We came up with what I still consider a pretty cool batch-rpc mechanism under the hood so that you wouldn't have to cross the process boundary on every OM calls (which is especially costly on Excel Web). I remember fighting so hard to have it be called `context.sync()` instead of `context.executeAsync()`...
That being said, done poorly it can be slow as the round-trip time on web can be on the order of seconds (at least back then).
I recently tried Claude Cowork for PowerPoint and I was stunned by the content as well as design quality of the deck it produced. That's a threat for Microsoft because now you don't need the editing tools of PowerPoint, AI replaces it, so all you need is the presentation mode of PowerPoint.
Copilot for Excel is useless. Ask it what is in cell A1 and it can't answer. I am looking forward to trying ChatGPT for Excel.
Nowadays I just make single-purpose websites with Claude Code because Google Sheets has such poor AI integration and is outrageously tedious to edit.
They had all the parts and I have a subscription and it still does terrible things like prompt me to use pandas after exporting as a CSV. It will mention some cell and then can’t read it. It can’t edit tables so they just get overwritten with other tables it generates.
It reminds me of something a friend told me: he heard that Google employees do dogfood their products; some even multiple times every year. There’s no way anyone internal uses Sheets even that often.
This seems like a security nightmare, which is especially relevant because sensitive data is often stored in Excel files.
Damn that OAI valuation is like a sore boil that is about to explode.
Also once again, a lack of imagination from OAI. Damn vision really is super scarce huh.
Instead of answering with 6, it came up with 15. The comment was "If AI is doing this, a global financial crash is inevitable."
Might not be real but it is something to keep an eye on. Hopefully, they are a bit more cautious on how this is implemented.
> (…) you can verify each step and revert edits if needed.
I wish there were different workflows.
It feels like current most popular way of working with GenAI requires the operator to perform significant QA. The net time savings are usually positive. But it still feels inefficient, risky and frustrating, especially with more complex and/or niche problem areas.
Are there GenAI products that focus more on skill enhancement than replacement? Or any other workflows that improve reliability?
Just this past week I used it to generate a simple model of a few different scenarios related to an investment property I own.
The first problem I ran into is that it was unable to output a downloadable XLS file. Not a huge deal - it suggested generating CSV tables I could copy/paste into a spreadsheet. The outputs it gave me included commas in a handful of numbers over 1,000 (but not all of them!) which of course shifted cells around when brought into Google Sheets. We pivoted our approach to TSV and solved this problem. Big deal? No. Seemingly basic oversight? Absolutely.
This is where the real fun began. Once I started to scrutinize and understand the model it built, I found incorrect references buried all over the place, some of which would have been extremely hard to spot. Here's my actual exchange with ChatGPT:
- - - - - - - - - -
> Can you check the reference in cell F3? It looks like it's calling back to the wrong cell on the inputs tab. Are there similarly incorrect references elsewhere?
> Yes, F3 is incorrect, and there are multiple other incorrect references elsewhere: (It listed about 30 bulleted incorrect references)
Bottom line - - Many formulas point to the wrong Inputs row because of the blank lines - The Sell + Condo section also has a structural design problem, not just bad references.
The cleanest fix is for me to regenerate the entire AnnualModel TSV with: - all references corrected - all 15 years included - the condo scenario modeled properly with a separate housing asset column
- - - - - - - - - -
This was me asking about the exact output I had just received (not something I had made any changes to or reworked.)
There are plenty of domains where I have enough faith and error tolerance to use ChatGPT all day, but this just sends a chill down my spine. How many users are really going to proof every single formula? And if I need to scrutinize to that level of detail, what's the point in the first place?
Show HN: I've built a C# IDE, Runtime, and AppStore inside Excel
670 points | 179 comments
One of the main use cases was to analyze Excel data with SQL. I'm the kind of nerd that loves stuff like that, but stuff like that seems completely obsolete now.
Tune in for the next episode: Word
Building an agent that can securely access systems of records, external data sources, and other files in your workspace—with context for the work you do outside of Excel—is where the revolution is at.
[for] ... users outside the EU.
hmmMicrosoft, being Microsoft, will find a way to win no matter who that vendor ends up being.
So, yes but no. Not that I care, but the answer to the above question is a no, and should start with No.
There are now just even more errors than there already were.
Now there's hope though: I take it at some point, just like we have AI that can already find (and fix and sometimes even properly fix) errors in code, we may end up with AI tools able to find all the broken assumptions and errors / wrong formulas the spreadsheets that make the corporate world are full of. But atm that's not where we are.
One such corporate-world company producing a gigantic turd would the "biggest" (but it's really not that big) european software company, SAP... They're going full on "business AI" as they see (rightly so?) AI as a terminal death threat to their revenue model. Market cap went from $360 bn to $200 bn: don't know if it's related to their "genius" AI-move.
And so now we have countless corporate drones who were already incapable of doing any kind of financial/accounting/math computation in a rigorous way who are now double-speeding on the errors, but this time AI-augmented.
It's the "let's add an AI chatbot to our site" (which so many companies are adding to their websites right now), but corporate version: "let's add AI to our corporate tools".
Just to be clear: I think this cannot fail. Failure and bogus numbers are the norm in spreadsheets, not the exception. More failure, more bogus computations, actually won't change a thing.
They (OAI+Anthropic) very much do not get exactly what these people are doing in the job (accounting+corporate finance+valuation+asset management) and what the actual production process is. These tools are irrelevant, disrupt flow and if anything just add noise to what one is doing.