That's so cool! Are you planning to open source any of this? Would love to see how you set everything up, or - maybe most interested in - some of your prompts.
Here's the initial spec it created. I started off writing to a local sqlite db instead of Supabase: https://gist.github.com/cowlby/0dbeb52403c3f3c0f1d8122505203...
Edit: Here's also the DSL categorization spec. First one was string based, found it cumbersome, so second one was the Markdown table refactor: https://gist.github.com/cowlby/30d6b5cf132fc1424ab146f0eaf4a...
https://gist.github.com/cowlby/d569c8e05b5b6eecfd4d237372c06...
(edit: put in Gist instead of inline here)
How well has the cash flow prediction worked?
The key was normalizing the payee/categories so we can analyze month to month, and separating fixed vs variable spend. It then did a fancy Monte Carlo simulation with the computed mean/stddev per payee. And out came T+30/T+60 estimates at P50/P80/P90.