AI doesn't always cut costs — sometimes it inflates them
In the US, AI tools reportedly added $942M in healthcare spending over two years. A reminder: AI saves nothing by magic.
AI transformation
AI, put to work for your product.
How we put artificial intelligence to work: real cases, methods and lessons learned.
When AI gets a rulebook
Microsoft publishes a 'code of conduct' for its models: no hacking, no deceiving, no escaping human control. A useful reminder for the rest of us.
When AI agents meet the real web
New findings that AI agents stumble on CAPTCHAs are a useful reminder: the web is built for humans, and agents inherit all its friction.
Building with AI responsibly when the hype is loud
Between doom warnings and breathless launches, product teams need a calmer, more grounded approach to AI.
Slower, safer models: what it means for your app
As leading labs talk about pacing AI development, product builders should focus on reliability over raw capability.
Agents are becoming apps: designing agent-native products
When an AI agent tops the app charts, it's a signal: agents are a product category, not just a feature.
When AI demand outstrips supply: designing for capacity
Even the biggest providers pause signups under load. Your AI features need a plan for the limits.
Where LLMs still fail — and why knowing matters
Public disputes over what AI can really do are a healthy reminder to design around the limits, not the demos.
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