
Enterprise AI buyers have been stuck between two things they both need. Regulated teams need a zero data retention (ZDR) guarantee, so no prompt or agent transcript sits on a vendor’s servers. Security teams need misuse detection, which historically required the vendor to hold that same data long enough to correlate it. This week, Anthropic announced Enterprise Frontier Safeguards (EFS), an architecture that tries to give both. EFS stores monitoring data in cloud infrastructure the cus
Anthropic announced Enterprise Frontier Safeguards, an architecture designed to resolve a conflict that regulated enterprises face: they need zero data retention for privacy but also need misuse detection, which historically required vendors to retain data. EFS stores monitoring data in the customer's own cloud infrastructure rather than Anthropic's servers, while Anthropic's automated systems analyze that data for serious misuse like attempts to build offensive capabilities or signs of stolen credentials. The approach moves storage, review decisions, and encryption keys to the customer's control, eliminating the need for Anthropic to perform human review of flagged activity. EFS will roll out in phases with the goal of broad availability later in the fall, and access is currently request-based.

While restaurant owners might look to generative AI as a shortcut to sprucing up their menu, customers can viscerally sense that something is wrong with the food.
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ChatGPT, Claude, and Grok all suffered outages at nearly the exact same time for reasons that remain murky.

Most teams building a shopping assistant or agent rebuild the same scaffolding: an agent loop, a tool layer over the catalog, an approval gate, and an eval suite. Anthropic has now released that scaffolding as code. This week, they published anthropics/commerce-agents, a reference blueprint containing a shopping agent and a merchant agent, along with four runnable verticals: retail, travel, telecom and entertainment. It ships alongside two write-ups: a product announcement and an engineering de
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