Since yesterday, I’ve had a noticeably better experience using GPT-5 in Cursor, in contrast to much of the feedback I’ve seen from other users.
In particular, when working with very large codebases, GPT-5 handles the work far better than any other model. I believe a big part of this comes down to GPT-5’s excellent tool usage. Together with Cursor, it genuinely feels like the two are working as a team.
It reliably finds the right places in the code, makes targeted edits, and does so with a solid understanding of the overall structure. As a result, changes aren’t just localized, they propagate correctly through process chains, ensuring that every related step is considered and updated.
I’m not sure whether this improvement is due to changes in Cursor’s internal context-finding and selection logic around the GPT-5 release, but the difference feels significant. Edits are more precise, coverage is more complete, and the overall workflow is smoother.
Another major improvement I’ve noticed is that GPT-5 handles weaker or less precise prompts much better than before. It seems to internally refine the request, identify the true purpose behind it, and deliver the best possible result, even when the input is imperfect.
Overall, great job to the Cursor and OpenAI teams, for me, this really takes assisted coding to a whole new level
aside from the pesky usage limit 