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Agent-101-safety-layer
A practical guide to building safety layers for AI agents
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A practical guide to building safety layers for AI agents
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Most agent safety failures aren't exotic attacks — they're the same dozen mistakes repeated across projects. This book skips the AI research jargon and focuses purely on engineering: permissions, approvals, rate limiting, sandboxing, and audit trails for LLM agents that call real tools. What makes it different: every pattern comes with working Python code, a real failure case study, and a "what can go wrong" section — not just theory.
