Świat F1 is a fully autonomous content pipeline that aggregates, filters, localizes, and publishes Formula 1 news in Polish across multiple social platforms. The project was built as a production-grade automation system, not a simple reposting bot.

The core goal was to design an end-to-end workflow where AI acts as a decision-making layer, while the infrastructure handles ingestion, processing, and distribution without manual intervention.

Formula 1 news is published continuously, but most high-quality sources are not localized for Polish audiences. Simply translating headlines is not enough. Timing, context, and platform-specific formatting matter.

Świat F1 addresses this by combining data ingestion, AI-based filtering, and UX-focused localization into a single automated system.

1. Ingestion
News is collected via RSS feeds from major Formula 1 media outlets.

2. Full-text extraction
The pipeline retrieves and parses full article content, not just titles, enabling deeper semantic analysis.

3. AI filtering, localization, and decision making
A single AI request performs multiple responsibilities at once. The model evaluates whether the material qualifies as a real news item, rejecting analytical articles, opinion pieces, or low-value content. The decision is returned explicitly as structured data.

4. Localization and context handling
Localization is embedded directly into the AI logic rather than handled as a separate step. All dates and event times are converted to the Polish time zone (CET or CEST), terminology is adapted for Polish readers, and references specific to Russian-language sources are removed.

5. Multi-platform content generation
If the material is accepted, the same AI response returns a structured JSON payload containing fully localized and platform-specific texts for each channel. Each platform output follows predefined constraints for tone, length, formatting, and audience expectations.

6. Automated publishing
Content is published via official APIs to Telegram, Facebook, Instagram, and other platforms, with duplicate protection and error handling built in.

• Workflow automation: n8n (self-hosted)

• AI layer: OpenAI API for filtering, rewriting, and decision making

• Data ingestion: RSS, HTTP scraping

• Distribution: Telegram API, Facebook Graph API, Instagram Business API

The entire system is designed to be observable, debuggable, and extensible.

This project sits at the intersection of two personal goals. I actively follow Formula 1, and I am currently improving my Polish language skills.

Building Świat F1 allowed me to consume content I genuinely care about, in the language I want to master, while simultaneously designing a real-world automation system that demonstrates my ability to work beyond a single platform or technology.

• Designing AI-driven decision-making pipelines

• Building production-grade automations with n8n

• Working with Meta and Telegram APIs

• Treating localization as a product and UX problem

• Connecting AI agents, data pipelines, and multi-channel publishing into a cohesive system