Worked on the menloresearch/ichigo repository to deliver Ichigo v0.4, introducing a unified training pipeline by consolidating Phases 2 and 3. This update improved context handling, noise management, and multi-turn capabilities, resulting in an MMLU score of 64.63 and enhancing model reliability. The work involved refining training data and streamlining the release process to reduce maintenance overhead. Addressed documentation by fixing a README bug, updating the demo URL to improve accessibility for live demonstrations. Utilized Markdown for documentation and contributed to the overall readiness of the project for customer-facing use, focusing on maintainability and demonstration support.