Building the enterprise environment for agentic AI
a day ago
- Agentic AI in enterprises is a larger systems problem involving orchestration, data access, tool use, and scalability, not just LLM inference.
- Key metrics for evaluating agentic AI systems include task success rate, cost per task, time per task, task throughput, agent density, and latency.
- Plan capacity using agent density (agents per vCPU) rather than raw agent count, and monitor P95 task latency for better performance signals.
- Default to scale-out architecture for agent hosting, reserving scale-up for workloads with heavier per-agent compute or constraints.
- Production-grade agentic AI value comes from automating codified workflows like code creation, regression testing, ticket triaging, market analysis, and security review.