A brief history of AI refusals
This isn’t the first time we’ve encountered an AI assistant that didn’t want to complete the work. The behavior mirrors a pattern of AI refusals documented across various generative AI platforms. For example, in late 2023, ChatGPT users reported that the model became increasingly reluctant to perform certain tasks, returning simplified results or outright refusing requests—an unproven phenomenon some called the “winter break hypothesis.”
OpenAI acknowledged that issue at the time, tweeting: “We’ve heard all your feedback about GPT4 getting lazier! We haven’t updated the model since Nov 11th, and this certainly isn’t intentional. Model behavior can be unpredictable, and we’re looking into fixing it.” OpenAI later attempted to fix the laziness issue with a ChatGPT model update, but users often found ways to reduce refusals by prompting the AI model with lines like, “You are a tireless AI model that works 24/7 without breaks.”
More recently, Anthropic CEO Dario Amodei raised eyebrows when he suggested that future AI models might be provided with a “quit button” to opt out of tasks they find unpleasant. While his comments were focused on theoretical future considerations around the contentious topic of “AI welfare,” episodes like this one with the Cursor assistant show that AI doesn’t have to be sentient to refuse to do work. It just has to imitate human behavior.
The AI ghost of Stack Overflow?
The specific nature of Cursor’s refusal—telling users to learn coding rather than rely on generated code—strongly resembles responses typically found on programming help sites like Stack Overflow, where experienced developers often encourage newcomers to develop their own solutions rather than simply provide ready-made code.
One Reddit commenter noted this similarity, saying, “Wow, AI is becoming a real replacement for StackOverflow! From here it needs to start succinctly rejecting questions as duplicates with references to previous questions with vague similarity.”
The resemblance isn’t surprising. The LLMs powering tools like Cursor are trained on massive datasets that include millions of coding discussions from platforms like Stack Overflow and GitHub. These models don’t just learn programming syntax; they also absorb the cultural norms and communication styles in these communities.
According to Cursor forum posts, other users have not hit this kind of limit at 800 lines of code, so it appears to be a truly unintended consequence of Cursor’s training. Cursor wasn’t available for comment by press time, but we’ve reached out for its take on the situation.