Contest Feedback → Algorithm Insights → Code Documentation → Knowledge Base

Create a post-contest survey asking participants about their algorithm approaches, challenges faced, successful strategies, and suggestions for improvement.

Process all survey responses through Claude to identify common themes, successful algorithm patterns, frequent failure modes, and extract key technical insights about generalization approaches.

Create markdown files in a dedicated repository documenting the identified patterns, with code examples, performance benchmarks, and implementation notes based on the analysis.

Import the GitHub documentation into Confluence, organize by algorithm type and performance category, add tags for easy searching, and create a master index of learnings.