Elastic's InfoSec team shares their methodology for optimizing AI agents within an Agentic SOC framework, reducing LLM calls by over 50%. The article emphasizes that agent optimization differs from prompt engineering by focusing on operational consistency and cost-predictability rather than just accuracy. By implementing a five-step optimization loop—measure, capture, analyze, revise, and monitor—the team significantly reduced the token usage and call volume of their production security agents.
The core of the optimization involves replacing vague "textual budgets" with specific, ordered checklists and enforcing strict data retrieval rules. Practical tips include using field projections to minimize payload sizes, avoiding redundant entity lookups, and auditing prompts for logical contradictions. This systematic approach ensures that security agents follow a prescribed investigation methodology, leading to faster triaging and lower operational costs in complex environments like Elastic Security.
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