AI-ready questions test whether you can reason about LLMs and AI systems as engineering material — limits, costs, evaluation, failure modes — not just hype.
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You're setting AI tool usage standards across a fast-growing engineering org where teams have wildly different comfort levels — some already delegate heavily to agents, others barely use autocomplete. How do you build a policy that raises the floor without capping the teams already ahead?
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