Agent Ops: Models, Deployment, and Validation

Feathery raises $30M to rewire financial-services workflows. Feathery raises $30M to scale an AI operating and decisioning platform that aims to rewire financial-services workflows. This signals a push to treat agentic decisioning as an operational layer—start designing orchestration, audit trails, and compliance hooks now (Principle 09).

Setting up your spare Mac for Claude Code to control, a step-by-step guide. The guide turns a spare Mac into a locked-down Claude Code agent host that supports remote mobile and SSH control while isolating sensitive data. Use it as a concrete pattern for safe, local agent hosting and runtime isolation when building your agent islands (Principle 07).

Japan to buy 27,500 Nvidia Rubin chips to build domestic AI foundation model for robots. Japan secures 27,500 Rubin chips to build a sovereign robotics foundation model led by Noetra with SoftBank, Sony, and NEC. National-scale compute procurement changes where and how robotics models are developed and hosted—plan for model locality, latency, and governance boundaries in your fleet designs (Principles 07, 12).

China Just Reset the AI Race: Here’s What to Know. Moonshot AI’s Kimi K3 matches or exceeds US frontier models while drastically cutting infrastructure costs, reshaping the competitive landscape. Cheap, capable models change the economics of deploying agentic systems—expect more model heterogeneity, different trust profiles, and new validation requirements (Principles 02, 12).

GPT-5.6 used a prompt to close a 30-year gap in convex optimization. GPT-5.6 produces a Lean-verified proof that resolves a long-standing convex optimization gap, advancing AI-driven formal mathematics. Models that output machine-checkable artifacts let you integrate formal verification into outcome validation pipelines—treat proofs and executable artifacts as first-class audit evidence (Principle 16).