Developed a Gmail body extraction fallback for the Significant-Gravitas/AutoGPT repository, enhancing the resilience of email-driven data ingestion workflows. The solution introduced a mechanism in Python backend code to continue extracting email content by reverting to raw HTML when html2text conversion fails, thereby reducing extraction outages. This approach incorporated robust exception handling and comprehensive unit and regression testing to validate the fallback path, ensuring reliability for downstream features. Collaboration with a co-author facilitated the resolution of a related issue, and the work focused on improving the stability of Gmail-based content ingestion without introducing disruptions during converter failures or updates.