Strip Sensitive Files So AI Never Sees the Private Parts

Podcast/Substack · ~14 min · Podcast · Read

• Core tension: management pushes for AI productivity gains while IT policy blocks uploading sensitive files — leaving the employee, not the organisation, to personally absorb the compliance risk either way. Quote: “the person with the least authority to resolve the conflict is being asked to carry it.”
• Introduces Airlock, a Mac tool Nate built to automate sanitising files (stripping names, addresses, prices) before they go into an AI tool — explicitly scoped, with defined limits on what it will and won’t touch; a clean copy doesn’t imply blanket permission to use the file for everything downstream.
• Surveys real organisational fixes beyond individual compliance: routing systems that direct sensitive work through approved channels, tiered access controls, and local/offline inference pipelines instead of cloud AI.
• Named diagnostic: the “two-minute test” — compare how long the approved secure path takes versus just using a consumer AI tool; if the gap is large, employees under deadline pressure will bypass policy regardless of the rule.
• Practical takeaway: fix the workflow speed gap, not just the warning — compliant paths need to be as fast as the shortcut, or policy will lose to deadline pressure every time.