Tag: AI agent lifecycle
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Snowflake’s agent object enhancements make it easier than ever to move from AI agent experimentation to governed production deployment without treating every agent as a long-lived, broadly visible shared asset. Temporary agents, Personal Database agents, and secure agents each reduce friction, including setup friction, specification exposure, or shared-environment dependency. Together, these three new agents support…
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AI initiatives don’t become production-ready simply because an organization has governed data and access to capable models. AI initiatives actually become scalable when the underlying data platform can enforce access controls, withstand failures, deliver predictable performance, provide operational evidence, and connect consumption to business value. That’s why data platforms need their own well-architected framework. Infrastructure…