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Building Defense in Depth for AI Agents: A Five Part Series Traditional workloads and applications tend to fail in predictable ways. A broken API call throws an error; a bad input gets rejected by a schema check. These are natural "safe" defaults when something goes wrong. AI agents are different because their nature is non-deterministic. When something goes wrong, an agent won’t stop or error out. There’s a good chance it will just keep going, taking plausible sounding, but harmful actions, because nothing forced a safe stop.
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