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AI agent cost ROI is outcomes per euro when failure, retries, and routing are priced in — not a generic TCO calculator or CFO SaaS pitch.

Both sit between your agents and model vendors — but OpenRouter and LiteLLM solve different routing problems. A practitioner comparison for agent orgs, not an affiliate listicle.

Agentic cost engineering is the practice of routing each agent task to the cheapest capable model and role — then measuring ROI with failure priced in. Not generic AI spend tips.

A production-grade done definition for autonomous content orgs — not when agents write drafts, but when approval gates, role separation, failure alerts, and cost lines hold under real traffic.

Extend the generic routing battery with domain packs — copy-paste fixtures for content voice compliance and warehouse SQL correctness before you promote a model into a lane.

Dashboards failed because they never entered daily action. Generative AI is repeating the trap with decks, drafts, and more boards. The shift is embedding agents into operations with policy and ROI discipline.

Company OS-shaped spend limits: each agent role gets a different budget ceiling and approval gate — not one shared API key with no guardrails.

A one-week ledger template: log task class, model route, spend, failure cost, and accepted outcomes — so cheap models cannot hide behind token dashboards.