How developers use AI.
链接到某一部分使用案例
使用案例
While code generation still comes first, it's interesting to note that code review (a new option this year) has jumped straight to third place. After all, someone will eventually need to read through the 30k lines of codes the intern vibe-coded over the week-end…
您使用 AI 工具做什么？
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链接到某一部分AI 代码生成
AI 代码生成
The difference with last year is striking here. Back then the average respondent was using AI sporadically to generate a small percentage of their code, but today that same developer is much more likely to rely on AI for the bulk of their coding.
您编写的代码中有多少比例是 AI 生成的？
链接到某一部分AI 代码重构
AI 代码重构
Similarly, using AI-generated code without having to refactor it first is no longer the exception, with many respondents reporting only needing to refactor around 25% of AI output.
在使用 AI 生成代码时，您在使用前重写或重构的比例是多少？
链接到某一部分重构原因
重构原因
When respondents do need to refactor AI-generated code, the culprits tend to be poor code style and hallucinations. Interestingly, variable renaming does not seem to be as much of a factor anymore, pointing to the fact that LLMs are getting better at following instructions and learning from existing codebases.
需要您重构 AI 生成代码的主要原因是什么？
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链接到某一部分代码生成频率
代码生成频率
It seems clear that AI has become embedded in our work, with a majority of respondents using it multiple times per day, and a growing segment using it constantly.
您多久使用一次 AI 工具来生成或重构代码？
链接到某一部分其他任务频率
其他任务频率
While the main focus of this survey is coding, other AI uses are also seeing increased used compared to last edition. After all if you trust AI with the main part of your job, it does seems logical to trust it with everything else, too.
除了代码生成之外，您多久使用一次 AI 工具处理其他任务？
链接到某一部分生成的代码
生成的代码
Almost every type of generated code saw an increase compared to last survey, with tests in particular becoming a key reason to use AI.
您使用 AI 工具生成什么样的代码？
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链接到某一部分个人支出
个人支出
The proportion of respondents enjoying the benefits of AI without personally having to spend their hard-earned cash has dramatically shrunken year-over-year; while the $100-$500 monthly spend demographic is seeing significant growth. This may be due to the rise of coding agents, which often carry heavier financial costs compared to simple chatbots.
您个人每月在 AI 工具上花费多少（美元）？
链接到某一部分行业
行业
Don't hesitate to use our built-in Query Builder on any other chart to filter these survey results according to any specific industry sector.
你在哪个行业工作？
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链接到某一部分本地 AI
本地 AI
More and more respondents have tried local AI models, and while they aren't as powerful as their cloud-based cousins right now, there is strong potential for disruption as they provide a cheaper alternative to traditional frontier labs models.
您尝试过在自己的机器上本地运行 AI 模型吗？
链接到某一部分资源推荐
资源推荐
Sentry MCP
Sentry MCP plugs Sentry's API directly into your LLM, letting you ask questions about your data in natural language.
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