I disagree. I believe engineers are generally smarter than accountants.

But are they well-versed in the things accountants specialize in? Is there a possibility that not every programmer can be a good accountant, or that accountants know things you're unaware of when you wrote that statement?

Even better, they're well versed in things that accountants aren't. When you're auditing trillions of dollars in spending, it helps to have software, data science and analytics experts that can use modern tools beyond COBOL written 62 years ago.

They can use data processing, detect anomalies better, leverage AI models, automate data extraction from analog records, ingest unstructured data like emails and memos, build complex financial dependency graphs, detect leaks, build custom scrapers, etc etc.

I'm sure there's at least one accountant in the loop, but you really want the team to consist mostly of data nerds.

What about GAAP/IFRS? How do you endow these software engineers with knowledge of common patterns of fraud or leaks so they can actually write the correct software to find them automatically? How do they identify material misstatements?

You also seem confused; COBOL might be used, but it isn't the only tool available to accountants working for the government. COBOL is a straw-man. What you're describing here—software engineers who presumably have training in accounting—already exists, and they work inside and out of the government. This is an existing career path.

You're speaking about this as though you know a better way to do something, but it's already happening, and has been for years. Accountants aren't writing 62 year old programming languages waiting to die in their chairs while the world continues to progress without them.

Accounting just about anywhere you find it is already accomplished by accountants, some of them technically trained, as well as data scientists and software engineers. It's an interdisciplinary collaboration in any serious organization.

As a person who works with data and has done both consulting and product building in Data Science and lack of domain knowledge is what makes or breaks the end result. Too often do technical people think they know better and then build mediocre solutions that don't get used.

If technical people were so good at these things, technical people would have a hell of a lot more successful startups for one thing.

Let me guess you are an engineer?

Accounting isn't about being smart.

An audit accountant can ask an engineer to implement whatever is needed to achieve a goal they understand. An engineer with no finance background will have no idea where to start or what questions they can ask an accountant.

Or they will have absolutely no idea about the context and for example reveal secret information while they think they're just looking at money https://www.huffpost.com/entry/elon-musk-doge-posts-classifi...

“Figures don’t lie, but liars can figure”.

You can easily get drowned by a see of numbers and get confused and gaslighted, unless you don’t make sure all data is available and computable.

Not sure how this release, which impressive by all means transformed into an attack on DOGE which is the exact approach startups are taking to disrupt an industry.

Because it's not their data.

How much disruption started with massive failures?

You don't start with a live system or did SpaceX put astronauts in therir first rockets?