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Enterprise adoption often stalls when tools struggle to index millions of legacy files. While frontier models reason through complex logic, latency remains a bottleneck during enterprise-scale navigation. Faster search allows developers to maintain an iterative loop without waiting for the tool to resolve file paths.
The optimizations include non-blocking pre-computation and reduced NAPI (the interface connecting JavaScript to native code) overhead for small result sets. In a demonstration of agentic engineering, the team used Claude to find and implement performance improvements for its own file search logic. These changes ensure the tool remains performant when navigating massive repositories.
Just got a nice DM from a big enterprise customer using Claude Code in one of the world's biggest codebases Here's how we made @-mentions 3x faster in large enterprise codebases 🧵 https://t.co/cDDeJ399ff
