For daily work - neither. They basically promote the style of work where you end up with mediocre code that you don't fully understand, and with time the situation gets worse.
I get much better result by asking specific question to a model that has huge context (Gemini) and analyzing the generated code carefully. That's the opposite of the style of work you get with Cursor or Windsurf.
Is it less efficient? If you are paid by LoCs, sure. But for me the quality and long-term maintainability are far more important. And especially the Tab autocomplete feature was driving me nuts, being wrong roughly half of the time and basically just interrupting my flow.
I wrote a simple Python script that I run in any directory that gets the context I usually need and copies to the clipboard/paste buffer. A short custom script let's you adjust to your own needs.
Legal issues aside (you are the legal owner of that code or you checked with one), and provided it's small enough, just ask an LLM to write a script to do so . If the code base is too big, you might have luck choosing the right parts. The right balance of inclusions and exclusions can work miracles here.
Cursor can index your codebase efficiently using vector embeddings rather than literally adding all your text files into context. Someone else mentioned machtiani here which seems to work similarly.
I get much better result by asking specific question to a model that has huge context (Gemini) and analyzing the generated code carefully. That's the opposite of the style of work you get with Cursor or Windsurf.
Is it less efficient? If you are paid by LoCs, sure. But for me the quality and long-term maintainability are far more important. And especially the Tab autocomplete feature was driving me nuts, being wrong roughly half of the time and basically just interrupting my flow.