
1/22/2026
What this post added
This post evaluates the effectiveness of different abstractions (SQL, bash, filesystem) for AI agents querying structured data. It details an evaluation harness, compares the performance and accuracy of SQL, bash, and filesystem agents, identifies performance bottlenecks in bash tools (e.g., `stat()` calls), and proposes a hybrid approach combining SQL and bash for improved accuracy and self-verification. It also highlights the importance of robust evaluation methodologies and the iterative improvement of tools like `just-bash`.