Claire and Peter break down today’s essential AI developments: Bloomberg reports Google has delayed Gemini 3.5 Pro after internal tests missed targets—especially on coding—raising fresh questions for enterprises about vendor lock-in and keeping a model-agnostic strategy. On the productivity side, Google’s Pics image editor is rolling out across Workspace business and education tiers, bringing prompt-to-image and edits directly into Docs, Slides, and Sheets—along with new needs for brand, copyright, and disclosure guardrails.They also unpack mounting pressure on model providers as Microsoft’s Satya Nadella critiques Anthropic’s Claude Fable policies around output rights and silent fallbacks to older models, pushing buyers to scrutinize predictability, data ownership, and contract terms. From China, Moonshot AI launches Kimi K3, a massive open-weight model with a million-token context window, while Beijing amplifies calls for multilateral AI governance—making global model sourcing a risk, compliance, and geography decision as much as a performance one.Finally: US opposition to AI data centres intensifies with lawsuits around a major Michigan project, regulators diverge across the EU, US, and Australia, enterprise services shift toward longer AI modernization partnerships, and investors start demanding clearer payback timelines. The takeaway: keep optionality, tighten governance, and focus AI spend where outcomes are measurable.

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