Tag archive
A practical guide to deploying AI agents safely: input validation, permission scoping, human approval, rate limiting, and rollback strategies.
Turn a new teen-AI safety discussion into an annotated design pattern with age-appropriate recovery, privacy, and research stop conditions.
test body content long enough to be valid for the dev to api endpoint here.
A practical guide to production AI agent safety: sandboxed execution, human-in-the-loop gates, idempotent actions, and rollback strategies.
Introduction The question of whether for loops should return values directly, akin to...
Introduction: Navigating the Roll Cage Installation Maze in South Florida Finding a...
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Building an evidence-first location and date risk checker while keeping AI interpretation carefully bounded.
Introduction: The Shift from Racing to Karting The allure of car racing—the speed, the...
Agentic AI for High-Stakes Incident Response: Lessons from Aerospace Failures You can't...
The human-in-the-loop pattern pauses an agent at a checkpoint so a person can approve high-stakes actions. When to use it and what it costs to build.
When people think about disinfecting a surface, they often think about the product first. What is in...