Large Language Models (LLMs) are excellent at generating text, but asking them to be witty, logical, or visually creative in a structured format is a different challenge entirely.
With Rebuzzle, I set out to build more than just a wrapper around OpenAI or Anthropic. I wanted to create a self-correcting, learning system capable of generating high-quality puzzles, from Rebus visual wordplay to complex Logic Grids, that are actually solvable and fun.
Here is a technical deep dive into how Rebuzzle works, moving beyond simple prompts to a sophisticated multi-agent orchestration system.
The Architecture: Serverless & Event-Driven
Rebuzzle is built on a modern, production-ready stack designed for modularity and scale. At its core, it utilizes and the , backed by for vector storage and analytics.