The calculator didn’t eliminate math majors. Excel and accounting software didn’t eliminate accountants and CPAs. These are all just tools.
I spend very little of my overall time at work actually coding. It’s a nice treat when I get a day where that’s all I do.
From my limited work with Copilot so far, the user still needs to know what they’re doing. I have 0 faith a product owner, without a coding background, can use AI to release new products and updates while firing their whole dev team.
When I say most of my time isn’t spent coding, a lot of that time is spend trying to figure out what people want me to build. They don’t know. They might have a general idea, but don’t know details and can’t articulate any of it. If they can’t tell me, I’m not sure how they will tell an LLM. I ended up building what I assume they want, then we go from there. I also add a lot of stuff that they don’t think about or care about, but will be needed later so we can actually support it.
If you were to go in another direction, what would it be where AI wouldn’t be a threat? The first thing that comes to my mind is switching to a trade school and learning some skills that would be difficult for robots.
Accounting mechanization is a good example of how unpredictable it can be. Initially there were armies of "accountants" (what we now call bookkeepers), mostly doing basic tasks of collecting data and making it fit something useful.
When mechanization appeared, the profession split into bookkeeping and accounting. Bookkeeping became a job for women as it was more boring and could be paid lower salaries (we're in the 1800s here). Accountants became more sophisticated but lower numbers as a %. Together, both professions grew like crazy in total number though.
So if the same happens you could predict a split between software engineers and prompt engineers. With an explosion in prompt engineers paid much less than software engineers.
> the number of accountants/book-
keepers in the U.S. increased from circa 54,000 workers [U.S.
Census Office, 1872, p. 706] to more than 900,000 [U.S. Bureau
of the Census, 1933, Tables 3, 49].
> These studies [e.g., Coyle, 1929;
Baker, 1964; Rotella, 1981; Davies, 1982; Lowe, 1987; DeVault,
1990; Fine, 1990; Strom, 1992; Kwolek-Folland, 1994; Wootton
and Kemmerer, 1996] have traced the transformation of the of-
fice workforce (typists, secretaries, stenographers, bookkeepers)
from predominately a male occupation to one primarily staffed
by women, who were paid substantially lower wages than the
men they replaced.
Interesting. Another take on that split could be engineers split to upper class AI engineers and lower class AI prompt developers, aka ai builders vs ai appliers.
Alternatively, I’ve thought a bit about this previously and have a slight different hypothesis. Businesses are ran by “PM types”.the only reason that developers have jobs is because pm types need technical devs to build their vision. (Obviously I’m making broad strokes here as there are also plenty of founders that ARE the dev). Now, if ai makes technical building more open to the masses, I could foresee a scenario where devs and pms actually converge into a single job title that eats up the technical-leaning PMs and the “PM-y” devs. Devs will shift to be more PM-y or else be cut out of the job market because there is less need for non-ambitious code monkeys. The easier it becomes for the masses to build because of AI, the less opportunity there is for technical grunt work. If before it took a PM 30 minutes to get together the requirements for a small task that took the entry level dev 8 hours to do, then it made sense. Now if AI makes it so a technical PM could build the feature in an hour, maybe it just makes sense to have the PM do the implementation and cut out the code monkey. And if the PM is doing the implementation, even if using some mythical AI superpower, that’s still going to have companies selecting for more technical PM’s. In this scenario I think non-technical PMs and non-pm-y devs would find themselves either without jobs or at greatly reduced wages.
We’re already seeing that split, between “developer” and “engineer”. We have been for years.
But that’s normal, eg, we have different standards for a shed (yourself), house (carpenter and architect), and skyscraper (bonded firms and certified engineers).
I think it depends on the size of the company. The larger the larger the company, the more likely they are to split this stuff out. Though various titles may seem to bleed together. I have a software engineer title, while another guy on my team is a software architect… we effectively do the same job. Stepping back from a higher level view, as a general theme, those with an architect title are more likely to be responsible for an overall design, while the engineers may have some input and build things to support the design.
The quality of said designs can vary wildly. Some designs I get from other team I completely ignore, because they have no idea what they’re talking about. Just because someone has the title doesn’t mean they deserve it.
Agreed. The sweet spot is people who have product owner skills _and_ can code. They are quickly developing superpowers. The overhead of writing tickets, communicating with the team and so on is huge. If one person can do it all, efficiency skyrockets.
I guess it's always been true to some extent that single individuals are capable of amazing things. For example, the guy who's built https://www.photopea.com/. But they must be exceptional - this empowers more people to do things like that.
Or people who can be product owners and can prompt LLMs to code (because I know him, that's me!).
I'm awestruck by how good Claude and Cursor are. I've been building a semi-heavy-duty tech product, and I'm amazed by how much progress I've made in a week, using a NextJS stack, without knowing a lick of React in the first place (I know the concepts, but not the JS/NextJS vocab). All the code has been delivered with proper separation of concerns, clean architecture and modularization. Any time I get an error, I can reason with it to find the issue together. And if Claude is stuck (or I'm past my 5x usage lol), I just pair programme with ChatGPT instead.
Meanwhile Google just continues to serve me outdated shit from preCovid.
90% of the way is still good enough for me because I can manage to think up and get through the rest of the 10%. The problem for me was that the 90% looked so overwhelming earlier and that would shy me away from pursuing that project at all.
