During February 2026, Christian Schramm developed a feature for the Blaizzy/mlx-audio repository that introduced a system_prompt parameter to the Qwen3ASR transcription methods. By enabling custom prompts within the transcription pipeline, he improved the adaptability and accuracy of audio-to-text outputs across diverse domains. The implementation, written in Python and leveraging audio processing and machine learning techniques, allowed for tailored prompt injection, supporting more consistent and domain-specific transcriptions. Although the work focused on a single feature and did not address bug fixes, it established a technical foundation for future prompt experimentation and fine-tuning workflows within the project’s architecture.