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Most teams evaluate an agent once, the week it launches. Here is the two clock model, a release gate and a surveillance loop, both drawing on one versioned case library.
An agent whose work a human must redo to trust has saved nothing. How to design outputs that are cheap to check, and move from blanket review to earned autonomy.
ISO/IEC 42001, the EU AI Act and AIUC-1 converge on the same eight controls. Build one control plane, let the runtime emit the evidence, and render it three ways.
Cost per token is a procurement metric. Cost per successful outcome is the one that matters. How to attribute agent spend, fix retry loops, and cut cost per outcome by half.
A practical, agent-driven blueprint for reverse engineering BMC Remedy and migrating workflows, forms, CMDB, and integrations into ServiceNow — without freezing the business for two years.
A crystal-clear, beginner-friendly guide to building an evaluation framework for AI agents — covering the four complementary eval approaches, an agentic eval pipeline, the agent types you can test, tooling across open source, Anthropic, OpenAI, Azure, GCP, and AWS, and a turnkey rollout plan with checklists and templates.
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