Frostbite Gazette: AI-Curated Canadian Journalism

Update (2026-10-23): is archived and both of its domains have lapsed. This piece is kept as a record of the build, not as a live product. The current work is on the projects page¹.

The Problem

Canadian journalism is fragmented. National stories get covered by dozens of outlets, each with different angles, different biases, and different paywalls, the walls that make you pay before you can read. Local stories often get missed entirely.

As someone who cares about staying informed — and as someone who builds things with AI — I wondered: could I build an automated system that aggregates, gathers the pieces into one place, filters, and curates Canadian news using AI, a model that reads a story and scores it?

That’s Frostbite Gazette.

The Architecture

[40+ RSS Feeds] → [Cloudflare Workers] → [Groq AI Filter] → [Astro SSG] → [Cloudflare Pages]

The system runs on two free tiers, two free plans:

Cloudflare Workers (free: 100k requests/day) — fetches feeds, runs AI filtering
Cloudflare Pages (free: unlimited static sites) — hosts the generated site
Groq (free tier) — fast LLM inference, a language model reading the article and scoring it, for content analysis

Data Flow

Scheduled Worker runs every hour via Cron Triggers, a timer that starts the job,
Fetches RSS/Atom feeds from 40+ Canadian news sources
Sends each article through Groq for classification and scoring
Filters for relevance, Canadian focus, and quality signals
Writes curated results to KV storage, a small shelf of named values,
Triggers Astro rebuild via Pages CI, the build that runs when the pages should update,
Static site regenerates with new content

The AI Pipeline

This is where the interesting work happens. Raw RSS feeds, the automatic headlines a site publishes, are noisy — lots of duplicates, opinion pieces masquerading as news, and low-quality content.

Classification

Each article gets classified on three dimensions:

interface ArticleClassification {
  relevance: number;    // 0-1: How relevant to Canadian readers
  accountability: number; // 0-1: Does it hold power to account?
  quality: number;      // 0-1: Factual, well-sourced reporting
  topics: string[];     // ["politics", "climate", "economy"]
  region: string;       // "national", "prairies", "bc", etc.
}

The Prompt

The classification prompt is carefully structured:

You are a Canadian journalism curator. Analyze this news article:

Title: {title}
Source: {source}
Excerpt: {excerpt}

Score on these criteria (0.0-1.0):
1. RELEVANCE: How relevant to Canadian readers?
2. ACCOUNTABILITY: Does it hold power to account? Factual reporting over opinion.
3. QUALITY: Well-sourced, factual, balanced reporting?

Also identify:
- Primary topic (politics, economy, climate, health, tech, indigenous, justice, other)
- Geographic focus (national, bc, alberta, prairies, ontario, quebec, atlantic, north)

Respond in JSON only.

Filtering Rules

Articles must meet minimum thresholds:

Relevance >= 0.7 — Must be relevant to Canadian readers
Accountability >= 0.5 — Prefer factual reporting over opinion
Quality >= 0.6 — Must be well-sourced and balanced

Articles that don’t pass get filtered out. This typically reduces 200+ raw articles to 30-50 curated pieces per cycle.

The Frontend

Frostbite Gazette is built with Astro, the tool that builds the pages ahead of time, for maximum performance:

Static generation — Pages are pre-built, no server rendering, no program assembling the page on each visit
Zero JavaScript by default — Astro’s islands architecture, a script only for the parts a person can click, means only interactive components ship JS
Fast — Lighthouse 100/100 on performance

Key Features

Topic filtering — Browse by politics, climate, economy, etc.
Regional sections — National, provincial, and territorial coverage
Source diversity — Track which outlets contribute to each story
Minimal design — Text-first, fast-loading, accessible

Cloudflare Workers Implementation

The feed aggregator runs as a scheduled Worker:

// Simplified version of the feed aggregator
export default {
  async scheduled(event: ScheduledEvent, env: Env) {
    const feeds = await loadFeedList(env.KV);
    const articles: Article[] = [];

    // Fetch all feeds in parallel
    const feedResults = await Promise.allSettled(
      feeds.map(url => fetchFeed(url))
    );

    // Collect successful results
    for (const result of feedResults) {
      if (result.status === 'fulfilled') {
        articles.push(...result.value);
      }
    }

    // Deduplicate by title similarity
    const unique = deduplicateArticles(articles);

    // Classify with Groq (batched for speed)
    const classified = await classifyBatch(unique, env.GROQ_API_KEY);

    // Filter and rank
    const curated = classified
      .filter(a => a.relevance >= 0.7 && a.quality >= 0.6)
      .sort((a, b) => (b.relevance + b.accountability) - (a.relevance + a.accountability))
      .slice(0, 50);

    // Store in KV for the Astro build to consume
    await env.KV.put('curated-articles', JSON.stringify(curated));
  }
};

Why Groq

Speed matters when you’re processing 200+ articles per cycle. Groq’s LPU architecture, hardware built to run language models quickly, gives me:

~500 tokens/sec on Llama 3 8B
Classification in ~100ms per article
Total pipeline in under 30 seconds

For comparison, the same workload on a standard would take 3-5 minutes. When you’re running hourly, that difference adds up.

Challenges and Learnings

RSS Feeds Are Messy

No two RSS feeds are alike. Some use Atom, some use RSS 2.0. Some have full content, some have excerpts. Some are broken XML. Building a robust feed , a reader that can survive a messy file, was half the work.

AI Classification Isn’t Perfect

The AI sometimes misclassifies satire as news, or misses regional relevance. I handle this with:

Manual overrides — I can flag articles the AI got wrong
Confidence thresholds — Low-confidence classifications get human review
Source reputation — Outlets with consistent misclassification get adjusted weights

Free Tier Limits

Cloudflare Workers free tier has limits:

100k requests/day (plenty for hourly feeds)
10ms CPU time per invocation (tight for AI calls, mitigated by batching)
KV writes limited to 1k/day (only write the final curated set)

I haven’t hit any of these limits yet.

Results After One Month

~1,200 articles processed from 40+ sources
~150 curated stories published
~35 articles per day pass quality filters
Average page load: < 1 second
Cost: $0 (entirely on free tiers)

What’s Next

Newsletter integration — Daily digest email via Cloudflare Email Workers
Source transparency scoring — Rate outlets on bias, correction frequency, and sourcing
Indigenous news coverage — Dedicated section with AI-assisted cultural sensitivity checks
Community submissions — Let readers flag stories and suggest sources

Frostbite Gazette is proof that you can build a meaningful, AI-powered product on free infrastructure, machines you do not have to rent by the hour. The tools are there. The APIs are there. The only thing between you and a shipped product is the decision to start building.

Projects. The current work, on the other site. ↩