Maybe Don’t AI provides custom guardrails that catch dangerous AI agent actions before they execute—because generic AI safety features don’t understand your specific business logic, and waiting until an agent deletes your database or orders 2,000 lbs of beef is too late.
MCP is the protocol connecting AI agents to your systems right now, and it has zero built-in security for the chaos agents create—get guardrails before you need them.
A practical implementation of Asimov’s Three Laws as real-time AI guardrails, proving science fiction ethics can be guidelines for real AI safety systems today.
Amazon Bedrock guardrails secure model training. Maybe Don’t AI governs what AI does—intervening on risky actions at runtime, not just risky thoughts at build time.
Maybe Don’t provides customizable, third-party AI validation to ensure AI actions are safe, ethical, and aligned with user needs, addressing the shortcomings of traditional security frameworks.
General Analysis recommends filtering inputs to MCP-based assistants to prevent prompt injection—looking for patterns like imperative verbs and SQL fragments. Maybe Don’t AI already does this. Instead of building your own wrapper, plug in Maybe Don’t today and secure your assistant input layer instantly.
When Agents Go Rogue, You Need a Failsafe—A Gateway
In today’s world, AI agents are increasingly being given tools to act—to make decisions, move data, spin infrastructure, write code, issue commands. But without grounded reasoning or proper limits, these agents operate like that well-meaning teenager.