OpenAI Dots vs Meta Muse: two agent trust models compared
OpenAI Dots and Meta Muse launched 21 days apart with opposite trust models: Dots inherit 4,000+ ChatGPT plugins and the user's identity behind auto-review and four rule levels, while Muse runs each user in a dedicated VM behind a Sentinel gatekeeper with surrogate credentials. Only Dots are reachable from Sweden, through Business Premium, so the practical work for a Swedish team is plugin inventory, rule levels and audit attribution.
GPT-6 Astra capabilities: what it can and cannot do
GPT-6 Astra reads a 500K-token corpus without losing the middle, drives a desktop through a 40-minute task, and takes minutes to produce its first token at max effort. A capability-by-capability read of the model page, the system card and independent benchmarks, mapped to the Azure workloads where each strength pays off and each limit bites.
A classifier is not a sandbox: isolating coding agents
A published attack chain achieved remote code execution against Claude Code in auto mode, with the safety classifier approving the steps that led to compromise and then blocking the cleanup command. What the break teaches teams running AI coding agents, and how to build real isolation on Azure with Hyper-V sandboxes, default-deny egress and short-lived credentials.