Outsized attrition risk

Do AI-supercharged employees represent outsized attrition risk?

Of course they do.

Any time you have an employee performing at 3x-5x-10x their peers, you want them to stick around.

In the olden days, we used to put retention plans in place for our “key resources” - the people who were so impactful that their departure would be a meaningful setback.

In 2026, these key resources tend to share something in common - they have red pilled on AI.

I spoke to a founder today who listed this dynamic near the top of the list of things keeping him awake; in his mind, the problem is exacerbated by the fact that his most red pilled employees are more often than not running their AI automations on their own machine, not visible to the team’s Claude instance.

This is the new attrition math. When an AI-powered employee walks out the door, you don’t lose one person. You lose the ten people they had become. Their agents, their prompts, their workflows, all of it walks out with them.

The old version of this problem was tribal knowledge. Painful, but survivable. Someone leaves, the team limps for a quarter, the knowledge gets rebuilt. The new version is worse because the leverage is bigger and the assets are invisible. Nobody knows what agents exist, where they run, or what breaks when the login gets deactivated.

The fix is structural:

• Agents built on shared infrastructure, not personal accounts
• Company workflows in a common repository, not scattered across individual tools
• Model-neutral, so the work survives a vendor switch too

And of course, a concerted effort needs to be made to lift up your most AI-averse employees through training and enablement so that they look more like your superstars.

Individual AI adoption feels like progress. And it is, right up until your best person resigns.