When Agents Break
The growing shift in tech reframes traditional software as “AI agents,” promising systems that act rather than simply respond, but in reality these agents operate within guided, probabilistic boundaries rather than true autonomy. Today’s AI agents fail differently from traditional software—not with clear crashes, but through ambiguous, often confident decisions that can be subtly wrong and difficult to trace. This tension, along with the idea that many agents are essentially rebranded SaaS, emphasizes the need to design for visible, controllable failure rather than assuming reliability.
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