The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion.

Other white collar business/bullshit job (ala Graeber) work is meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate those thoughts, thinking about market positioning, etc.

Maybe tools like Cowork can help to find files, identify tickets, pull in information, write Excel formulas, etc.

What’s different about coding is no one actually cares about code as output from a business standpoint. The code is the end destination for decided business processes. I think, for that reason, that code is uniquely well adapted to LLM takeover.

But I’m not so sure about other white-collar jobs. If anything, AI tooling just makes everyone move faster. But an LLM automating a new feature release and drafting a press release and hopping on a sales call to sell the product is (IMO) further off than turning a detailed prompt into a fully functional codebase autonomously.

I’m confused what kind of software engineer jobs there are that don’t involve meeting with people, “aligning expectations”, getting consensus, making slides/decks to communicate that, thinking about market positioning, etc?

If you weren’t doing much of that before, I struggled to think of how you were doing much engineering at all, save some more niche extremely technical roles where many of those questions were already answered, but even still, I should expect you’re having those kinds of discussions, just more efficiently and with other engineers.

> making slides/decks to communicate those thoughts,

That use case is definitely delegated to LLMs by many people. That said, I don't think it translates into linear productivity gains. Most white collar work isn't so fast-paced that if you save an hour making slides, you're going to reap some big productivity benefit. What are you going to do, make five more decks about the same thing? Respond to every email twice? Or just pat yourself on the back and browse Reddit for a while?

It doesn't help that these LLM-generated slides probably contain inaccuracies or other weirdness that someone else will need to fix down the line, so your gains are another person's loss.

Thinking is always the hardest part and the bottleneck for me.

It doesn’t capture everyone’s experience when you say thinking is the smaller part of programming.

I don’t even believe a regular person is capable of producing good quality code without thinking 2x the amount they are coding

> The thing with a lot of white collar work is that the thinking/talking is often the majority of the work… unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed.

WHOAH WHOAH WHOAH WHOAH STOP. No coder I've ever met has thought that thinking was anything other than the BIGGEST allocation of time when coding. Nobody is putting their typing words-per-minute on their resume because typing has never been the problem.

I'm absolutely baffled that you think the job that requires some of the most thinking, by far, is somehow less cognitively intense than sending emails and making slide decks.

I honestly think a project managers job is actually a lot easier to automate, if you're going to go there (not that I'm hoping for anyone's job to be automated away). It's a lot easier for an engineer to learn the industry and business than it is for a project manager to learn how to keep their vibe code from spilling private keys all over the internet.

> unlike coding, where thinking is (or, used to be, pre-agent) a smaller percentage of the time consumed. Writing the software, which is essentially working through how to implement the thought, used to take a much larger percentage of the overall time consumed from thought to completion.

huh? maybe im in the minority, but the thinking:coding has always been 80:20 spend a ton of time thinking and drawing, then write once and debug a bit, and it works

this hasnt really changed with Llm coding either, except that for the same amount of thinking, you get more code output

when the work involves navigating a bunch of rules with very ambiguous syntax, AI will automate them to the point computers automated rules based systems with very precise syntax in the 1990s

https://hazel.ai/tax-planning

this software (which i am not related to or promoting) is better at investment planning and tax planning than over 90% of RIAs in the US. It will automate RIA to the point that trading software automated stock broking. This will reduce the average RIA fee from 1% per year to 0.20% or even 0.10% per year just like mutual fund fees dropped in the early 00s