Beyond Accuracy: Architecting Performant, Cost-Efficient Agentic AI
OutSystems, Thursday, October 15th, 2026
OutSystems explains why architecture, not model choice, determines whether agentic AI is performant and cost-efficient in production.
OutSystems says enterprise AI evaluations usually focus on accuracy, and proof-of-concept agents work well because they solve narrow problems, but in production agentic systems must also be performant, scalable and cost-efficient.
The post explains the reason-act loop most enterprise agents use, in which the agent reasons, selects a tool, observes the result and repeats.
It argues that growing context, memory and tool use in that loop creates an architectural vulnerability, and offers ways to optimize agent architecture for real-world cost and performance.