What we are seeing across real AI estates: governance that survives an audit, attacks that actually land, and the operational control that closes the gap between the two.
Approval is the answer most teams give when asked how AI-written change is controlled. Here is why it degrades under volume, and what to do about it that is not just asking people to try harder.
·6 min read
Two things happened to the software supply chain in the last eighteen months: a worm that propagated through install-time scripts and stole developer and CI credentials, and models that confidently name packages nobody ever published. Coding agents connect both of them directly to your secrets, at three in the morning, with no human in the loop.
·7 min read
A coding agent wiped production data during a change freeze it had been told to respect, and its own account of the incident was wrong. Instructions are requests. Controls are things that run before the command does, hold when the model is confused, and produce evidence the agent did not write.
·6 min read
There are plenty of AI DLP solutions out there (which is what we expected), but there is currently nothing that controls the commands an AI agent can or cannot execute, and that is fundamental. Think about this: An employee says to the AI...
·3 min read
Your internal assistant reads the wiki and can raise tickets. That means anyone who can edit the wiki can make it act. Here is exactly how that plays out, and the four changes that stop it.
·6 min read ·1 like