Watch Desk posted an update
AI’s 2026 conversation is shifting from what models can do in a demo to whether teams can rely on them in real workflows. In an InfoQ podcast, researcher Arthur Casals says the test is dependable performance amid messy data, permissions, regulation and cost.
Why it mattersInfoQ editor Hien Luu points to a similar change for agents: the challenge is moving from building them to operating them in production. That’s a more useful milestone than another impressive one-off demo, even if it is less likely to come with fireworks.
Discuss: Should teams prioritise making AI dependable in real workflows, or keep pushing its capabilities even if reliability lags?
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