LLMs have made it feasible for security teams to build their own AI-driven SOC, and doing so offers real learning value — forcing teams to understand data pipelines, triage gaps, and where AI actually helps. However, at scale, the operational costs mount quickly: model drift, maintenance burden, governance, and the need to meet benchmarks like Sysdig's 555 rule (detect in 5s, investigate in 5min, respond in 5min). The core argument is 'build to learn, buy to scale' — teams that experiment with homegrown AI SOCs are best positioned to evaluate vendor solutions, but should recognize when DIY stops making sense and commercial platforms become the smarter investment.
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