Magnus Helander focused on backend reliability for the MemoriLabs/Memori repository, addressing tool-call corruption in multi-turn conversations by refining conversation history sanitization. He implemented a dedicated sanitization path to ensure compatibility with OpenAI providers, removing orphaned tool roles and empty assistant messages from recalled histories. Using Python, Magnus normalized legacy role formats and corrected injected message counting after sanitization, aligning storage state with request payloads. His work leveraged skills in API integration, data sanitization, and unit testing to reduce OpenAI 400 errors and maintain backward compatibility across providers, demonstrating a deep understanding of provider-specific requirements and robust backend engineering practices.