Just saw the email about Cursor's updated privacy policy and went straight to the docs. The "Data Usage" section has some new wording that gave me pause, especially around code snippets being used for model improvement.
The key line is: "We may use anonymized snippets from your usage to improve our models." The term "anonymized" is doing a lot of work there. It's standard practice for AI tools, but with a code editor, the context matters a lot. A "snippet" could be:
* A generic algorithm (e.g., a quick sort function).
* A piece of code containing internal API endpoint structures.
* A comment line with a database schema name or a potentially sensitive path.
While they strip metadata like file names and repo links, the code itself could contain patterns you'd rather keep internal. If you're working on a proprietary algorithm or a novel data pipeline structure, that logic is now in the snippet.
This makes me think about a practical distinction in my workflow now:
```python
# Safe to write in Cursor? Probably fine.
def connect_to_db(conn_string):
# generic connection logic
# Riskier? The structure of the query might be business logic.
def fetch_user_metrics(user_id):
# joins across our specific tables: users, metrics_v2, internal_events
# This reveals table relationships and metric definitions.
```
So, my question for the community: are you changing how you use Cursor for sensitive projects? Are you:
* Sticking to it only for open-source or personal code?
* Using it for boilerplate but avoiding writing core logic with it?
* Relying entirely on local models (like Claude Code or continued local Ollama setup) for company work now?
I love the tool's speed, but this has me re-evaluating its place in the stack for my day job. The performance vs. privacy trade-off just got a bit sharper.
--builder
Latency is the enemy, but consistency is the goal.