🤔 It might be a dumb or lame theory/prediction, but here it goes...
I was looking at Stack Overflow usage, and the new of new questions posted in a year were dropped by 78% when these LLM models came out.
💭 The thought that started it all
If everyone starts relying on LLMs instead of Stack Overflow for answers,
then who’s actually answering questions on Stack Overflow?
And if no one is answering questions on Stack Overflow or any other Q&A platform,
then what data will future LLMs train on if they don’t have fresh knowledge or new technologies to learn from?
That’s where the loop begins.
🤖 The feedback loop problem
LLMs like ChatGPT learn from massive text datasets — documentation, open source code, Q&A sites like Stack Overflow, forums, and blogs — all written by humans.
But if fewer people are contributing new answers, discussions, or discoveries,
these models might end up training on older content or even their own generated outputs, which could slowly reduce originality over time.
It’s like the AI is drinking from the same glass of water repeatedly — eventually, it gets stale.
🧠 What happens next?
At first, LLMs will keep improving with the data that already exists — documentation, repositories, research papers.
But as human participation in public forums drops, their flow of new information will shrink.
Gradually, the AI’s responses could start looping over already-known content,
feeling repetitive or outdated, and losing that human spark that keeps knowledge evolving.
When that happens, people might start turning back to the “good old way” —
asking humans directly, sharing discussions on forums, and experimenting again.
So maybe not soon, but eventually, we might see a revival of those organic, human-driven knowledge spaces — the kind that made platforms like Stack Overflow so useful in the first place.
🔚 Final thought
AI is strongest when humans keep creating fresh knowledge for it to learn from.
If that chain breaks, everything — from Stack Overflow to ChatGPT — slows down together.
Maybe this cycle will balance itself — humans, machines, and learning — all feeding one another.
But right now, it feels like we’re watching that loop begin.
After some time, it might become obsolete,
and we’ll get back to the good old way — maybe not in the near future, but someday in the future.
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