AI 教程与实战
收录 AI 工具教程、提示词、安装部署、配置指南、开发实战与可复现步骤。
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教程 / 实战普通
Intesta: an attested fact registry that AI agents query through MCP instead of scraping stale pages
AI agents already answer questions about small businesses. Most of the time they do it from stale...
信息来源:DEV Community
教程 / 实战普通
Make Your Code Review Agent Write Down How the Bug Actually Happens
My review agent turned a 1,000-line feature into 4,000 lines by flagging attacks that could never happen. One required field in every finding fixed it.
信息来源:DEV Community
教程 / 实战普通
Breeze v2: An AI-First Go Framework Built for MCP, Agents, and Distributed Systems
What if your backend wasn't just built for humans and services — but for AI agents too? That's the...
信息来源:DEV Community
教程 / 实战普通
Dev log #20 Deleting 180k lines and chasing socket leaks: A week in the OSS trenches
Yash K Saini — Engineer, building in public — AI/ML, low-level (Rust/C/C++), and open source. GitHub...
信息来源:DEV Community
教程 / 实战普通
AI Can Write Your Code. But Can You Explain What It Wrote?
We’re entering an era where producing code is becoming easier. Understanding what we produce may be...
信息来源:DEV Community
教程 / 实战普通
How to Run an AI Model on Almost Any Hardware: A Practical Guide to Tiny Local LLMs
This month a developer ran a working language model on a Sony PSP-2000. That is a 333 MHz MIPS...
信息来源:DEV Community
教程 / 实战普通
vincent v0.8.0: From Agent Conversations to Durable Workflows
I've released vincent v0.8.0, and this release pushes the project much further toward the workflow...
信息来源:DEV Community
教程 / 实战普通
Why I Taught My AI Agent to Forget
I've spent about 700 hours in Claude Code over the last year, building a personal AI assistant that...
信息来源:DEV Community · Claude
教程 / 实战普通
With Context Windows This Large, Why Do We Still Need Memory?
I've been reading through dev communities lately, and this exact topic keeps showing up in different...
信息来源:DEV Community
教程 / 实战普通
The Real Cost of LLM APIs in 2026: A Developer's Field Guide
Every week someone asks a version of the same question: "How much will this actually cost me per...
信息来源:DEV Community
教程 / 实战普通
Can Rust Make Unsafe AI Agent Actions Unrepresentable?
I went looking for a better runtime check and found a different way to think about the problem. I...
信息来源:DEV Community
教程 / 实战普通
Inside nano-vLLM: What an RTX 3090 Reveals About LLM Serving
0. What I studied and what I found I studied nano-vLLM as a small LLM serving engine:...
信息来源:DEV Community
教程 / 实战普通
Building DevLog: What Happens When You Tell an AI to Think Like a Security Engineer First
Submission for the Cloud Run AI Challenge — #AccelerateAIwithCloudRun When I started this challenge,...
信息来源:DEV Community
教程 / 实战普通
Tripo + Astra 工作流:用隐藏网格实现角色表情切换
创作者用 Tripo 生成同一角色的多个表情差分模型,将当前表情以外的网格缩至极小藏进头部,再通过驱动器切换,从而绕开 Blender 形状键的高难度操作。该方案由 Astra 完成大部分设置,缺点是消耗大量 Tripo 额度、无中间表情、无法合成表情,且 VRM 等加载端多不支持。
信息来源:Tripo(官方 X)
教程 / 实战普通
I Rebuilt My RAG Pipeline Without LangChain — What Got Better and What Got Worse
The first time I seriously doubted the framework was not because the model hallucinated. It was...
信息来源:DEV Community
教程 / 实战普通
Giving AI Agents the Same RBAC Rules as Your Users: Building a Laravel Permission Layer LLMs Actually Respect
AI agents don’t use web browsers. They don’t click buttons, submit forms, or trigger standard HTTP...
信息来源:DEV Community
教程 / 实战普通
Building a Production RAG Pipeline with n8n, Qdrant, and Gemini: A Step-by-Step Walkthrough
The first version of a RAG system always looks convincing. You connect a document loader, a vector...
信息来源:DEV Community · Gemini
教程 / 实战普通
Multi-Agent Orchestration in Laravel: Coordinating Specialists Instead of One Giant Prompt
The first version of most AI features is not a system. It is one giant prompt doing too many...
信息来源:DEV Community
教程 / 实战普通
The Hidden Cost of AI Agents: A Token Budget Framework for Production Laravel Apps
Your Laravel app adds an agent. The controller action looks harmless: one user message, one model...
信息来源:DEV Community
教程 / 实战普通
We Deleted Our Vector Database. Postgres Was Faster.
