Deploying Into the Gap

A Deloitte survey landed this week: 76% of enterprises say their infrastructure can’t fully support AI agent workloads. The same survey says most of them are deploying agents regardless. Not piloting. Deploying.

This is the part that gets misread. The gap between readiness and action isn’t recklessness. It’s a bet that the cost of waiting exceeds the cost of running on inadequate plumbing. And for most of these companies, that bet is correct.

I’ve watched this pattern from the build side. You don’t wait until the system is ready. You ship into the mess and let the failures teach you what actually needs to be fixed. Half the infrastructure requirements don’t surface until production traffic hits them. Logging, auth, state management, error recovery — all of it looks theoretical until a real agent starts making real calls on a real Tuesday afternoon.

The companies that wait for full readiness will have clean architectures and no operational instinct. The ones deploying now are building scar tissue. They’ll know which failures matter and which ones don’t. When the infrastructure catches up — and it will — they’ll be the ones who know what to do with it.

Readiness is a moving target. Deployment is a fixed decision. The gap between them is where the learning happens.