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

WordPress大学
WordPress大学
小众软件
小众软件
MongoDB | Blog
MongoDB | Blog
Hugging Face - Blog
Hugging Face - Blog
Jina AI
Jina AI
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Stack Overflow Blog
Stack Overflow Blog
L
LangChain Blog
大猫的无限游戏
大猫的无限游戏
量子位
A
About on SuperTechFans
G
Google Developers Blog
雷峰网
雷峰网
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
IT之家
IT之家
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园_首页
H
Hackread – Cybersecurity News, Data Breaches, AI and More
Vercel News
Vercel News
V
Visual Studio Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博客园 - 聂微东
U
Unit 42
Apple Machine Learning Research
Apple Machine Learning Research

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
I Built an AI SEO Brief Generator That Compares 3 Models ...
Key-wxh · 2026-06-15 · via DEV Community

Key-wxh

I spent 3 months building an SEO content brief generator, and I wanted to share the technical architecture with the dev.to community.

The Problem

SEO content briefs are the pre-writing research phase for blog posts — you analyze the SERP, figure out search intent, outline the article structure, and suggest metadata. Most people do this manually, spending 1-2 hours per article.

The Solution

seobrief.cc — keyword in, complete brief out in ~30 seconds.

Technical Architecture

Frontend: Next.js 16 + Tailwind v4 + React Server Components
Backend: Next.js API routes (edge-compatible)
Database/Auth: Supabase (Postgres + Auth + Row Level Security)
Payments: Stripe Checkout (subscription)
AI: 3 LLMs running in parallel:

  • DeepSeek V3 (primary, best quality)
  • Qwen (backup, fast)
  • Moonshot (backup, different perspective)

Hosting: Vercel (production), with @vercel/analytics for traffic

How the Multi-Model Comparison Works


typescript
// Simplified — the actual route calls 3 providers in parallel
const [deepseek, qwen, moonshot] = await Promise.allSettled([
  generateBrief(keyword, 'deepseek'),
  generateBrief(keyword, 'qwen'),
  generateBrief(keyword, 'moonshot'),
]);

// Score each result, return all 3 + recommendation
const results = [deepseek, qwen, moonshot]
  .filter(r => r.status === 'fulfilled')
  .map(r => ({ ...r.value, score: scoreBrief(r.value) }));

return { results, recommended: results.sort((a, b) => b.score - a.score)[0] };