As engineering organizations scale, merging code into a shared codebase becomes a major productivity bottleneck. Thousands of engineers changing code continuously can overwhelm build systems, slow feedback loops, and erode trust in the mainline.

This talk explores how large teams keep builds green while maintaining high developer throughput by treating code integration as a systems problem. We’ll introduce the core ideas behind speculative merging, including dependency graphs, speculation trees, and invalidation, and show how predicting likely future states of the codebase enables parallelism without sacrificing correctness.

We’ll examine why naive approaches don’t scale, how combinatorial explosion and finite CI resources shape real-world designs, and what tradeoffs are required to make speculation practical. Finally, we’ll share lessons learned from evolving SubmitQueue over several years, highlighting how build stability, fast feedback, and merge confidence directly impact engineering productivity.