You can hardly get online these days without hearing some AI booster talk about how AI coding is going to replace human programmers. AI code is absolutely up to production quality! Also, you’re all…
As a dumb question from someone who doesn’t code, what if closed source organizations have different needs than open source projects?
Open source projects seem to hinge a lot more on incremental improvements and change only for the benefit of users. In contrast, closed source organizations seem to use code more to quickly develop a new product or change that justifies money. Maybe closed source organizations are more willing to accept slop code that is bad but can barely work versus open source which won’t?
Baldur Bjarnason (who hates AI slop) has posited precisely this:
My current theory is that the main difference between open source and closed source when it comes to the adoption of “AI” tools is that open source projects generally have to ship working code, whereas closed source only needs to ship code that runs.
Maybe closed source organizations are more willing to accept slop code that is bad but can barely work versus open source which won’t?
Because most software is internal to the organisation (therefore closed by definition) and never gets compared or used outside that organisation: Yes, I think that when that software barely works, it is taken as good enough and there’s no incentive to put more effort to improve it.
My past year (and more) of programming business-internal applications have been characterised by upper management imperatives to “use Generative AI, and we expect that to make you nerd faster” without any effort spent to figure out whether there is any net improvement in the result.
Certainly there’s no effort spent to determine whether it’s a net drain on our time and on the quality of the result. Which everyone on our teams can see is the case. But we are pressured to continue using it anyway.
When did you last time decide to buy a car that barely drives?
And another thing, there are some tech companies that operate very short-term, like typical social media start-ups of which about 95% go bust within two years. But a lot of computing is very long term with code bases that are developed over many years.
The world only needs so many shopping list apps - and there exist enough of them that writing one is not profitable.
And another thing, there are some tech companies that operate very short-term, like typical social media start-ups of which about 95% go bust within two years.
This is a very generous sentence you have made, haha.
My observation is that vast majority of tech companies seem to operate unprofitably (the programming division is pure cost, no measurable financial befit) and with churning bug riddled code that never really works correctly.
Netflix was briefly hugely newsworthy in the technology circles because they… Regularly did disaster recovery tests.
Edit: Netflix made news headlines because someone decided that Kevin in IT having a bad day shouldn’t stop every customer from streaming. This made the news.
Our technology “leadership” are, on average, so incredibly bad at computer stuff.
I’d argue the two aren’t as different as you make them out to be. Both types of projects want a functional codebase, both have limited developer resources (communities need volunteers, business have a budget limit), and both can benefit greatly from the development process being sped up. Many development practices that are industry standard today started in the open source world (style guides and version control strategy to name two heavy hitters) and there’s been some bleed through from the other direction as well (tool juggernauts like Atlassian having new open source alternatives made directly in response)
No project is immune to bad code, there’s even a lot of bad code out there that was believed to be good at the time, it mostly worked, in retrospect we learn how bad it is, but no one wanted to fix it.
The end goals and proposes are for sure different between community passion projects and corporate financial driven projects. But the way you get there is more or less the same, and that’s the crux of the articles argument: Historically open source and closed source have done the same thing, so why is this one tool usage so wildly different?
As a dumb question from someone who doesn’t code, what if closed source organizations have different needs than open source projects?
Open source projects seem to hinge a lot more on incremental improvements and change only for the benefit of users. In contrast, closed source organizations seem to use code more to quickly develop a new product or change that justifies money. Maybe closed source organizations are more willing to accept slop code that is bad but can barely work versus open source which won’t?
Baldur Bjarnason (who hates AI slop) has posited precisely this:
That’s basically my question. If the standards of code are different, AI slop may be acceptable in one scenario but unacceptable in another.
Because most software is internal to the organisation (therefore closed by definition) and never gets compared or used outside that organisation: Yes, I think that when that software barely works, it is taken as good enough and there’s no incentive to put more effort to improve it.
My past year (and more) of programming business-internal applications have been characterised by upper management imperatives to “use Generative AI, and we expect that to make you nerd faster” without any effort spent to figure out whether there is any net improvement in the result.
Certainly there’s no effort spent to determine whether it’s a net drain on our time and on the quality of the result. Which everyone on our teams can see is the case. But we are pressured to continue using it anyway.
When did you last time decide to buy a car that barely drives?
And another thing, there are some tech companies that operate very short-term, like typical social media start-ups of which about 95% go bust within two years. But a lot of computing is very long term with code bases that are developed over many years.
The world only needs so many shopping list apps - and there exist enough of them that writing one is not profitable.
This is a very generous sentence you have made, haha. My observation is that vast majority of tech companies seem to operate unprofitably (the programming division is pure cost, no measurable financial befit) and with churning bug riddled code that never really works correctly.
Netflix was briefly hugely newsworthy in the technology circles because they… Regularly did disaster recovery tests.
Edit: Netflix made news headlines because someone decided that Kevin in IT having a bad day shouldn’t stop every customer from streaming. This made the news.
Our technology “leadership” are, on average, so incredibly bad at computer stuff.
I’d argue the two aren’t as different as you make them out to be. Both types of projects want a functional codebase, both have limited developer resources (communities need volunteers, business have a budget limit), and both can benefit greatly from the development process being sped up. Many development practices that are industry standard today started in the open source world (style guides and version control strategy to name two heavy hitters) and there’s been some bleed through from the other direction as well (tool juggernauts like Atlassian having new open source alternatives made directly in response)
No project is immune to bad code, there’s even a lot of bad code out there that was believed to be good at the time, it mostly worked, in retrospect we learn how bad it is, but no one wanted to fix it.
The end goals and proposes are for sure different between community passion projects and corporate financial driven projects. But the way you get there is more or less the same, and that’s the crux of the articles argument: Historically open source and closed source have done the same thing, so why is this one tool usage so wildly different?