A short story about Cursor's counterattack.
Cursor follows the path you mentioned - deeply distilling the programming scene to the extreme.
The valuation in 2024 is several billion dollars.
But - by the end of 2025, after Claude and GPT have greatly improved their programming capabilities, Cursor's "model layer advantage" has almost disappeared.
Its current moat is not the distilled model, but: - The editing behavior data accumulated by users - The deeply integrated product experience of IDE - The engineering capabilities of multi-file context understanding Distillation itself has not become a barrier, the data flywheel is.
What data is Cursor actually collecting?
Every time you write code in Cursor, it is recording: - Did you accept AI completion, or delete and rewrite?
- After you accepted it, what did you change within 5 seconds?
- What question did you ask and were you satisfied with the answer?
- In what context (what language, what framework, what code structure) do you have a higher acceptance rate?
What these data tell it is not "which answer is right" - but "what is good in a real programming scenario".
This is exactly what the general large model does not have.
GPT knows "how to write grammatically correct code", but it doesn't know "what style of component structure Brad prefers in this React project".
How the flywheel turns: Users accept/reject completion ↓ Cursor knows "what is good in this scenario" ↓ Use these signals to fine-tune/distill the model ↓ Completion is more accurate → Higher acceptance rate ↓ More high-quality signals are collected 🔄 The key is: the more users, the denser the signals, the faster the flywheel.
Even if latecomers use the same distillation method, they cannot replicate this data accumulation.
This is why Cursor has not been completely replaced by GitHub Copilot or users who directly use Claude API after the model layer advantage disappears.