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.

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.

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.

(I pulled the quote by using yt-dlp to grab the MP4 and then running that through MacWhisper to generate a transcript.)

“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.

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.

When tools break, people stop using them before they sink the ship down. If AI is that terrible at spreadsheet, people will just revert to Brenda.

And it's not like spreadsheets have no errors right now.

You can save time still, but perhaps not as much as you think, because you need to check the ai's work thoroughly.

Coding agents are useful and good and real products because when they screw up, things stop working almost always before they can do damage. Coding agents are flawed in ways that existing tools are good at catching, never mind the more obvious build and runtime errors.

Letting AI write your emails and create your P&L and cash flow projections doesn't have to run the gauntlet of tools that were created to stop flawed humans from creating bad code.

Other than that, it is pretty horrible for coding.

Over the past couple of months, I’ve tried some smaller models on duck.ai and also ChatGPT directly to create some columns and formulas for a specific purpose. I found that ChatGPT is a lot better than the “mini” models on duck.ai. But in all these cases, though these platforms seemed more capable than me and could make attempts to explain their formulas, they were many a times creating junk and “looping” back with formulas that didn’t really work. I had to point out the result (blank or some #REF or other error) multiple times and they would acknowledge that there’s an issue and provide a working formula. That wouldn’t work either!

I really love that these LLMs can sort of “understand” what I’m asking, break it down in English, and provide answers. But the end result has been an exercise in frustration and waste of time.

Initially I really thought and believed that LLMs could make Excel more approachable and easier to use — like you tell it what you want and it’ll figure it out and give the magic incantations (formulas). Now I don’t think we’re anywhere close to that if ChatGPT (which I presume powers Copilot as well) struggles and hallucinates so much. I personally don’t have much hope with the (comparatively) smaller and older models.

Brendas actually aren’t totally perfect so the tools between Brendas need to deterministically store and show their work so they can reliably check each other. If the tool itself has a Brenda baked into it—even if it’s a very good Brenda simulation!—it seems like a company could run the risk of losing that deterministic basis for double-checking. And therefore lose track of their accounting reality.

Some people will for sure over-trust the AI in the spreadsheet and make some dumb mistakes. Let’s all remember though that dumb mistakes in business are not illegal, and the whole point of a private market is to enable “natural consequences” for businesses that make them. Some people will need to touch the hot stove of AI to understand how it could hurt them. I’m not sure there is any way to stop that, or even if we should.

But never during work hours. The woman's a saint M-F.

Brenda"

I don't know about that. There could be lots of interesting ways Brenda can (be convinced to) hallucinate.

https://support.microsoft.com/en-gb/office/get-started-with-...

The CEO has been itching to fire this person and nuke her department forever. She hasn't gotten the hint with the low pay or long hours, but now Copilot creates exactly the opening the CEO has been looking for.

AI may be able to spit out ann excel sheet or formula - But if it can’t be verified, so what ?

And here’s my analogy to think about the debugging of an excel sheet - you can debug most corporate excel sheets with a calculator.

But when AI is spitting out excel sheets - when the program is making smaller programs - what is the calculator in this analogy ?

Are we going to be using excel sheets to debug the output of AI?

I think this is the inherent limiter to the uptake of AI.

There’s only so much intellectual / experiential / training depth present.

And now we’re going to be training even fewer people.

At the end of the day I /customers need something to work.

But failing that - I will settle for someone to blame.

Brenda handles a lot of blame. Is OpenAI going to step into that gap ?

I suppose the person that wrote that have not ideia Excel is just an app builder where you embed data together with code.

You know that we have excel because computers didn’t understand column names in databases and so data extraction needed to be made by humans. Humans then design those little apps in excel to massage the data.

Well, now an agent can read the boss saying gimme the sales from last month and the agent don’t need excel for that, because it can query the database itself, massage the data itself using python and present the data itself with html or PNGs.

So, we are in the process of automating Brenda AND excel away.

Also, finance departments are a very small part of excel users. Just think everywhere were people need small programs, excel is there.

I'm not saying that this can't happen and it's not bad. Take a look at nudge theory - the UK government created an entire department and spent enormous amounts of time and money on what they thought was a free lunch - that they could just "nudge" people into doing the things they wanted. So rather than actually solving difficult problems the uk government embarked on decades of pseudo-intellectual self agrandizement. The entire basis of that decades long debacle was based on bullshit data and fake studies. We didn't need AI to fuck it up, we managed it perfectly well by ourselves.

e.g. MS Access is well on its way. as soon as x86 gets fully overtaken by ARM, and LLMs overtake "compilers" (also taken enterprise only).. then things like sqlite-browsers (FOSS "access") will be an arcane tool of binary incompatible ("obsolete") formats

(edits: this worry has not been easy to type out)

Financial statements are correct because of auditors who check the numbers.

If you have a good audit process then errors get detected even if AI helped introduce them. If you aren't doing a good audit then I suspect nobody cares whether your financial statement is correct (anyone who did would insist on an audit).

its like the xlookup situation all over again, yet another move aimed at the casual audience, designed to bring in the party gamers and make the program an absolute mess competitively