# Cost optimization Organizations that treat cost as a first-class design constraint from the start build agentic systems that scale sustainably and deliver measurable business value per dollar spent. Agentic AI introduces cost dynamics that differ fundamentally from traditional cloud workloads, reasoning cycles consume tokens through iterative plan-execute-verify-reflect loops, multi-agent coordination adds multiplicative overhead, and autonomous tool invocations generate unpredictable cost spikes. Effective cost optimization requires designing with cost awareness from inception, right-sizing model and memory capabilities to task requirements, and implementing full visibility to enable data-driven decisions. **Capabilities** + [Reasoning and execution cost optimization](agentcost01.html) + [Model invocation and token cost optimization](agentcost02.html) + [Agent memory and state cost management](agentcost03.html) + [Agent tool serving cost optimization](agentcost04.html) + [Agent cost visibility and attribution](agentcost05.html) + [Agent discovery and deployment cost optimization](agentcost06.html) + [Agent cost governance and continuous optimization](agentcost07.html)