惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

月光博客
月光博客
Cyberwarzone
Cyberwarzone
L
LINUX DO - 最新话题
N
News and Events Feed by Topic
T
Troy Hunt's Blog
Help Net Security
Help Net Security
S
Security @ Cisco Blogs
Google DeepMind News
Google DeepMind News
Security Archives - TechRepublic
Security Archives - TechRepublic
M
MIT News - Artificial intelligence
G
Google Developers Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
V2EX - 技术
V2EX - 技术
Y
Y Combinator Blog
D
Darknet – Hacking Tools, Hacker News & Cyber Security
大猫的无限游戏
大猫的无限游戏
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Microsoft Security Blog
Microsoft Security Blog
Cisco Talos Blog
Cisco Talos Blog
T
Threatpost
Recent Commits to openclaw:main
Recent Commits to openclaw:main
S
SegmentFault 最新的问题
I
InfoQ
H
Hacker News: Front Page
D
Docker
Scott Helme
Scott Helme
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Blog — PlanetScale
Blog — PlanetScale
人人都是产品经理
人人都是产品经理
博客园 - 叶小钗
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
N
Netflix TechBlog - Medium
AWS News Blog
AWS News Blog
Know Your Adversary
Know Your Adversary
博客园 - 【当耐特】
T
Tor Project blog
U
Unit 42
H
Heimdal Security Blog
Microsoft Azure Blog
Microsoft Azure Blog
K
KPMG report finds enterprise disconnect between AI and its ROI | CIO
P
Privacy & Cybersecurity Law Blog
PCI Perspectives
PCI Perspectives
美团技术团队
O
OpenAI News
T
Tailwind CSS Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
B
Blog
GbyAI
GbyAI
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
MyScale Blog
MyScale Blog

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
You Already Know What Your First AI Rule Should Be. You Just Have Not Written It Down Yet.
Avery · 2026-06-17 · via DEV Community

Every developer who works with AI regularly has a list of corrections they make.

Not a written list. A mental one. The things they fix after every session. The patterns the AI gets wrong consistently. The naming that never quite matches. The component that always ends up doing too much. The state that keeps ending up in the wrong place.

Those corrections are not random. They are consistent. And consistent corrections are rules that have not been written down yet.

You already know what your first rule should be. You have been communicating it to the AI through corrections for months. You just have not written it down where the AI can follow it before it makes the mistake.

Why the first rule is the hardest

Starting a rule system feels like a big decision.

Where do the rules live? How many do you need? What format should they be in? Do you need a whole system before you start? Do you need to cover every case before the rules are useful?

The answer to all of those questions is the same. You do not need to answer them before you write the first rule.

The first rule does not need to be part of a system. It does not need a format. It does not need to be comprehensive. It just needs to exist somewhere the AI can see it before the session starts.

One rule. The thing you correct most often. Written down. Given to the AI before the next session.

That is the entire starting point.

What the first rule usually is

The first rule is almost always the same category of thing across different developers.

It is the correction that happens in nearly every session. The one that takes two minutes to fix but has been taking two minutes every session for six months. The one that feels too obvious to write down because surely the AI should just know.

It does not just know. It cannot. It has no memory of the last correction. It has no definition of what the standard is. It generates based on what it receives and then you correct what it got wrong.

For most React developers the first rule falls into one of three categories. Component boundaries. State placement. Naming conventions. Not because those are the most important rules. Because those are the decisions the AI gets wrong most consistently when no constraints exist.

Here is what writing that first rule actually looks like:

The first rule for most React developers:
Every component has exactly one responsibility.
If it renders UI and manages state and handles data fetching,
it is three components pretending to be one.
Split before continuing.

One rule. Specific enough to follow. The AI stops making that particular decision on its own.

What happens after the first rule

The first rule does two things.

It reduces the correction it covers. That session, the component is already the right size, or the state is already in the right place, or the naming already follows the convention. The specific correction the rule addressed does not appear.

And it shows you that the system works. That writing a rule down and giving it to the AI actually changes the output. That the problem was never the AI. It was the missing constraint.

That realization is what leads to the second rule. And the third. Not because you planned a system. Because you experienced the result of one rule and wanted more of it.

The system grows from evidence, not from planning.

The rule you keep not writing

Most developers who work with AI regularly have a correction they make so often it has become automatic.

They do it without thinking. They barely notice anymore. It is just part of the workflow.

That correction is a rule. A rule the AI has never been given. A rule that has been communicated through corrections hundreds of times and has never transferred because corrections do not transfer between sessions.

Writing it down takes less time than making the correction one more time.

The prompt does not matter. The rules do.

You do not need a complete system to start. You do not need a format. You do not need to know where this is going.

You need one rule. The one you already know. The one you have been communicating through corrections for months.

Write it down. Give it to the AI before the next session. See what happens.

Everything after that is just doing it again.


Want help identifying what your first rule should be?

I built a free 24 point checklist that helps you find exactly that. The corrections you keep making that are waiting to become rules.

Get the React AI Clean Code Checklist — free

Avery Code React AI Engineering System