The number of questions on Stack Overflow fell by 78 percent in December 2025 compared to a year earlier. Developers are switching en masse to AI tools in
I’ve posted questions, but I don’t usually need to because someone else has posted it before. this is probably the reason that AI is so good at answering these types of questions.
the trouble now is that there’s less of a business incentive to have a platform like stack overflow where humans are sharing knowledge directly with one another, because the AI is just copying all the data and delivering it to the users somewhere else.
What we’re all afraid is that cheap slop is going to make stack broke/close/bought/private and then it will be removed from the public domain…then jack up the price of islop when the alternative is gone…
I do wonder then, as new languages and tools are developed, how quickly will AI models be able to parrot information on their use, if sources like stackoverflow cease to exist.
It’ll certainly be of lesser quality even if they go through steps to make it able to address it.
good documentation and open projects ported might be enough to give you working code, but it’s not going to be able to optimize it without being trained on tons of optimization data.
There are open weight models that users can download and run locally. Because the weights are open, they can be customised and fine tuned.
And then there are fully open source models, that publish everything, the model with open weights, the training source code, as well as the full training dataset.
The hot concept around the late 2000’s and early 2010’s was crowdsourcing: leveraging the expertise of volunteers to build consensus. Quora, Stack Overflow, Reddit, and similar sites came up in that time frame where people would freely lend their expertise on a platform because that platform had a pretty good rule set for encouraging that kind of collaboration and consensus building.
Monetizing that goodwill didn’t just ruin the look and feel of the sites: it permanently altered people’s willingness to participate in those communities. Some, of course, don’t mind contributing. But many do choose to sit things out when they see the whole arrangement as enriching an undeserving middleman.
Yes, I think this will create a new problem. new things won’t be created very often, at least not from small house or independent developers, because there will be this barrier to adoption. corporate controlled AI will need to learn them somehow
I’ve posted questions, but I don’t usually need to because someone else has posted it before. this is probably the reason that AI is so good at answering these types of questions.
the trouble now is that there’s less of a business incentive to have a platform like stack overflow where humans are sharing knowledge directly with one another, because the AI is just copying all the data and delivering it to the users somewhere else.
What we’re all afraid is that cheap slop is going to make stack broke/close/bought/private and then it will be removed from the public domain…then jack up the price of islop when the alternative is gone…
I do wonder then, as new languages and tools are developed, how quickly will AI models be able to parrot information on their use, if sources like stackoverflow cease to exist.
I think this is a classic of privatization of commons, so that nobody can compete with them later without free public datasets…
It’ll certainly be of lesser quality even if they go through steps to make it able to address it.
good documentation and open projects ported might be enough to give you working code, but it’s not going to be able to optimize it without being trained on tons of optimization data.
There are free open source models you can run locally and they have all the answers.
But can anyone train on them? What happens to the original dataset?
There are open weight models that users can download and run locally. Because the weights are open, they can be customised and fine tuned.
And then there are fully open source models, that publish everything, the model with open weights, the training source code, as well as the full training dataset.
The hot concept around the late 2000’s and early 2010’s was crowdsourcing: leveraging the expertise of volunteers to build consensus. Quora, Stack Overflow, Reddit, and similar sites came up in that time frame where people would freely lend their expertise on a platform because that platform had a pretty good rule set for encouraging that kind of collaboration and consensus building.
Monetizing that goodwill didn’t just ruin the look and feel of the sites: it permanently altered people’s willingness to participate in those communities. Some, of course, don’t mind contributing. But many do choose to sit things out when they see the whole arrangement as enriching an undeserving middleman.
Probably explains why quora started sending me multiple daily emails about shit i didn’t care about and removed unsubscribe buttons form the emails.
I don’t delete many accounts… but that was one of them
Works well for now. Wait until there’s something new that it hasn’t been trained on. It needs that Stack Exchange data to train on.
Yes, I think this will create a new problem. new things won’t be created very often, at least not from small house or independent developers, because there will be this barrier to adoption. corporate controlled AI will need to learn them somehow