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Diverging safety approaches could fragment access and complicate enterprise AI strategy.
Why governance, observability and accountability matter more than reach when enterprises deploy AI agents
We assumed most of the productivity improvement would come from AI writing code faster, but the biggest gains came from getting rid of the handoffs between stages.
Spurred on by an army of enthusiastic consultants with prepackaged solutions, companies forgot that technology should serve business needs, not the other way around.
AI consumption and AI impact are not the same.
Tempo’s new Workforce Intelligence offering ties AI activity and cost to individual Jira work items to measure its contribution alongside that of human labor.
AI makes it too easy to create slide decks, reports, blog posts, and software that nobody cares about and nobody needs. Use it when it matters.
Scale becomes manageable when generative AI is treated as a service with explicit constraints and measurable outcomes. Rely on these production disciplines to get there.
Britain’s new oversight of Microsoft, Google, Amazon, and Oracle shows that hyperscalers are no longer being treated as ordinary IT vendors.
Platform engineering succeeds when treated as a product, reducing developer friction, cognitive load and accelerating software delivery.
