This article explores the cost and efficiency differences between two architectures in an AI-driven Security Operations Center (SOC): single agents with on-demand skills versus a fleet of specialized agents. Based on production data from Elastic InfoSec, specialized agents are significantly more cost-effective, reducing the price per investigation from $3.42 to $0.69. This 5.7x cost reduction is achieved by using deterministic orchestration and inline methodologies, which minimize expensive reasoning-only LLM calls and token overhead.
While specialized workflows excel at high-volume automated triage, single agents with skill libraries remain valuable for analyst-led, exploratory investigations where flexibility is prioritized over cost. The article provides a decision framework for security teams to choose the right architecture based on volume, reproducibility, and the need for interactive pivots. By leveraging consumption APIs, organizations can measure their own token usage to optimize their agentic SOC spend.
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