4 ms·

Seems like you're very confused about what this work typically entails. The job of these employees is not mental arithmatic. It's closer to: - Log in to the in

• Ntrails 1y ago
  Checking someone elses spreadsheet is a fucking nightmare. If your company has extremely good standards it's less miserable because at least the formatting etc will be consistent... The one thing LLMs should consistently do is ensure that formatting is correct. Which will help greatly in the checking process. But no, I generally don't trust them to do sensible things with basic formulation. Not a week ago GPT 5 got confused whether a plus or a minus was necessary in a basic question of "I'm 323 days old, when is my birthday?"
  • szundi 1y ago
    [dead]
  • xmprt 1y ago
    I think you have a misunderstanding of the types of things that LLMs are good at. Yes you're 100% right that they can't do math. Yet they're quite proficient at basic coding. Most Excel work is similar to basic coding so I think this is an area where they might actually be pretty well suited. My concern would be more with how to check the work (ie, make sure that the formulas are correct and no columns are missed) because Excel hides all that. Unlike code, there's no easy way to generate the diff of a spreadsheet or rely on Git history. But that's different from the concerns that you have.
    • collingreen 1y ago
      I've built spreadsheet diff tools on Google sheets multiple times. As the needs grows I think we will see diffs and commits and review tools reach customers
      • break_the_bank 1y ago
        hey Collin! I am working on an AI agent on Google Sheets, I am curious if any of your designs are out in the public. We are trying to re-think how diffs should look like and want to make something nicer than what we currently have, so curious.
        • collingreen 1y ago
          Hi! Nothing public nor generic enough to be a good building block. I found myself often frustrated by the tools that came out of the box but I believe better apis could make this slightly easier to solve. The UX of spreadsheet diffs is a hard one to solve because of how weird the calculation loops are and how complicated the relationship between fields might be. I've never tried to solve this for a real end user before in a generic way - all my past work here was for internal ability to audit changes and rollback catastrophes. I took a lot of shortcuts by knowing which cells are input data vs various steps of calculations -- maybe part of your ux is being able to define that on a sheet by sheet basis? Then you could show how different data (same formulas) changed outputs or how different formulas (same data) did differently? Spreadsheets are basically weird app platforms at this point so you might not be able to create a single experience that is both deep and generic. On the other hand maybe treating it as an app is the unlock? Get your AI to noodle on what the whole thing is for, then show diff between before and after stable states (after all calculation loops stabilize or are killed) side by side with actual diffs of actual formulas? I feel like Id want to see a diff as a live final spreadsheet and be able to click on changed cells and see up the chain of their calculations to the ancestors that were modified. Fun problem that sounds extremely complicated. Good luck distilling it!
    • alfalfasprout 1y ago
      proficient != near-flawless. > Most Excel work is similar to basic coding so I think this is an area where they might actually be pretty well suited. This is a hot take. One I'm not sure many would agree with.
  • runarberg 1y ago
    > The one thing LLMs should consistently do is ensure that formatting is correct. In JavaScript (and I assume most other programming languages) this is the job of static analysis tools (like eslint, prettier, typescript, etc.). I’m not aware of any LLM based tools which performs static analysis with as good a results as the traditional tools. Is static analysis not a thing in the spreadsheet world? Are there the tools which do static analysis on spreadsheets subpar, or offer some disadvantage not seen in other programming languages? And if so, are LLMs any better?
    • eric-burel 1y ago
      Just use a normal static analysis tool and shove the result to an LLM. I believe Anthropic properly figured that agents are the key, in addition to models, contrary to OpenAI that is run by a psycho that only believes in training the bigger model.
  • koliber 1y ago
    Maybe LLMs will enable a new type of work in spreadsheets. Just like in coding we have PR reviews, with an LLM it should be possible to do a spreadsheet review. Ask the LLM to try to understand the intent and point out places where the spreadsheet deviates from the intent. Also ask the LLM to narrate the spreadsheet so it can be understood.
    • Insanity 1y ago
      That first condition "try to understand the intent" is where it could go wrong. Maybe it thinks the spreadsheet aligns with the intent, but it misunderstood the intent. LLMs are a lossy validation, and while they work sometimes, when they fail they usually do so 'silently'.
      • monkeydust 1y ago
        Maybe we need some kind of method, framework to develop intent. Most of things that go wrong in knowledge working are down to lack of common understanding of intent.
