Hacker News Reader

Comment by saidnooneever | Hacker News Reader

its a classical effect of having a hammer and recognising everything as a nail to whack. its pretty tricky to find a problem well suited to a tool like LLMs.

i programming stuff using LLM of which the resultant programs are deterministic and dont use LLMs or tokens is a better or easier approach to having gains. because the resulting program can be easier to use and doesnt cost a lot to run. Automations are a good target, or integratig libraries into other programs. tedious things u know well how to do but take time to do manually. then once done fix a problem or workflow that u need fixed by the solution yielded.

ive not seen 1 app that does calls to an LLM that i find useful, apart from harnesses that produce code (which is only recently becoming more appealing and might depend on how good and fast u can write code, at which im not the best nor the fastest.)

View on HN

My wife has to submit a bunch of translated documents for procurement processes. Noone really reads those but they are a hard requirement. These are usually in DOCX or sometimes PDF with tables, product images etc. So I built her a little applet which (after clicking two buttons) sends the XML or PDF to an LLM in chunks and it spits back the same structure but with translated text. Of course there are edge cases where it doesn’t work perfectly but I’d say it works 95% of the time in a good enough quality to submit them. Saves her roughly 0.5-1 hour per job and much cheaper than other alternatives.

I’m doing something similar at work. Thousands of contracts, need to extract billing terms/logic. It’s scattered throughout each contract but has no summary, each contract can be hundreds of pages of non applicable legalese. The problem is, once I run it, can I trust the output without manual verification? How will I know if it skipped/missed something from a contract?

I would build a review dashboard that shows you the extracted data on one side and the visual snippet of the contract on the other. Quick to double check, and you still save time over opening the contract and searching for the right section and extracting it by hand or via OCR.

We have done something similar where it highlights the terms, basically each extracted term is linked to a specific highlight in the contract, and has them side by side like you said and you can jump around the contract by clicking on the extracted term. This helps when the agent needs HITL clarification on a term, as it gets you there quick and you can tell it more information to aid interpretation. But, if it missing something completely, I’d never know without reading the whole contract and validating every term I found the agent noticed. We’ve done some training sets and it does help and get better but the large variation of contracts means there’s little standardization.

I think we’re on path to just do random full review audits of maybe 10% to get a baseline confidence level and then just note it as a risk. Still a large manual task, we’ll probably outsource it.

Recently laid off and not a big AI guy… but to illustrate your points:

Tailoring + proofing resumes to _manually_ apply to jobs is a great application of LLMs in my experience. But I wouldn’t want an AI to apply for jobs for me.

Funny thing about that. This time last year I was applying for jobs and kept my same old latex generated flawed human resume that I’ve been using 20 years or so.

Recruiters said it was standing out in the tech sector. Apparently AI likes to embellish way too much so you don’t trust it.

> But I wouldn’t want an AI to apply for jobs for me.

why? they’re using ai for most of the hiring process. it’s only fair for us to do it too.

Not that you're wrong, but it creates a race to the bottom. More and more people with use AI to apply because more and more people used AI to apply.

Reply on news.ycombinator.com