But if the time it takes an engineer to build any one thing goes down, now there are a lot more things that are cost effective.
Consider niche use cases. Every company tends to have custom processes and workflows. Think about being an accountant at one company vs. another -- while a lot of the job is the same, there will always be parts that are significantly different. Those bespoke processes often involve manual labor because off-the-shelf accounting software cannot add custom features for every company.
But what if it could? What if an engineer working with AI could knock out customer-specific features 10x as fast as they could in the past. Now it actually makes sense to build those features, to improve the productivity of each company's accounting department.
It's hard to say if demand for engineers will go down or up. I'm not pretending to know for sure. But I can see a possibility that we actually have way more developers in coming years!
That's definitely an interesting area, but I think we'll actually see (maybe) individual employees solving some of these problems on their own without involving IT/the dev team.
We kind of see it already - a lot of these problem spaces are being solved with complex Excel workflows, crappy Access databases, etc. because the team needed their problem solved now, and resources couldn't be given to them.
Maybe AI is the answer to that so that instead of building a house of cards on Excel, these non-tech teams can have something a little more robust.
It's interesting you mentioned accounting, because that's the one department/area I see taking off and running with it the most. They are already the department that's effectively programming already with Excel workflows & DSLs in whatever ERP du jour.
So it doesn't necessarily open up more dev jobs, but maybe fulfills the old the mantra of "everyone will become a programmer." and we see more advanced computing become a commodity thanks to AI - much like everyone can click their way through an office suite with little experience or training, everyone will be able to use AI to automate large chunks of their job or departmental processes.
I agree, but in my book, those employees are now developers. And so by that definition, there will be a lot more developers.
Will we see more or fewer people whose primary job is software development? That's harder to answer. I do think we'll see a lot more consultant-type roles, with experienced software developers helping other people write their own personal automations.
LLMs don't change that. If a business does not have the budget for a software engineer, LLMs won't make up budget headroom for it either. What LLMs do is allow engineers to iterate faster, and work on more tasks. This means less jobs.
But what has happened instead is that we are now building much more buildings and much more complex ones than we ever would have even conceived of back then. The Three Gorges dam required the work of thousands or even tens of thousands of people when it was built, and it would have required the work of millions in the year 1000. But it didn't actually generate millions of jobs in the year 1000: it was in fact never even conceived of as a possibility, much less attempted.
Of course, the opposite can also happen. The number of carpenters has reduced to almost nothing, when it used to be a major profession, and there are many other professions that have entirely disappeared.
Nevertheless, I don't think they are trying to frame it that way, either. The point is that making software development easier can actually increase the demand of software engineers in some cases (where projects that were previously not considered due to budget constraints are now feasible).
Why? Inevitably, I changed positions / jobs / platforms, and all that effort was lost / inapplicable, and I had to relearn to use the stock settings anyway.
Now, I understand that some companies have different setups, but it might just make more sense to change the company's accounting procedures (if possible) to conform to most accounting software defaults, rather than invest heavily in modifying the setup, unless you're a huge conglomerate and can keep people on staff. Why? Because someone, somewhere will have to maintain those changes. Sure, you can then hire someone else to update those changes - but guess what? Most likely, unless they open-source their changes, no LLM will have seen those changes, and even if they are allowed to fine-tune on it, they'll have seen exactly ONE instance of these changes. Odds they'll get everything right, AND the person using the LLM will recognize when it doesn't go right? Oh right, they invested in hundreds of unit tests to ensure everything works as expected even with changes, and I'm the tooth fairy..
I don't actually think this is going to take the form of LLMs implementing custom patches to off-the-shelf software. I think instead it's going to look like LLMs writing code that uses APIs offered by off-the-shelf software to script specific workflows.
(Though I think it's true of engineering too. We all have our own weird team-specific processes for code reviews and CI and deployments which could probably use better automation.)
But even where lots of customization exists today (such as in engineering!), more is always possible. It's always just a question of whether the automation saves as much time as it took to build. If the automations can be built faster, then it makes sense to build more of them.
It took time as different firms adapted to adopt computer technologies in their various business needs and workflows. It's hard to precisely predict how labor roles will change with each revolutionary technology.
We assume quite a bit about the challenge when we say it’s getting feature out.
It’s sort of like saying we can sprint faster with these tools, when the race is a marathon.
Or a better example is Coke vs Pepsi.
How do LLMs impact long term project, firm, process viability ?
Will AI be able translate all that into rust?
