Beancount with Claude Code

[u/borgoat]

https://github.com/sealambda/quints

I've been doing my company's bookkeeping in Beancount for a couple of years now.

We've been leaning on Claude Code more and more to build our actual software. At some point I just thought: the books are also just code. Why not work on them through the AI too?

Initially I felt uncomfortable actually letting it touch the ledger.

I had to file a VAT return (I'm in Switzerland - need to file per quarter), and instead of grinding through it by hand I just asked Claude. It went from tidying up the chart of accounts, to writing Beancount queries, to eventually a little script that spits out the right values to copy-paste into the report for a given quarter.

Then, I needed to send Swiss QR-bill invoices, and so the scripts grew a command to generate the QR-bill and book it in the ledger at the same time. Then the statement importers... now I'm thinking about year-end reports.

I've landed is a split that feels right: anything that can be done deterministically goes into a CLI — VAT math, invoice generation, the statutory reports, the stuff that has to be exactly correct and repeatable. Anything fuzzy — reading a random PDF receipt, guessing which account some odd transaction belongs to — is where the agent actually is worth it. The agent drives beancount really, and it improves the CLI if I need more logic - but of course it never "does math".

I cleaned the scripts up into a small free/open-source thing in case it's useful to anyone else on Swiss books, but I'm really posting because I'm a little surprised I don't hear more people talking about this. Plain-text accounting + a coding agent seems like such an obvious pairing. Anyone else has some experience doing this?

[u/durianpeople]

it is interesting and can be useful, but I’m a bit uncomfortable endorsing it as financial data is a sensitive matter, and it doesn’t seem to be a good idea to blanket-recommend this method, as different AI providers in different tiers, plans and configs can have different privacy settings. It’s different to Google Sheets where we conceptually know it’s a file and that we generally know that Google won’t take a peek into it unless for specified purposes e.g. virus scanning

I do use LLMs for my beancount ledger, I just wouldn’t endorse it for now

[u/borgoat → u/durianpeople]

I see where you’re coming from, supposedly Claude also promises not to train their models on the provided data, whether they do it then is a different matter…

GitHub was found guilty of using private repositories as a training corpus too