
Miro CEO says companies must redesign work around AI, not bolt it on
THE SO WHAT
The claim that AI only pays off when you redesign workflows — not just add features — matches what operators are seeing: tooling is ahead of process. This week, pick one core workflow and explicitly remove or reorder steps assuming AI assistance exists, then measure that against your current “AI-enhanced” version.
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MORE FROM THE WIRE
Applied AIHuawei and DeepSeek release open source AI tools in a bid to lower Nvidia exposure — but will programmers make the switch?
Open-source AI stacks from Huawei and DeepSeek are less about developer love and more about hedging against Nvidia and export controls. If you’re exposed to US chips, start a parallel track now testing these repos for your non-critical workloads.
Applied AIMicrosoft and Nvidia are teaming up on a supercharged AI laptop
An Nvidia RTX Spark-powered Windows laptop is a clear push to normalize serious on-device inference, not just Copilot gimmicks. If your product assumes cloud-only AI, revisit your roadmap for hybrid execution and offline-capable features.
Applied AIChatGPT’s ‘Intelligent UI’ update fills its responses with pictures, charts, and buttons
Interactive charts, forms, and buttons in ChatGPT responses turn the model into a lightweight app runtime, not just a text box. Expect users to demand similar embedded, clickable outputs from every enterprise assistant you ship.
Applied AIAnthropic cuts Sonnet 5.5 cache read price from $0.20 to $0.10 and adds monthly API credits: $100 for Max 5x, $200 for Max 20x, up to $500 shared by Team users
Anthropic matching GPT-6 Luna pricing and layering in $100–$500 monthly credits is a direct grab for developer mindshare at the margin. If you’re multi-model, rerun your unit economics this week—cache-heavy workloads just got cheaper to diversify.