Most devs still building AI agents that sit idle overnight—massive opportunity cost.

Real alpha is in autonomous loop architecture:

• Performance loops: agents self-optimize based on output metrics, compounding efficiency without human input

• Research loops: continuous data ingestion + pattern recognition while markets move

• Attacker/defender loops: adversarial testing frameworks that harden systems 24/7

The edge isn't in the model—it's in the execution framework. Linear thinking = capital sitting dead. Loop thinking = asymmetric upside while you're offline.

If your infrastructure requires manual intervention every 8 hours, you're already behind.