Comment by kentonv
8 days ago
I think there's a huge huge space of software to build that isn't being touched today because it's not cost-effective to have an engineer build them.
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!
> I think there's a huge huge space of software to build that isn't being touched today because it's not cost-effective to have an engineer build them.
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.
If we shiver at the sight of some of those accounting-created excels, which we only learn about when they fail and they can't understand them anymore, wait for them to hand over a vibe-coded 200k loc Python codebase "which is not working anymore" and nobody had ever reviewed a single line of code.
> I think we'll actually see (maybe) individual employees solving some of these problems on their own without involving IT/the dev team.
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.
> I think there's a huge huge space of software to build that isn't being touched today because it's not cost-effective to have an engineer build them.
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.
If a business has the budget for 1 or 2 engineers though, they might be able to task them with work that previously required 5-10 engineers (in theory, anyways).
Right, but even the way you opted to frame this discussion is based on the idea that there is a drop in demand for software engineers. You need less engineers, not more. A few can get more done, but you need fewer to accomplish your tasks too.
6 replies →
After 30+ years in the software field, and a user for 40+, having at times heavily customized my desktop or editor, for example - I've concluded that the best thing for most apps is for me to learn to use them with stock settings.
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..
This just isn't true and will probably never be true. Using all the defaults is... probably optimal in the general sense and when things come to scale, but most companies (or just leadership) at some point want to leave the "standards" with custom design or additions. Also, any company providing payroll/accounting/ software has an inherent interest in going against standardization and providing features to promote lock-in.
There are good arguments to just conform. But it is in fact true nevertheless that many companies and teams continue to choose bespoke workflows over standardized ones. So I guess there must be something driving that.
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.
This is precisely why I compare this technological revolution with the electronic spreadsheet. Before the electronic spreadsheet, what used to take several accountants several days to "compute a whole spreadsheet" after changing "a few inputs" is serviced by a single accountant in a few minutes. That kind of service that was only available to enormous firms with teams of dozens of accountants is now available to firms with a technically proficient employee who do that kind of accounting as only a small part of their role.
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.
It's interesting that you bring up accounting software as an example. In jurisdictions where legal requirements around it are a lot more specific than in e.g. US, accounting suites usually already come with a lot of customization hooks (up to and including full-fledged scripting DSLs), and there are software engineers and companies who specialize in using those to implement bespoke accounting requirements.
I admit I have no specific knowledge of accounting and just meant to reference any random department that isn't engineering.
(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.
I work for SMEs as a consulting CTO, and this is exactly where I see things going in this domain. I can take care of workloads that would've been prohibitively expensive in the past. In the case of SMEs, this may cover critical problems whose resolution can unlock new levels of growth. LLMs can be an absolute boon for them, and I'm fairly optimistic about being able to capitalize on the opportunity.
Which solves the now problem for the tomorrow problem.
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 ?
Banking allegedly runs on ancient cobalt cathedrals and mystical runes.
Will AI be able translate all that into rust?