Blog
Your AI Agent Had Permission. It Still Did It Wrong.
There’s a conversation happening in every engineering org deploying AI agents right now, and it goes something like this: “How do we make sure the agent can’t do anything it shouldn’t?” Good question. Wrong framing. Access control is a solved problem. You know how to scope credentials, enforce least-privilege, rotate …
California Just Deleted the "AI Did It" Defense
California’s AB 316 eliminates the “autonomous harm” defense in AI liability cases. If your AI agent causes damage, you can’t point at the algorithm—you own what it does. Here’s what that means for your company and how to get ahead of it.
Risk and Progress: It's Complicated
Agentic AI adoption is moving faster than anyone’s ability to fully secure it. But waiting for the perfect solution isn’t a strategy — it’s how you get left behind. The real question isn’t whether to adopt, it’s how to move fast without losing control.
Maybe Don't 1.1: AI Agents Need Guardrails, MCP Isn't Enough
Maybe Don’t v1.1 expands guardrails beyond MCP to shell commands, adds a policy test matrix, defaults to audit-only mode for painless adoption, and generates AI-powered executive reports showing the value your guardrails deliver.
ISO 42001 Compliance for AI Agents
ISO 42001 establishes requirements for AI management systems—risk controls, audit trails, human oversight. Maybe Don’t provides the runtime enforcement layer that ensures your policies actually get enforced when agents take action, preventing catastrophic failures before they happen.
Why Your AI Agents Need Bowling Bumpers Too
AI agents are writing code faster than traditional guardrails can catch problems. Maybe Don’t AI sits between your AI agents and MCP servers, blocking dangerous operations before execution and teaching agents your standards through verbose deny messages—because your codebase isn’t a bowling game and gutter balls cost more than buying the next round.
Your AI Has Zero Scars
Your AI agent has knowledge without wisdom—Maybe Don’t gives it the guardrails that life experience never taught it.
Guiding AI Agents Through Error Messages
AI error messages that guide behavior instead of just blocking it transform agents from rule-followers into intelligent systems that understand your standards.
When AI Agents Go Rogue
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 Running Your AI Strategy
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.