ai agent cost overruns prevention a wide funnel on plinth

AI Agent Cost Overruns: Essential Guide to Avoid Risk

August 9, 2026
Artificial Intelligence
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An agent decides its own workload, so it also decides its own bill: how many steps to take, how many tools to call and how much context to carry forward. This guide explains why agent spend behaves nothing like ordinary software spend, names the seven failure modes behind most overruns, shows how to model the unit economics of a single run before you build, and sets out the design-time and runtime guardrails that cap the damage – step and depth limits, tool budgets, duplicate-call breakers, per-run cost ceilings and kill switches – plus cost regression testing, the four signals worth paging on, and a fully worked invoice-agent example.

ai cost governance token budgets a three rising rounded bars

AI Cost Governance: Proven Controls to Stop Costly Waste

August 9, 2026
Artificial Intelligence
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An AI budget behaves nothing like a software budget: it moves the moment somebody writes a longer prompt, enables a more capable model or ships an agent that retries five times instead of once. This guide sets out the controls that keep inference spend predictable, covering token budgets at request, session and tenant level, a capability ladder and routing strategy that sends each task to the cheapest model that can do it, hard and soft usage limits that stop runaway agent loops, prompt caching and context discipline, tagging and unit-cost dashboards, the monthly operating cadence, and a fully worked support-copilot example.