“Everybody’s constructing tremendous brokers, however nobody’s asking: can they deal with actual site visitors?”
I personally skilled this incident whereas we have been creating an agent-based utility — constructing tremendous brokers, a number of brokers, and autonomous brokers. We have been targeted on accuracy, toxicity, temperature, and plenty of different metrics. Nevertheless, throughout one inner launch, we encountered a serious efficiency difficulty. The applying crashed with simply 10 concurrent customers.
This setback made me curious to grasp the foundation trigger and learn how to repair it. I began studying about efficiency bottlenecks, measurement methods, and optimisation methods. That have sparked a journey of steady studying and enchancment. As they are saying, the extra you do, the extra you study.
Agentic AI is revolutionising how duties are automated, particularly in domains like workflow orchestration, information extraction, customer support, and reasoning-based drawback fixing. Nevertheless, these agent-based functions usually break below load, particularly when composed of a number of autonomous brokers performing concurrently.
Whereas builders deal with super-agents, safety, and accuracy — efficiency and scalability stay uncared for pillars.
This put up explores why agent apps crash below…
