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It was all GitHub Spec Kit + Claude Opus tbh. I narrated a couple paragraphs of how I wanted to sync to flow and it knocked it out in one pass practically. Her
by cowlby 6mo ago
It was all GitHub Spec Kit + Claude Opus tbh. I narrated a couple paragraphs of how I wanted to sync to flow and it knocked it out in one pass practically.
Here's the initial spec it created. I started off writing to a local sqlite db instead of Supabase: https://gist.github.com/cowlby/0dbeb52403c3f3c0f1d812250520360d 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/30d6b5cf132fc1424ab146f0eaf4a13b https://gist.github.com/cowlby/30d6b5cf132fc1424ab146f0eaf4a...
https://gist.github.com/cowlby/d569c8e05b5b6eecfd4d237372c06213 https://gist.github.com/cowlby/d569c8e05b5b6eecfd4d237372c06...
(edit: put in Gist instead of inline here)
- mbm 6mo agoThis is really neat, and actually pretty sophisticated. It's like a tiny fintech. How well has the cash flow prediction worked?
- cowlby 6mo agoIt's great because Claude Code generated complex analysis/models 10X better than I was familiar with. 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.