For more complex environments, use multiple VMs (common to have large VMs running in AWS/GCP for development and only use your laptop or phone as a thin client)
I personally, can handle only one feature at a time, prompt the AI, refine the changes, re-plan, review changes, rewrite parts when necessary, but my mind is still with one feature.
How do you folks manage multiple parallel feature development at the same time?
or 8 VMs? won't syncing be super slow there? like i believe it, but it feels like a lot of setup and i don't understand why nobody seems to be talking about it.
Long before AI I routinely had 5 parallel development environments I would flip between. (I do distributed systems stuff, think HPC-adjacent clusters, when you're too big for Kubernetes and too small for supercomputing). One would be running long-running tests for my current changes, one being reset to a clean state, and 3 more on standby so I had 100% "duty cycle" (the reset took a while). You got used to multitasking.
Some people have multiple agents working in the same directory, and allow the agents to tell each other what they're doing and which files they're editing: https://github.com/Dicklesworthstone/mcp_agent_mail
In case of AI, it just delivers things in 2-3 minutes, this time is not enough (or worth) to switch the context (for me personally)