Your AI Agent Just Deleted Something It Shouldn't Have. Here's How to Prevent It.

You gave your agent access to the filesystem. It was supposed to clean up temp files. Instead, it deleted something important. Or maybe it called an external API with production credentials when you only meant to test it. Or executed a shell command that made sense in isolation but was catastrophic in context. These aren't hypotheticals. They're the kinds of failures that happen when we give agents power without governance. Today I want to show you a small library I built to solve exactly this: Canopy Runtime — a minimal agent safety runtime that adds ALLOW / DENY / REQUIRE_APPROVAL decisions to any action your agent wants to take, with a tamper-evident audit trail. The Core Problem When you build an autonomous agent, you typically think about: What model to use What tools to give it What the system prompt should say What most developers don't think about until it's too late: What happens when the agent does something it's allowed to do... but shouldn't? The model isn't broken. The too