• lossolo 1y ago
  Last time, I gave claude an invoice and asked it to change one item on it, it did so nicely and gave me the new invoice. Good thing I noticed it had also changed the bank account number.. The more complicated the spreadsheet and the more dependencies it has, the greater the room for error. These are probabilistic machines. You can use them, I use them all the time for different things, but you need to treat them like employees you can't even trust to copy a bank account number correctly.
  • mikeyouse 1y ago
    We’ve tried to gently use them to automate some of our report generation and PDF->Invoice workflows and it’s a nightmare of silent changes and absence of logic.. basic things like specifically telling it “debits need to match credits” and “balance sheets need to balance” that are ignored.
  • wholinator2 1y ago
    Yeah, asking llm to edit one specific thing in a large or complex document/ codebase is like those repeated "give me the exact same image" gifs. It's fundamentally a statistical model so the only thing we can be _certain_ of is that _it's not_. It might get the desired change 100% correct but it's only gonna get the entire document 99 5%
  • onion2k 1y ago
    Something that Claude Sonnet does when you use it to code is write scripts to test whether or not something is working. If it does that for Excel (e.g. some form of verification) it should be fine. Besides, using AI is an exercise in a "trust but verify" approach to getting work done. If you asked a junior to do the task you'd check their output. Same goes for AI.
• dpoloncsak 1y ago
  Sysadmin of a small company. I get asked pretty often to help with a pivot table, vlookup, or just general excel functions (and smartsheet, these users LOVE smartsheet)
  • toomuchtodo 1y ago
    Indeed, in a small enough org, the sysadmin/technologist becomes support of last resort for all the things.
  • JumpCrisscross 1y ago
    > these users LOVE smartsheet I hate smartsheet… Excel or R. (Or more often, regex followed by pen and paper followed by more regex.)
    • dpoloncsak 1y ago
      They're coming to me for pivot tables.... Handing them regex would be like giving a monkey a bazooka
• AvAn12 1y ago
  > “Does it have to be perfect?” Actually, yes. This kind of management reporting is either (1) going to end up in the books and records of the company - big trouble if things have to be restated in the future or (2) support important decisions by leadership — who will be very much less than happy if analysis turns out to have been wrong. A lot of what ties up the time of business analysts is ticking and tying everything to ensure that mistakes are not made and that analytics and interpretations are consistent from one period to the next. The math and queries are simple - the details and correctness are hard.
  • 2b3a51 1y ago
    There is another aspect to this kind of activity. Sometimes there can be an advantage in leading or lagging some aspects of internal accounting data for a time period. Basically sitting on credits or debits to some accounts for a period of weeks. The tacit knowledge to know when to sit on a transaction and when to action it is generally not written down in formal terms. I'm not sure how these shenanigans will translate into an ai driven system.
    • AvAn12 1y ago
      That’s the kind of thing that can get a company into a lot of trouble with its auditors and shareholders. Not that I am offering accounting advice of course. And yeah, one can not “blame” and ai system or try to ai-wash any dodgy practices.
    • iamacyborg 1y ago
      > Sometimes there can be an advantage in leading or lagging some aspects of internal accounting data for a time period. This worked famously well for Enron.
  • extr 1y ago
    Speak for yourself and your own use cases. There are a huge diversity of workflows with which to apply automation in any medium to large business. They all have differing needs. Many excel workflows I'm personally familiar with already incoporate a "human review" step. Telling a business leader that they can now jump straight to that step, even if it requires 2x human review, with AI doing all of the most tediuous and low-stakes prework, is a clear win.
• next_xibalba 1y ago
  The use cases for spreadsheets are much more diverse than that. In my experience, spreadsheets just as often used for calculation. Many of them do require high accuracy, rely on determinism, and necessitate the understanding of maths ranging from basic arithmetic to statistics and engineering formulas. Financial models, for example, must be built up from ground truth and need to always use the right formulas with the right inputs to generate meaningful outputs. I have personally worked with spreadsheet based financial models that use 100k+ rows x dozens of columns and involve 1000s of formulas that transform those data into the desired outputs. There was very little tolerance for mistakes. That said, humans, working in these use cases, make mistakes >0% of the time. The question I often have with the incorporation of AI into human workflows is, will we eventually come to accept a certain level of error from them in the way we do for humans?
• jay_kyburz 1y ago
  >Does it have to be perfect? Also no. Yeah, but it could be perfect, why are there humans in the loop at all? That is all just math!