I don't see this happening with for example deepseek.
Is it possible they are saving on resources by having it answer that way?
When I worked at Netflix I sometimes heard the same speculation about intentionally bad recommendations, which people theorized would lower streaming and increase profit margins. It made even less sense there as streaming costs are usually less than a penny. In reality, it’s just hard to make perfect products!
(I work at OpenAI.)
Example, I asked it to write something. And then I asked it to give me that blob of text in markdown format. So everything it needed was already in the conversation. That took a whole minute of doing web searches and what not.
I actually dislike using o3 for this reason. I keep the default to 4o. But sometimes I forget to switch back and it goes off boiling the oceans to answer a simple question. It's a bit too trigger happy with that. In general all this version and model soup is impossible to figure out for non technical users. And I noticed 4o is now sometimes starting to do the same. I guess, too many users never use the model drop down.
I am not saying they haven't improved the laziness problem, but it does happen anecdotally. I even got similar sort of "lazy" responses for something I am building with gemini-2.5-flash.
takes tinfoil hat off
Oh, nvm, that makes sense.