Yes, it’s amazing for giving rails and structure to data so you can be sure an LLM is making more sense than it might with grep and jq. It also allows a little more sanity at scale with jobs like this. You can get pretty crazy with parquet in S3 with an engine like duckdb. And it’s dirt cheap to keep that stuff hanging around for future reference and sanity checking your understanding of things.

For data I reference frequently, and especially which I know will grow over time, I’ve started using Rill because it makes ad-hoc exploration very smooth and low-friction.

My process tends to be something like:

1. Explore logs or some other at least somewhat structured dataset

2. Use Claude to find useful patterns and determine how I might benefit from this data in ways I wasn’t yet aware

3. See how often it’s useful for decision making

4. If it’s frequently useful, formalize it as a view in my Rill instance and refine the models to maximize their utility