But excel eliminated need in multiple accountants. One accountant with excel replaced ten with paper.
Chatgpt already eliminated many entry-level jobs like writer or illustrator. Instead of hiring multiple teams of developers, there will be one team with few seniors and multiple AI coding tools.
Guess how depressing to the IT salaries it will be?
A whole lot of automation is limited not by what could be automated, but what one can automate within a given budget.
When I was coding in the 90s, I was in a team that replaced function calls into new and exciting interactions with other computers which, using a queuing system, would do the computation and return the answer back. We'd have a project of having someone serialize the C data structures that were used on both sides into something that would be compatible, and could be inspected in the middle.
Today we call all of that a web service, the serialization would take a minute to code, and be doable by anyone. My entire team would be out of work! And yet, today we have more people writing code than ever.
When one accountant can do the work of 10 accountants, the price of the task lowers, but a lot of people that before couldn't afford accounting now can. And the same 10 accountaings from before can just do more work, and get paid about the same.
As far as software, we are getting paid A LOT more than in the early 90s. We are just doing things that back then would be impossible to pay for, our just outright impossible to do due to lack of compute capacity.
The pay being larger, is caused (I think) by VC money and the illegality of non-compete contracts. If your competitor can do something you can't, hire someone away from the competitor to show you how to do it. Hence developers can demand more pay for retention, and more pay to move.
I don’t don’t doubt that it might depress salaries but that excel example is a good one in that suddenly every company could start to do basic financial analysis in a manner that only the largest ones could previously afford.
> the Jevons paradox occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.
The increased work capacity of an accountant means that nowadays even small businesses can do financial analysis that would not have scaled decades ago.
>GOLDSTEIN: When the software hit the market under the name VisiCalc, Sneider became the first registered owner, spreadsheet user number one. The program could do in seconds what it used to take a person an entire day to do. This of course, poses a certain risk if your job is doing those calculations. And in fact, lots of bookkeepers and accounting clerks were replaced by spreadsheet software. But the number of jobs for accountants? Surprisingly, that actually increased. Here's why - people started asking accountants like Sneider to do more.
> The calculator didn’t eliminate math majors. Excel and accounting software didn’t eliminate accountants and CPAs. These are all just tools.
This just feels extremely shortsighted. LLMs are just tools right now, but the goal of the entire industry is to make something more than a tool, an autonomous digital agent. There's no equivalent concept in other technology like calculators. It will happen or it will not, but we'll keep getting closer every month until we achieve it or hit a technical wall. And you simply cannot know for sure such a wall exists.
If we hit that point, it’s then a question of access, cost, learning curve, and vision of individual companies. Some things are technically possible, but done by very few companies.
I’ve seen the videos of Amazon warehouses, where the shelves move around to make popular items more accessible for those fetching stuff. This is possible today, but what percentage of companies do this? At what point is it with the investment for a growing company? For some companies it’s never worth it. Others don’t have the vision to see the light at the end of the tunnel.
A lot of things that we may think of as old or standard practice at this point would be game changing for some smaller companies outside of tech. I hear my friends and family talking about various things they have to do at their job. A day writing a few scripts could solve a significant amount of toil. But they can’t even conceptualize where to begin to change that, they aren’t even thinking about it. Release all the AI the world has to offer and they still won’t. I bet some freelance devs could make a good living bouncing from company to company pair programming with their AI to solve some pretty basic problems for small non-tech companies that would be game changes for them, while being rather trivial to do. Maybe partner with a sales guy to find the companies and sell them on the benefits.
You can't ignore the fact that literally studying coding at this point is so demoralizing and you don't need really to study much if you think about it. You only need to be able to read the code to understand if it generated correctly etc but when if you don't understand some framework you just ask it to explain it to you etc. Basically gives vibes of a skill not being used anymore that much by us programmers. But will shift in more prompting and verifying and testing
I completed the book Programming Principles and Practice using C++ (which I HIGHLY recommend to any beginner interested in software engineering) about year ago with GPT4 as a companion. I read the book throughly and did all the exercises, only asking questions to GPT4 when I was stuck. This took me about 900-1000 hours total. Although I achieved my goal of learning C++ to a basic novice level, I acquired another skill unintentionally: the ability to break down tasks effectively to LLMs and prompt in a fashion that is extremely modular. I've been able to create complex apps and programs in a variety of programming languages even though I really only know C++. It has been an eye-opening experience. Of course it isn't perfect, but it is mind blowing and quite disturbing.
I spend very little of my overall time at work actually coding. It’s a nice treat when I get a day where that’s all I do.
From my limited work with Copilot so far, the user still needs to know what they’re doing. I have 0 faith a product owner, without a coding background, can use AI to release new products and updates while firing their whole dev team.
When I say most of my time isn’t spent coding, a lot of that time is spend trying to figure out what people want me to build. They don’t know. They might have a general idea, but don’t know details and can’t articulate any of it. If they can’t tell me, I’m not sure how they will tell an LLM. I ended up building what I assume they want, then we go from there. I also add a lot of stuff that they don’t think about or care about, but will be needed later so we can actually support it.
If you were to go in another direction, what would it be where AI wouldn’t be a threat? The first thing that comes to my mind is switching to a trade school and learning some skills that would be difficult for robots.