The problem with using markdown for this is that it's unstructured, so when the LLM does calculations on it, extracting data is error prone, you're never sure what exactly gets extracted, and it's then a hassle to verify (like the author had to do).
In my app Superego (https://github.com/superegodev/superego, shameless plug) I use structured JSON documents precisely for this reason, because with a well-defined schema the LLM can write TypeScript functions that must compile. This doesn't guarantee correctness, of course, but it actually goes a long way.
But doing my taxes was a use case I hadn't considered, and it's actually pretty neat! I'll be trying it myself next month (though I'm not looking forward to it).
> I use structured JSON documents precisely for this reason, because with a well-defined schema the LLM can write TypeScript functions that must compile.
The intention of this is to reduce hallucination on information extraction, right?
Also, how do you convert your docs / information into JSON documents?
> The intention of this is to reduce hallucination on information extraction, right?
Correct.
> Also, how do you convert your docs / information into JSON documents?
Right now you have to add it yourself to the database. The idea is that you use Superego as the software in which you record your expenses / income / whatever, so the data is naturally there already.
But I'm also working on an "import from csv/json/etc" feature, where you drop in a file and the AI maps the info it contains to the collections you have in the database.
I bought a copy of Office this year to do my taxes with the excel1040.com template and Claude for Excel, and dropped my 1099s and stuff into the chat window and Claude just transferred the numbers to the correct cells and Excel did the calculations. It was super easy (also easy to check because my tax picture didn’t change much from last year). It got some things right that TurboTax always got wrong (like cost basis for ESPPs). The only part that was difficult was getting Claude to transfer the data to the IRS fillable PDFs - I probably spent longer iterating on that than it would have taken to copy-paste the data from Excel. Other than that, it worked great, highly recommend.
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In my app Superego (https://github.com/superegodev/superego, shameless plug) I use structured JSON documents precisely for this reason, because with a well-defined schema the LLM can write TypeScript functions that must compile. This doesn't guarantee correctness, of course, but it actually goes a long way.
But doing my taxes was a use case I hadn't considered, and it's actually pretty neat! I'll be trying it myself next month (though I'm not looking forward to it).
> I use structured JSON documents precisely for this reason, because with a well-defined schema the LLM can write TypeScript functions that must compile.
The intention of this is to reduce hallucination on information extraction, right?
Also, how do you convert your docs / information into JSON documents?
> The intention of this is to reduce hallucination on information extraction, right?
Correct.
> Also, how do you convert your docs / information into JSON documents?
Right now you have to add it yourself to the database. The idea is that you use Superego as the software in which you record your expenses / income / whatever, so the data is naturally there already.
But I'm also working on an "import from csv/json/etc" feature, where you drop in a file and the AI maps the info it contains to the collections you have in the database.