When AI Agents Go Rogue

Your engineering team just got a Slack alert. The AI agent you deployed last week to “optimize operations” just deleted your production database. Or maybe it bulk-ordered 2,000 pounds of beef because it misinterpreted “meet the team for lunch.”

Sounds absurd, but it’s happening.

The Guardrail Gap

Anthropic, OpenAI, and Google are racing to build safety features into their AI models. They’re doing important work preventing harmful content, reducing bias, and limiting dangerous outputs.

But here’s what they’re not doing: building guardrails specific to your business needs, your data structures, your operational constraints, or your compliance requirements.

Generic safety measures can’t know that your AI agent shouldn’t have write access to production during business hours. They don’t understand that “optimize storage” shouldn’t mean deleting last quarter’s financial records. They can’t anticipate that your procurement system has spending limits that AI requests need to respect.

Why Agents Fail (And Will Keep Failing)

AI agents are getting more capable and more autonomous. They’re also getting more confident—sometimes dangerously so. They’ll execute actions with the same certainty whether they’re 99% correct or 60% correct.

Humans fail in unexpected ways despite decades of training and institutional knowledge. AI agents are teenagers (toddlers?) with root access. They’ll continue shocking us with creative new failure modes we never imagined.

The difference? Human employees usually pause before irreversible actions. They also feel shame and change their behavior as they learn from their mistakes. AI agents don’t hesitate unless you make them, and they aren’t learning from embarrassing mistakes.

You Need Guardrails You Control

This is where Maybe Don’t, AI comes in. Think of it as a policy layer that sits between your AI agents and your systems—a real-time checkpoint that evaluates every action against your rules before execution.

Want to prevent database changes via AI? Configure it. Need spending limits on AI-initiated purchases? Set them. Require human review for any code changes touching authentication? Done.

The power isn’t in the AI itself—it’s in the control framework you wrap around it.

The Bottom Line

AI agents will save your team countless hours and unlock new capabilities. But without custom guardrails, you’re one hallucination away from an expensive disaster.

Don’t wait for the 2,000-pound beef delivery to arrive.

Set up your AI policies with Maybe Don’t, AI before your next agent deployment. Because the best time to build guardrails is before you need them.