Safer AI agents use structured errors and guardrails

Building safer AI agents requires declarative constraints on tool execution and output screening rather than interpreting model prose. The author argues that tools should raise structured errors with distinct technical and user-facing messages, irreversible actions require a persistent execution ledger to prevent duplicate processing, and untrusted input must be strictly fenced as data to mitigate prompt injection. Open article →