The Problem: Information Overload Is Real

Every day, we're bombarded with articles, blog posts, news stories, and research papers. The average knowledge worker:

1. Has 50+ browser tabs open with "read later" articles
2. Spends 2-3 hours daily skimming content they'll never fully read
3. Misses important insights buried in lengthy articles
4. Can't keep up with industry news, research, and competitor updates
5. Bookmarks articles that sit unread for months

Reading a 15-minute article to extract 2 key insights is inefficient. But how do you decide what's worth your time before investing the time to read it?

I built iBrief to solve this: get the essence of any article in seconds, then decide if it's worth a deeper read.

The Vision: Read Smarter, Not More

iBrief is an AI-powered article summarizer that extracts key insights from any web article in seconds. The core principles:

The Tech Stack: Modern Full-Stack Architecture

The Architecture: From URL to Summary

When a user pastes an article URL, here's what happens under the hood:

The Summarization Pipeline

1. URL Validation: Check if URL is valid and accessible
2. Cache Check: Look up URL in database—if already summarized recently, return cached result
3. Content Extraction: Fetch page HTML, extract article content using readability algorithms
4. Language Detection: Identify article language for multi-language support
5. AI Summarization: Send content to Claude API with structured prompt
6. Tag Generation: AI extracts relevant categories and tags
7. Database Storage: Save article, summary, tags, and metadata
8. Response Streaming: Return summary with progress updates to frontend

Database Schema Design

The Prisma schema tracks multiple entities:

• Article: URL, title, original content, summary, reading time, tags, source domain
• User: Account info, preferences, saved articles, voting history
• Vote: User upvotes/downvotes on articles for "top articles" ranking
• Tag: Category taxonomy with hierarchical structure (tech → AI, web3, cloud)

Caching is crucial—summarizing the same article twice wastes API calls and user time. The system checks for existing summaries before hitting the AI, reducing costs and improving response times for popular articles.

The AI Integration: Prompt Engineering for Quality Summaries

The quality of summaries depends entirely on prompt engineering. Here's the approach:

Structured Output Format

The prompt instructs Claude to return structured JSON with specific fields:

{
  "summary": "2-3 paragraph summary of key points",
  "keyTakeaways": ["Bullet point 1", "Bullet point 2", ...],
  "tags": ["tech", "ai", "startups"],
  "readingTime": 12,
  "sentiment": "positive|neutral|negative"
}

This structured format ensures consistent UI rendering and enables filtering by tags.

Content Quality Guidelines

The prompt includes specific instructions for summary quality:

• Focus on actionable insights, not just description
• Preserve specific data points (statistics, quotes, names)
• Identify the main argument or thesis
• Note counterarguments if the article presents multiple viewpoints
• Flag time-sensitive information (news events, announcements)

Multi-Language Support

Claude handles non-English articles gracefully. The system detects the source language and can translate summaries to English while preserving key terminology. Users can read summaries of French, Spanish, German, and other language articles without leaving the platform.

The Browser Bookmarklet: One-Click Summarization

The bookmarklet is a key UX feature. Instead of copy-pasting URLs, users can summarize any article with a single click:

1. Drag the "Summarize" button to the browser's bookmark bar
2. Navigate to any article on the web
3. Click the bookmarklet
4. iBrief opens with the summary already generated

The bookmarklet is a simple JavaScript snippet that captures the current URL and redirects to iBrief:

javascript:(function(){
  window.open('https://ibrief.co/?url=' + encodeURIComponent(window.location.href));
})()

This frictionless workflow means users can integrate iBrief into their daily reading habits without changing how they browse. See an interesting article? One click. Summary ready.

The Tagging System: Intelligent Content Categorization

Every summarized article is automatically tagged with relevant categories. The taxonomy is hierarchical:

Primary Categories

Users can filter the "top articles" section by tag, discovering trending content in their areas of interest. The voting system surfaces the most valuable summaries to the top.

Inside iBrief: A Visual Tour

Clean, Focused Interface

The homepage features a single-purpose design: paste a URL and get your summary. No distractions, no complex menus—just the core functionality front and center with beautiful gradient backgrounds and a modern aesthetic.

The Deployment: Kubernetes on DigitalOcean

iBrief runs on a Kubernetes cluster with the following infrastructure:

• DigitalOcean Kubernetes (DOKS): Managed K8s cluster with autoscaling
• PostgreSQL: Managed database with automated backups
• Nginx Ingress: Load balancing and TLS termination
• Let's Encrypt: Automated SSL certificate management
• Trigger.dev: Background job processing for async tasks

The deployment pipeline uses Docker multi-stage builds for optimized images. Kubernetes handles rolling deployments with zero downtime. Health checks ensure traffic only routes to healthy pods.

The Challenges and Trade-Offs

The Results: Time Saved at Scale

The Developer Experience Lessons

Future Roadmap

1. Email Digest: Daily/weekly summaries of saved articles delivered to your inbox
2. RSS Feed Integration: Auto-summarize articles from your favorite publications
3. Custom Prompts: Let users customize summary style—bullet points, executive brief, technical deep-dive
4. Team Sharing: Share summaries with colleagues, comment and discuss
5. Mobile App: Native iOS/Android apps with share sheet integration

Conclusion: AI That Amplifies Human Reading

iBrief isn't about replacing reading—it's about making reading more intentional. By surfacing the essence of any article in seconds, users can make informed decisions about what deserves their full attention.

The technical architecture is deliberately simple: Next.js for the frontend and API, Prisma for data, Claude for AI. No complex microservices. No over-engineered infrastructure. Just a focused tool that does one thing well.

In an age of infinite content and limited attention, tools like iBrief help knowledge workers stay informed without drowning in information. That's the real value—not just summaries, but time to think.

Read smarter, not more. That's the iBrief philosophy.