
benchmarks
Measuring ghost-text latency honestly
Learn how to accurately measure AI code completion latency across all four components that affect the delay between typing and seeing suggestions.
Goatfied blog
Developer-to-developer writing. No fluff. Just what worked, what failed, and what shipped.

benchmarks
Learn how to accurately measure AI code completion latency across all four components that affect the delay between typing and seeing suggestions.

benchmarks
A reproducible methodology for benchmarking AI refactoring tools using auditable pass criteria, version control, and automated validation across real repositories.

benchmarks
SWE-bench scores measure isolated patch generation on open-source issues, not the multi-file refactoring and codebase navigation that dominates real development work.

benchmarks
Inline code completion engines must balance response time under 100ms with suggestion accuracy, as latency below 80ms matters more than high acceptance rates.

benchmarks
Learn how to evaluate AI-generated code for production readiness using metrics beyond compilation, including performance impact, architectural patterns, and team conventions.

benchmarks
We tested six AI coding assistants on a 400,000-line Python monorepo with real feature tasks to document how they handle cross-service changes at scale.