No-Code AI Agent Recommends Games Based on Preferences

This article showcases a fascinating approach to building a recommendation AI Agent without writing any code! The author successfully leverages existing tools and data to create a personalized game recommendation system, offering a glimpse into the future of accessible AI development.

• •An AI Agent was created for game recommendations using only Kiro, markdown files, and Tavily's MCP, without any programming.
• •The system analyzes game information to suggest similar games based on the user's preferences.
• •The author emphasizes the ease of using natural language for testing and quickly iterating on features.