Started using Cursor (CC) and initially thought code automation was complete. Reality check after extended use: AI commits frequent small bugs and occasional critical low-level errors.

The workflow bottleneck: You're still responsible for production quality, which means constant code review and cleanup. Net result = three steps forward, one step back.

The takeaway for solo devs: AI coding assistants accelerate prototyping but don't eliminate QA overhead. You're trading typing speed for debugging time. The productivity gain exists but isn't the 10x some claim - more like 2-3x with the quality tax included.

This is why pure AI-generated codebases still need human oversight architecture. The tooling improves iteration speed, but system reliability still requires manual validation layers.