#intelligent agent development
1473 related articles
·3 min
LangChain Practical Guide: From RAG Applications to Intelligent Agent Development
A comprehensive guide to LangChain: core concepts, RAG applications, Agent development, version selection (0.3/1.0), and career opportunities for Java/Python developers entering LLM development.
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·2 min
AI Agent Learning Path: Mastering Intelligent Agent Development from 0 to 1
Many people learn tons of fragmented content yet remain confused. This article maps out the complete AI Agent knowledge landscape—from LLM and prompt basics, tool calling, and RAG to LangChain and multi-agent collaboration—with a clear learning order.
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·3 min
Getting Started with AI Agent Development: A Complete Learning Path to Building Intelligent Applications from Scratch
AI Agents are reshaping software development with 42.8% market CAGR. Learn the difference between Agents and traditional AI, plus a complete LangChain-based curriculum to launch your career in intelligent agent development.
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·3 min
AI Agent Core Architecture Breakdown: From Concept to Enterprise-Grade Intelligent Agent Development
Deep dive into AI Agent architecture: perception, brain, and action modules. Covers RAG memory systems, tool calling mechanisms, Chain of Thought reasoning, and enterprise agent development roadmap.
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Tutorials·3 min
AI Agent Practical Development: A Complete Guide from Concept to Building Production-Grade Intelligent Agents
A deep dive into AI Agent core principles and practical development paths, covering perception-decision-execution capabilities, MCP protocol tool integration, and analysis of Manus and AutoGLM.
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Tutorials·3 min
Hands-On Intelligent Agent Development with LangGraph: From Getting Started to Full Project Architecture
A deep dive into intelligent Agent development with LangGraph, covering core concepts, project architecture, state management, and practical tips for building AI agents in Python.
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·2 min
Voice AI Migration Pitfall Guide: Handoff Failures and Solutions During Parallel Operation
During enterprise voice AI migration, parallel operation periods often encounter context loss and unstable handoff routing. This article analyzes core pain points through real cases and provides practical solutions.
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·3 min
A Practical Guide to Preventing Context Loss During Cursor Development
Learn how to prevent context drift in Cursor, Claude Code, and other AI coding agents using AGENTS.md, layered rules, validation checklists, and structured workflows.
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·3 min
Kiro Crew: An Open-Source Agentic Development Workspace with Persistent Memory
Kiro Crew is an open-source agentic development workspace that solves AI coding assistants' cold start problem through persistent memory, multi-agent collaboration, and purpose-built Apps.
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·2 min
Dynamic Workflows: A New Paradigm for AI-Driven Quantitative Strategies
Explore how dynamic workflows are transforming quantitative strategy development. From agent orchestration to adaptive strategy iteration, discover the potential and challenges of AI-driven workflows.
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·3 min
Qwen3.8-Max Released: A New Benchmark in Autonomous Programming with 2.4 Trillion Parameters
Alibaba releases Qwen3.8-Max with 2.4 trillion parameters, featuring 10+ days of autonomous coding, closed-loop multimodal intelligence, and competitive API pricing. Open weights coming next week.
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·3 min
Zero-Mem: How Zero-Token Memory Solutions Reduce LLM Agent Costs
Deep dive into Zero-Mem's zero-token memory approach for LLM agents, exploring how decoupling memory from token consumption cuts inference costs and enables scalable agent deployment.
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·3 min
GitHub Daily · August 6: Giving AI Agents a Real Computer
GitHub Trending Aug 6: Cloudflare/computer surges 900 stars giving AI Agents real computing environments, while AutoGPT, Guava, and authentik show Agent infrastructure is the new battleground.
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·3 min
Cursor Agent vs Codex: Which Should Visual AI Developers Choose?
In-depth comparison of Cursor Agent Window vs OpenAI Codex for Vision AI development, analyzing large task handling, multi-file edits, debugging, and long-running tasks to help developers decide.
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·3 min
Running a Local AI Voice Assistant on a $50 Arduino Board: A Practical Guide to Edge AI
How to run a fully local AI voice agent on a $50 Arduino Uno Q board, covering speech recognition, intent understanding, and TTS implementation for edge AI applications.
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·3 min
Vibe Buddy: A Desktop Hardware Companion That Makes AI Coding Status Visible
Vibe Buddy is a desktop robot that displays real-time Codex and Claude Code status and usage quotas, helping developers track AI task progress without switching windows.
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·3 min
The 5-Layer AI Tech Stack Explained: A Complete Industry Chain from Energy to Applications
Deep dive into the 5-layer AI tech stack: Energy, Chips, Infrastructure, Models, and Applications. Understand the key players, competitive landscape, and value distribution logic across the AI industry chain.
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·3 min
GrowthBook 5.0: Deep Dive into the AI-Native All-in-One A/B Experimentation & Growth Platform
GrowthBook 5.0 unifies feature flags, A/B experimentation, and product analytics into an AI-native, warehouse-native platform. Deep dive into its AI Visual Editor, Agent Skills ecosystem, and value for growth teams.
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·2 min
Cursor's Unlimited Auto Plan Is Ending: How Developers Burning 300M Tokens/Month Can Control Costs
Cursor's Unlimited Auto plan is ending. Learn how developers consuming 300M+ tokens/month can control AI coding costs with optimized workflows and hybrid tool strategies.
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·3 min
GitHub Daily · August 5: AI Agents Enter the 'Production Engineering' Era
GitHub Trending Aug 5: AI Agents shift from demos to production with new projects for state management, long-term memory, skill systems, and security.
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