building Enterprise-Grade AI Agents Natively in Java
Deep dive into Spring AI Alibaba Agent framework covering core architecture, tool calling, RAG integration, multi-agent collaboration, and production deployment for Java developers.
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·4 min
Building a Coding Agent from Scratch: Creating a Codex-like AI Programming Tool
Deep dive into AI coding agent architecture: from interview-level cognition to building a Codex-like CLI agent tool, covering agents.md, Skills systems, context management, and more.
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·3 min
AI Agent Learning Path from Zero: A Complete Guide from Principles to Practice
A systematic AI Agent learning path covering core principles, dev environment setup, memory management, multi-agent collaboration, and hands-on projects for beginners.
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·3 min
AI Agent Development: A Three-Stage Learning Roadmap from Zero to One
A systematic three-stage AI Agent development roadmap: from Python basics and LLM fundamentals, through five core capabilities like planning and tool use, to hands-on RAG projects for real-world deployment.
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·3 min
Java Developer's Guide to AI: Hands-On with Spring AI and RAG
A practical guide for Java developers to build AI apps without switching languages — covering LLM APIs, prompt engineering, RAG, Spring AI, and Langchain4j.
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·4 min
Spring AI vs LangChain4j: How to Choose a Java AI Framework
In-depth comparison of Spring AI and LangChain4j — two major Java AI frameworks — covering core features, completeness, ecosystem support, and usability to help Java developers make the right choice.
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·3 min
Deep Dive into Claude Code's Source Architecture: Harness Engineering and Seven Core Mechanisms
Deep analysis of Claude Code's leaked source architecture, covering TypeScript stack choices, Harness architecture's seven core mechanisms, tool call management, and context optimization.
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