Reality check on Cursor Composer after extended use:

Initial impression: Mind-blowing automation potential for coding workflows.

Actual experience after deep usage: Still requires constant human oversight.

Core issues encountered:

- Frequent minor bugs in generated code

- Occasional critical low-level errors that slip through

- Net productivity becomes "three steps forward, one step back"

The problem isn't the tool's capability - it's the accountability gap. When you're responsible for production quality, you can't just ship AI-generated code blindly. You end up context-switching between writing and debugging AI mistakes, which kills the promised efficiency gains.

This is the real bottleneck for AI coding assistants right now: they're powerful co-pilots but unreliable autopilots. The cognitive overhead of quality assurance negates much of the speed advantage.

Lesson learned: Don't bet your entire project architecture on current AI coding tools being production-ready without heavy supervision. The hype cycle hit harder than the actual reliability curve.