We paid for a vector database for a year. It was faster than Postgres at the one thing it does. We...
信息来源:DEV Community
教程 / 实战普通
Why Better Prompts Won't Save Your Broken AI Agent
The tenth prompt tweak usually feels like progress. The eleventh reveals the problem: the fix that...
信息来源:DEV Community
教程 / 实战普通
Why AI Agents Need an Evaluation Loop, Not Another Better Prompt
The tenth prompt tweak usually feels like progress. The eleventh reveals the problem: the fix that...
信息来源:DEV Community
教程 / 实战普通
The Next RAG Problem Isn’t Retrieval — It’s Knowing When Not to Retrieve
The most expensive RAG failure is often not an empty search result. It is a confident answer built...
信息来源:DEV Community
教程 / 实战普通
RAG vs Memory vs Tools: What Information Should an AI Agent Actually Store?
The first time an AI agent remembers something useful, it feels like product magic. The first time...
信息来源:DEV Community
教程 / 实战普通
n8n: When AI Writes the Workflow, Who Reviews the Workflow?
The most dangerous AI-generated n8n workflow is not the one that fails immediately. It is the one...
信息来源:DEV Community
教程 / 实战普通
n8n Can Now Build Its Own Workflows — What Could Possibly Go Wrong?
The dangerous part is not that a system can generate an n8n workflow as JSON. The dangerous part is...
信息来源:DEV Community
教程 / 实战普通
From Prompt Engineering to Context Engineering: The Skill AI Developers Actually Need
The most dangerous failure in an LLM application is not a bad prompt. It is a perfect prompt wrapped...
信息来源:DEV Community
教程 / 实战普通
GPT-6 vs. Claude 5.1 vs. Gemini 4: A Code Test
Ask any frontier model to implement binary search, and the answer will look impressive. Ask it to...
信息来源:DEV Community · GPT / Claude / Gemini
教程 / 实战普通
Is History Repeating Itself? From the PC Era to the AI Era: A Developer’s Take on the Hype and Healthy Skepticism
Note: This article is a developer-focused adaptation of my original blog post in Italian. You can...
信息来源:DEV Community
教程 / 实战普通
When Your Benchmark Finally Tells the Truth
Update — v0.1.0 released. CauterRule is now live on GitHub and PyPI. It turns repeated agent...
信息来源:DEV Community
教程 / 实战普通
Your agent orchestrator is a black box. Mine is a folder.
An experimental, repo-local coordination layer for coding agents: folders are columns, Markdown files are tickets, and Git is the audit log.
信息来源:DEV Community
教程 / 实战普通
Speculative decoding won't change your model's distribution. It might still change your output.
There's a thread on the DeepSeek-R1 model page that's been sitting unresolved since March last year,...
信息来源:DEV Community · DeepSeek
教程 / 实战普通
RAG Poisoning Is a Supply Chain Attack, Not a Prompt Injection Variant
In August 2024, researchers demonstrated a silent attack against Microsoft 365 Copilot. Any user with...
信息来源:DEV Community
教程 / 实战普通
AI Agents Are eval(userInput) With Extra Steps
In July 2025, a developer asked the Replit AI agent to make minor fixes during a code freeze. The...
信息来源:DEV Community
教程 / 实战普通
JSON, CSV, and YAML Are Not Safe Formats for AI Agents: They Are Attack Vectors
JSON, CSV, and YAML Are Not Safe Formats for AI Agents: They Are Attack Vectors A...
信息来源:DEV Community
教程 / 实战普通
The Next.js Security Checklist for AI-Generated Code
Here's a number that should make you check your own repo: an audit of over 200 vibe-coded...
信息来源:DEV Community
教程 / 实战普通
It Only Sent a GET. Why Did It Write? Effect Boundaries in Agent Tool Gates
GET is a method, not proof of no write. Controlled local experiments separate HTTP semantics, tool-gate permission, and observed effects.
信息来源:DEV Community
教程 / 实战普通
Binary Search Trees
Why should you care? Imagine you have thousands or millions of numbers and frequently need...
信息来源:DEV Community
教程 / 实战普通
Agent Code Execution Collapses the Trust Model to the Container Runtime
Agent Code Execution Collapses the Trust Model to the Container...
信息来源:DEV Community
教程 / 实战普通
I Tested 5 Local LLM Sizes in n8n. The 1.5B Model Beat 14B on Tool-Calling.
I spent a weekend benchmarking Qwen2.5 at five sizes — 0.5B, 1.5B, 3B, 7B, 14B — through five real...
信息来源:DEV Community · Qwen