Retaining context across tasks could let organizations control their AI assistants' behavior without relying on external platforms.
funes is a memory system that stores the reasoning traces and decision-making history produced by coding agents as they work. It indexes this history locally on a machine, allowing agents to recall past decisions and rationale rather than starting each new session from zero. The memory can be shared across machines and agents as a private dataset that the user owns, enabling continuity when switching between different coding agents or working from different locations. This matters because coding agents currently lose the context of their past work when sessions end, and funes makes that accumulated knowledge accessible and searchable during future work.

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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