Recently, I used Cursor and AI Studio in conjunction with GPT and Gemini to build an enterprise-level crypto intelligence monitoring and semi-automated publishing system from scratch.

The core logic is actually not complicated—24/7 nonstop scanning of the entire internet for cryptocurrency news via RSS, Grok, and various large models, then the system automatically performs information cleaning, quality scoring, content generation, and finally decides the timing and channels for publishing based on traffic algorithms. From raw data input to publication, the entire process requires almost no manual intervention.

This setup is quite practical for teams engaged in intelligence aggregation and market monitoring. Automatic scanning combined with intelligent scoring helps you quickly identify truly valuable information, much more efficient than manual filtering. Especially in the explosive information environment of the crypto market, the ability to automatically capture key data changes and public opinion trends greatly supports decision-making.

Now that AI programming tools are so mature, and with the reasoning capabilities of large models, many workflows that previously required manual work can now be automated. This system is a good example of practical implementation.