Often the AI makes a recommendation that looks good, but has consequences 4 or 5 changes later that you'll need to reckon with. You'll see this especially with web vs. mobile UI behaviours. Cursor isn't so good at reverting changes yet, and GIT has saved me a LOT of headache.
2. Collaborate with o1 to create a PRD and put it in the same folder as your specs.
This increases the likelihood Cursor's recommended changes comply with your intent, style and color guidelines and overall project direction.
I don't know if docker would be the right service for my use case, but considering the user experience on this thread I thought I'd ask...
I'm looking to deploy a python based analytics service which runs for about 12 hours per job, uploads the results to a separate server then shuts down. At any given time there could be up to 100 jobs running concurrently.