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110 related articles
·7 min
The Agent Engineer Transition Roadmap: A Deep Dive into Three Core Skill Systems
Want to become an Agent engineer? This article systematically covers three core skill tracks—LLM fundamentals, LangChain architecture development, and enterprise deployment—to help you avoid detours.
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·7 min
Dify 1.8.0 in Practice: A Complete Guide to Building Enterprise-Grade AI Workflows with Zero Code
An in-depth walkthrough of deploying Dify 1.8.0 and building applications: three-step Docker deployment, five app types compared, and Workflow vs Chatflow use cases—build enterprise AI apps with zero code.
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·7 min
Harness Engineering: The Six-Layer Engineering Framework for Enterprise AI Agent Deployment
From Prompt Engineering to Harness Engineering, a deep dive into the core challenge of truly deploying AI Agents in enterprises. This article breaks down the six-layer architecture and shares real-world Hermes Agent practice.
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·7 min
Getting Started with OpenAI LLM Development: A Practical Guide to Model Selection, Token Pricing, and API Usage
A systematic guide to the three cores of OpenAI LLM app development: GPT-4/GPT-3.5 model selection, token billing and cost-saving tips, and practical use of the Models, Completion, and Chat Completion APIs.
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·4 min
Career Switch to LLM Development: A Four-Level Skill Progression Roadmap
Want to switch careers into LLM development but don't know where to start? This guide breaks down a four-level skill roadmap — from basics and API calls to RAG, fine-tuning, Agent development, and multimodal — to help you build real AI career value.
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·6 min
AutoScout24's AI-Native Journey: How Codex and Agents Are Reshaping Enterprise Efficiency
As one of the world's largest car marketplaces, AutoScout24 is going AI-native with OpenAI Codex and agents. It built a CapEx agent in 48 hours, saving ~$1M/year, and explores hands-off coding.
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·7 min
The Trap of AI Visibility Dashboards: Why Most Metrics Are Meaningless
Can a brand's "visibility" in AI answers really be quantified? This article deeply dissects the methodological flaws of AI visibility dashboards—from LLM output randomness and black-box mechanisms to vanity metric traps.
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·6 min
Coze from Scratch: A Complete Guide to Building Multi-Agent Collaboration
A detailed guide to Coze's core features: cross-platform interoperability, the Skills system, multi-agent collaboration, and workflow building. Compare Coze and Dify to build practical AI apps with zero coding.
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·6 min
AI Agent Learning Roadmap: A Four-Stage Guide from Beginner to Practical Mastery
A systematic AI Agent learning roadmap in four progressive stages: fundamentals → ReAct core paradigm → memory & tools → multi-agent collaboration. Master LangChain, AutoGen, and more, growing from beginner to practical developer in three months.
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·5 min
A Programmer's Guide to Large Language Models: The Complete Path from Prompts to Agents
A tailored large-model learning path for ordinary programmers: from prompt engineering, API calls, and LangChain, to RAG, Agents, fine-tuning, and enterprise deployment—six steps to build AI application skills fast.
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·7 min
Otari: A Comprehensive Look at the Open-Source LLM Control Plane Tool
An in-depth analysis of the open-source LLM control plane tool Otari—covering unified multi-model access, cost observability, and security compliance governance to help teams build manageable, production-grade AI infrastructure.
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·3 min
Unsloth Major Update: GLM-5.2 Support, 3x Longer Context, and a New Model Hub
Unsloth v0.1.471-beta adds full GLM-5.2 support, 3x longer context (up to 200K tokens on a single GPU), a new Model Hub, and Chat Canvas — a major leap for local LLM fine-tuning.
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·5 min
Introduction to Prompt Engineering: A Complete Guide to Core Concepts, Methodologies, and Limitations
Prompt engineering is a core skill in the AI era. This article breaks down the essential differences between prompts and prompt engineering, the six-step workflow, four evaluation criteria, and key limitations like context limits and hallucination.
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·6 min
Semi-AI Mode: A Practical Guide to Implementing API Automation Testing
Can't make pure AI work? This guide explores the Semi-AI approach to API automation testing, covering key challenges, enterprise framework design, and how AI and frameworks work together for maximum impact.
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·6 min
LangChain 1.0 Comprehensive Guide: Three Core Frameworks and Hands-On AI Application Development
Deep dive into LangChain 1.0's architecture: LangChain framework, LangGraph multi-Agent orchestration, and LangSmith observability platform, with hands-on RAG and intelligent customer service projects.
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·5 min
Cursor Reshapes AI Programming: Cloud Agents, the Origin Platform, and a Custom-Built Foundation Model
Cursor launches three major products: cloud agents on mobile, Origin — an agent-native Git platform challenging GitHub, and a custom foundation model with 10-20x compute. AI coding enters the Agent-First era.
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In-Memory Layer Mapping: How to Effect…
·2 min
In-Memory Layer Mapping: How to Effectively Solve LLM Context Overload
Context overload is a core pain point for LLM deployment. This article breaks down In-Memory Layer Mapping, compares it with RAG, and offers practical architecture insights for AI engineering teams.
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·3 min
Full-Stack AI Development with Vercel: A Complete Guide to AI SDK, RAG, and Production-Ready Applications
Master full-stack AI development with Vercel: from LLM, RAG, and vector embeddings to AI SDK, AI Gateway, and v0 — build production-ready AI web apps end to end.
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·6 min
Dify Self-Hosted Deployment in Practice: Building an Enterprise-Grade AI Application Platform from Scratch
A complete guide to self-hosting Dify, the open-source AI platform: environment setup, Docker Compose deployment, LLM integration, and app building. Runs on just 2 cores and 4GB RAM.
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·3 min
Dify Comprehensive Guide: The Open-Source Platform for Building AI Apps Without Code
Deep dive into Dify, the open-source LLM app development platform featuring visual workflow engine, RAG knowledge base, Agent capabilities, hundreds of model integrations, Docker deployment, and comparisons with LangChain, Coze, and FastGPT.
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