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- Hacker News
- Many fears of “AI mucking it up” could be mitigated with an ability to connect a workbook to a git repository. Not for data, but for VBA, cell formulas, and cell metadata. When you can encapsulate the changes a contributor (in this case co-pilot) makes into a commit, you can more easily understand what changes it/they made.
- Brenda has been getting slower over the years -as we all have-, but soon the boss will learn that it was a small price to pay for knowing well how to keep such house of cards from collapsing.
- That mirrors my experience as well. LLMs get instantly confused in real world scenarios in Excel and confidently hallucinate millions in errors
If you look at the demos for these it’s always something that is clean and abundantly available in training data. Like an income statement. Or a textbook example DCF. Or my personal fav „here is some data show me insights“. Real world excel use looks nothing like that.
I’m getting some utility out of them for some corporate tasks but zilch in excel space.
by Havoc - Hmmm the Brendas I know look a little different.
“There are two Brendas - their job is to make spreadsheets in the Finance department. Well, not quite - they add the months and categories to empty spreadsheets, then they ask the other departments to fill in their sales numbers every month so it can be presented to management.
“The two Brendas don’t seem to talk, otherwise they would realize that they’re both asking everyone for the same information, twice. And they’re so focused on their little spreadsheet worlds that neither sees enough of the bigger picture to say, ‘Wait… couldn’t we just automate this so we don’t need to do this song and dance every month? Then we wouldn’t need two people in different parts of the company compiling the same data manually.’
“But that’s not what Brenda was hired for. She’s a spreadsheet person, not a process fixer. She just makes the spreadsheets.”
We need fewer Brendas, and more people who can automate away the need for them.
by Esophagus4 - This quote is pulled from a TikTok, I recommend watching the whole thing here: https://www.tiktok.com/@belligerentbarbies/video/75683800086...
(I pulled the quote by using yt-dlp to grab the MP4 and then running that through MacWhisper to generate a transcript.)
by simonw - This reminds me of a friend whose company ran a daily perl script that committed every financial transaction of the day to a database. Without the script, the company could literally make no money irrespectively of sales because this database was one piece in a complex system for payment processor interoperability.
The script ran in a machine located at the corner of a cubicle and only one employee had the admin password. Nobody but a handful of people knew of the machine's existence, certainly not anyone in middle management and above. The script could only be updated by an admin.
Copilot may be good, but sure as hell doesn't know that admin password.
by glimshe - Co-pilot and AI has been shoved at the Microsoft Stack in my org for months. Most of the features were disabled or hopelessly bad. It’s cheaper for Microsoft to push this junk and claim they’re doing something, it’s going to improve their stock far more than not doing it, even though it’s basically useless currently.
Another issue is that my org disallows AI transcription bots. It’s a legit security risk if you have some random process recording confidential info because the person was too busy to attend the meeting and take notes themselves. Or possibly they just shirk off the meetings and have AI sit in.
by Dumblydorr - I find the contrast between two narratives around technology use so fascinating:
1. We advocate automation because people like Brenda are error-prone and machines are perfect.
2. We disavow AI because people like Brenda are perfect and the machine is error-prone.
These aren't contradictions because we only advocate for automation in limited contexts: when the task is understandable, the execution is reliable, the process is observable, and the endeavour tedious. The complexity of the task isn't a factor - it's complex to generate correct machine code, but we trust compilers to do it all the time.
In a nutshell, we seem to be fine with automation if we can have a mental model of what it does and how it does it in a way that saves humans effort.
So, then - why don't people embrace AI with thinking mode as an acceptable form of automation? Can't the C-suite in this case follow its thought process and step in when it messes up?
I think people still find AI repugnant in that case. There's still a sense of "I don't know why you did this and it scares me", despite the debuggability, and it comes from the autonomy without guardrails. People want to be able to stop bad things before they happen, but with AI you often only seem to do so after the fact.
Narrow AI, AI with guardrails, AI with multiple safety redundancies - these don't elicit the same reaction. They seem to be valid, acceptable forms of automation. Perhaps that's what the ecosystem will eventually tend to, hopefully.