This developer deploys stateful AI Agents to the free tier of Cloudflare Workers and pairs them with an evaluation mechanism. The focus is quite specific: the Agent should not merely answer a question once on a temporary basis; it must also preserve state across multi-turn tasks while using evaluations to check whether an update has broken its original behavior.
This developer deploys stateful AI Agents to the free tier of Cloudflare Workers and pairs them with an evaluation mechanism. The focus is quite specific: the Agent should not merely answer a question once on a temporary basis; it must also preserve state across multi-turn tasks while using evaluations to check whether an update has broken its original behavior.
This type of solution is suitable for prototyping and internal validation, especially in scenarios that require linking together simple forms, conversation records, or task queues. Before going live, it is important to check whether state storage is properly isolated, whether the system can recover after failures, whether invocation costs might spiral out of control as usage increases, and whether the evaluation samples cover the branches real users are likely to encounter. The free tier lowers the barrier to experimentation, but does not mean the production environment is already adequately protected.
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