
Every agent that writes code needs somewhere to run it. That “somewhere” is now a product category with at least a dozen vendors, four incompatible billing models, and marketing pages that quote cold starts measured under conditions nobody publishes. This comparison fixes the units. It covers the five platforms most teams shortlist — E2B, Daytona, Modal Sandboxes, Cloudflare Sandbox SDK, and Vercel Sandbox — along with Runloop, Fly.io Sprites, and Northflank where they change the
Agents that write code need somewhere to execute it, creating a product category with multiple vendors, incompatible billing models, and inconsistent performance claims. This comparison establishes standardized measurement units across five major platforms, examining cold start times under concurrent load, filesystem persistence between operations, internet access policies, and idle billing charges. The analysis demonstrates that vendor-quoted performance numbers measure different conditions and that tail latency matters more than median speeds for real-world agent workloads. Cost comparisons show that billing structure dramatically affects total expenses, with idle time scenarios producing 3 to 7 times higher costs than short burst scenarios on the same infrastructure.

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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