February 2026 monthly summary for microsoft/FluidFramework focusing on a performance-focused delivery for core data-structures. Delivered the FluidFramework B-tree union-based merge optimization by introducing a faster union method, upgrading the B-tree library version, and refactoring the merge logic to leverage the new functionality. This work, committed as 4ba3a899f01a8360391623cb6823534cb408db20 (Co-authored by Claude Sonnet 4.5), improves efficiency of B-tree operations, particularly in workloads involving multiple B-trees. No major bugs fixed this period. Overall impact: stronger scalability and lower CPU costs for B-tree heavy workloads, enabling faster data-sync and collaboration scenarios. Technologies/skills demonstrated: performance optimization, library upgrades, code refactoring, cross-team collaboration, and data-structure proficiency.