I built 5 Gemini Gems that stop me repeating myself to AI — here’s how to make them
THE SO WHAT
Reusable Gemini Gems are an early proof that users will invest in configuring task-specific agents once and then expect that behavior everywhere. If you’re shipping AI features, assume a future where users bring their own prompts/agents—design for import, sharing, and composition, not one-off chats.
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Anthropic’s “workspace” hypothesis is another step toward mechanistic interpretability—treating models as systems with internal structures you can probe, not just black boxes. For teams betting heavily on LLMs, this is a nudge to start tracking interpretability research alongside capability gains, because future regulation and risk frameworks will likely lean on these concepts.
Applied AIThe AI architecture that let Liberty Mutual shrug off the Fable 5 outage
Liberty Mutual treating Anthropic’s three-week Fable 5 outage as a non-event is the payoff of building an “AI backbone” with model redundancy and orchestration baked in. If you’re standardizing on a single LLM vendor today, this is your cue to design for hot-swapping models and regions before an outage forces the issue.
Applied AIHud CEO Roee Adler says runtime intelligence will define the next era of software operations
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Applied AIClaude Cowork expands to mobile and web
Agentic workflows are moving from “thing you run on a laptop” to ambient background process across devices — Anthropic’s Cowork now follows you from desktop to phone with persistent tasks. If you’re building internal agents, design for long-running, cross-device jobs and notification UX, not just chat-style sessions.