#Agent开发
127 related articles
Three Key Takeaways from Hex 4.0: Code as the Backbone, Review-First UX, and Infrastructure Reborn
Hex 4.0 sparks discussion on agent building: code-driven UI over YAML, review-first UX, and rebuilt execution engines and storage for agent workloads—three lessons that echo LangChain's practices and point to a shared direction for agent products.
Java to AI: A Full-Cycle, Production-Grade Agent Development Bootcamp
How can Java developers transition to AI? This article introduces a production-grade Agent development bootcamp covering industry trends, job market demand, target audience, and two enterprise Agent project demos to help Java developers seamlessly transition to AI Agent development.
Java Engineers Transitioning to Agent Development: A Complete Four-Week Learning Roadmap
A roadmap for Java engineers transitioning to AI Agent development: a four-week learning plan from core theory, the ReAct paradigm, and multi-agent collaboration to hands-on projects, analyzing the strengths, gaps, and job-market realities of a career change.
Backend to AI Agent Engineer: What Are P7 Interviewers Really Testing?
Based on a popular Bilibili AI Agent course, this analyzes backend developers' real path to Agent engineer: P7 interviews test engineering stability like strong validation, fallback degradation, and Semantic Cache—not Prompt tricks.
Switching to AI Agent Development in Three Months: Is the ByteDance Expert's Learning Path Reliable?
Breaking down the viral Bilibili three-month AI Agent development learning path: from large model basics, prompting, and function calling to single-Agent practice, RAG and memory, and multi-agent projects. An analysis of its reasonableness, target audience, and the gap between crash-course promises and reality.
LangChain Enterprise Development in Practice: A Complete Path from Zero to Agent Deployment
Analysis of the Bilibili LangChain enterprise development tutorial: environment setup, model invocation, Prompt management, Output Parser, LCEL, RAG, and enterprise Agent deployment, with a zero-foundation learning path and key knowledge points.
Agent Development Learning Path: A Complete Guide to LangChain and LangGraph in Practice
Confused by LangChain, LangGraph, and MCP? This article distills a Bilibili hands-on course, covering environment setup, the create_agent core API, Agent Loop principles, and tool-calling demos to provide a complete Agent development learning path from model integration to multi-agent collaboration.
From Principles to Practice: A Complete Guide to Understanding AI Agents and the ReAct Pattern
Based on a Bilibili hands-on course, this guide explains the essence of AI Agents and the ReAct pattern, then shows how to build a working ReAct Agent from scratch using a system prompt and Python code—ideal for beginners in agent development.
Getting Started with LangChain: Agent Development and RAG in Practice
A Bilibili LangChain tutorial breakdown: what LangChain is, its analogy to Spring, the three LLM limitations (knowledge cutoff, external interaction, statelessness) and how LangChain solves them, plus official docs learning path and Agent development tips.
Spring AI 2.0 in Practice: A Java Developer's Guide to Agent Development
Based on Turing Classroom's Spring AI 2.0 course, this article maps the complete path for Java developers to build AI Agents with Tools, MCP, and Skill, with an airline customer service demo.
Agent Development Engineer: Pivoting to AI from Zero and Catching the Hot New Role Companies Are Desperate to Fill
Agent Development Engineer is a hot new role companies are desperate to fill. Learn why it pays well and how ordinary people can enter in four steps—no algorithms required.
Full Breakdown of the LangChain + LangGraph + MCP + Agent Enterprise Development Learning Path
An analysis of Bilibili creator Loulan's LangChain+LangGraph+MCP+Agent enterprise development course, covering the four-stage learning path, framework selection logic, time travel, and token cost planning to help developers build a complete Agent development system.
Building an MCP Server from Scratch: Let AI Apps Call Your Agent Tools
A hands-on guide to building an MCP server from scratch so AI apps like Claude Desktop can call your Agent tools, covering version negotiation, tool discovery, invocation, error handling, and testing.
Build an AI Agent by Hand Without Frameworks: A Practical JavaScript Guide
Build a runnable AI Agent in pure JavaScript and Node 22 with no frameworks. Covers tool calling, the agent loop, memory, error handling, max-steps guardrails, real failures from a local small model, and when to switch to frameworks like LangGraph.
Building Millisecond-Level Identity Resolution for AI Agents with M|BOX and Python
Based on a YouTube tutorial, this article details how to build a millisecond-level deterministic identity resolution tool for OpenAI Agents using the M|BOX Python SDK: indexing 10,000 CRM records in under 0.2 seconds, single queries in single-digit milliseconds, and field-level scoring for typo tolerance, conflict follow-ups, and no-match hallucination refusal.
LangGraph for Beginners: Agent Flow Control and Enterprise Development in Practice
Based on a Bilibili tutorial, this article explains how LangGraph solves the control problem of Agents in fixed flows, compares the hierarchy of LangChain and Deep Agent, and offers scenario selection advice.
Bilibili's 100-Episode Agent Development Course: A Complete Guide from Zero to Employment
A Bilibili creator offers a 100-episode Agent development course covering fundamentals, advanced topics, hands-on projects, and employment—from Agent principles and Prompt engineering to RAG and multi-agent collaboration, with complete roadmap and interview questions. Ideal for zero-foundation learners starting AI agent development.
Agent Development Engineer: The Most In-Demand Engineering Role in the AI Era — A Four-Step Guide to Breaking In
Agent Development Engineer is the hot new role big tech is scrambling to hire for, with junior salaries reaching 2-3x previous pay. This article explains what the job really involves and lays out a four-step path to break in: prompt engineering, RAG knowledge bases, Agent workflows, and real-scenario practice — ideal for career changers and non-elite university candidates.
The Most Systematic Agent Development Course on Bilibili: From Zero to Enterprise-Level Practice
An in-depth look at a systematic Agent development course on Bilibili: prompts, tool calling, memory and context management, knowledge bases, and multi-agent collaboration, with practical projects aligned to enterprise hiring.
The Most Comprehensive Agent Development Tutorial on Bilibili: From Zero to Expert in Seven Days
A Bilibili creator releases a 748-episode zero-foundation AI Agent tutorial in three parts: cognition, advanced, and hands-on, covering ReAct, LangChain, AutoGen, multi-Agent collaboration, and enterprise projects, with source code and a learning roadmap.