Worked on the crawl4ai repository to enhance backend reliability and configurability, focusing on both stability and user experience. Addressed core bugs in areas such as screenshots, crawling, serialization, and error handling, using Python and asynchronous programming with Starlette and Redis. Improved content filtering by deduplicating outputs and strengthened browser context management to prevent navigation issues. Extended the API endpoint to support per-request LLM and Redis configuration, allowing dynamic provider selection and flexible deployment. Emphasized robust error handling and increased test coverage, ensuring more resilient production runs and streamlined feature delivery through comprehensive unit testing and code hygiene improvements.