Worked on the tathagatasrimani/codesign repository to deliver a feature focused on scheduling and architecture search optimization. The work centered on refining core algorithms in Python, specifically improving the handling of buffer and memory nodes and enhancing the logic for selecting functions during architecture search. Emphasis was placed on optimizing time accounting and resource allocation, enabling faster and more predictable design iterations. The approach leveraged skills in algorithm design and code optimization to create a more scalable and maintainable exploration workflow. These improvements prepared the repository for efficient architecture search with better performance characteristics and streamlined resource utilization for future development.