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Agent-101-safety-layer
A practical guide to building safety layers for AI agents
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.
Hey Product Hunt! 👋
I built this after noticing the same pattern everywhere: developers give an LLM agent tool access (send email, run shell, delete files), it works great in the demo, and then someone asks "wait, what stops it from doing something we didn't want?"
There wasn't a simple, code-first resource that answered that question without diving into AI research theory — so I wrote one myself while learning it hands-on.
The book covers permissions, approvals, rate limiting, sandboxing, and audit trails — with real Python code you can drop into a project, not just concepts.
Would love feedback from anyone building agents right now — what safety problems are you running into?
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About Agent-101-safety-layer on Product Hunt
“A practical guide to building safety layers for AI agents”
Agent-101-safety-layer was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #32 on the daily leaderboard. 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.
Agent-101-safety-layer was featured in Developer Tools (517.6k followers), Artificial Intelligence (476.1k followers) and Books (122.6k followers) on Product Hunt. Together, these topics include over 206.3k products, making this a competitive space to launch in.
Who hunted Agent-101-safety-layer?
Agent-101-safety-layer was hunted by kr1shna. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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