What AI did to stackoverflow in a graph

你刚刷到这条消息，本来准备顺手划走，但又怕自己错过了真正会影响下一步判断的那一点。

最容易做错的，是What AI did to stackoverflow in a graph；代价往往是如果只盯表面热闹，你很容易在错误方向上花掉时间、预算和注意力。；我先给一个保守判断：Stack Overflow成了AI错误急诊室。

The easy mistake is assuming the graph means AI replaced Stack Overflow. If you only watch the surface hype, you can waste time, budget, and attention in the wrong direction. My conservative read is simpler: Stack Overflow became AI's error ER.

The number that changed my mind was 35%: in Stack Overflow's 2025 survey, about a third of developers said they return at least sometimes because AI or AI-assisted tools created something they needed to fix, understand, or debug. [S002] That is not a majority, and it should not be exaggerated. It is still too large to dismiss.

The rest of the survey sharpens the picture. 66% said the most frustrating AI behavior is being almost correct. 45.2% said debugging AI-generated code takes more time. 75.3% said they still go to a real person when they do not trust the model. [S001] Demand did not disappear. It moved downstream into rework.

A tool update is not worth following because it lists more features; it matters if it changes your next decision. Based on Stack Overflow's 2025 survey pages on AI and platform usage, not a full traffic graph or product telemetry, my next investment would be a library of known failure cases, counterexamples, and debugging notes. If someone on your team still treats AI output as finished work, share this with them. What failure pattern do you document on purpose?

真正该讨论的是：What AI did to stackoverflow in a graph