The "upside" description:

  On the other you have a non-technical executive who's got his head round Claude Code and can run e.g. Python locally.

  I helped one recently almost one-shot converting a 30 sheet mind numbingly complicated Excel financial model to Python with Claude Code.

  Once the model is in Python, you effectively have a data science team in your pocket with Claude Code. You can easily run Monte Carlo simulations, pull external data sources as inputs, build web dashboards and have Claude Code work with you to really integrate weaknesses in your model (or business). It's a pretty magical experience watching someone realise they have so much power at their fingertips, without having to grind away for hours/days in Excel.

I've a reasonably intense math background corrupted by application to geophysics and implementing real world numerical applications.

To be fair, this statement alone:

* 30 sheet mind numbingly complicated Excel financial model

makes my skin crawl and invokes a flight reflex.

Still, I'll concede that a Claude Code conversion to Python of a 30 sheet Excel financial model is unlikely to be significantly worse than the original.

One of the dirty secrets of a lot of these "code adjacent" areas is that they have very little testing.

If a data science team modeled something incorrectly in their simulation, who's gonna catch it? Usually nobody. At least not until it's too late. Will you say "this doesn't look plausible" about the output? Or maybe you'll be too worried about getting chided for "not being data driven" enough.

If an exec tells an intern or temp to vibecode that thing instead, then you definitely won't have any checkpoints in the process to make sure the human-language prompt describing process was properly turned into the right simulation. But unlike in coding, you don't have a user-facing product that someone can click around in, or send requests to, and verify. Is there a test suite for the giant excel doc? I'm assuming no, maybe I'm wrong.

It feels like it's going to be very hard for anyone working in areas with less black-and-white verifiability or correctness like that sort of financial modeling.

I'm almost certain it will be significantly worse.

The Excel sheet will have been tuned over the years by people who knew exactly what it was doing and fixed countless bugs along the way.

The Claude Code copy will be a simulacrum that may behave the same way with some inputs, but is likely to get many of edge cases wrong, and, when you're talking about 30 sheets of Excel, there will be many, many of these sharp edges.

we're going from "bad excel sheet caused recession" to "bad vibe-coded financial thing caused recession"

The thing is, when you use AI, you're not really doing things, you're having things done. AI isn't a tool, it's a service.

Now, back in the day, IBM designed and built an "executive data terminal". It wasn't really a computer terminal in the sense that you and I understand it. Rather, it was a video and two-way-audio feed to a room with a team of underlings, which an executive could ask for business data and analyses, which could be called up on a computer display (also routed to the executive's office). This allowed the executive to ask questions so he (it was the 1960s, it was almost invariably a he) could make informed decisions, and the team of underlings to call up data or crunch numbers on the computer and show the results on the display.

So because executives are used to having things done for them, I can totally see AI being used by executives to replace the "team of underlings" in this setup—in principle. The fact is that were I in that CEO's chair, I'd be thinking twice before trusting anything an LLM tells me, and double-checking those results—perhaps with my team of underlings.

Discussed on Hackernews: https://news.ycombinator.com/item?id=42405462 IEEE article: https://spectrum.ieee.org/ibm-demo

Obligatory xkcd: https://xkcd.com/1667/