Mitchell Hashimoto's AI Adoption Journey

Mitchell Hashimoto has built more developer infrastructure than most people will write in a career — Vagrant, Terraform, Packer, Vault. When someone with that background writes honestly about how AI tools have changed how they work, I pay attention.

The post isn't a conversion story. It's not "AI changed everything and now I'm 10x more productive." It's more careful than that, and more interesting because of it.

The honest middle ground

What Hashimoto describes is a gradual shift in where he reaches for AI assistance, and an evolving sense of which tasks benefit and which don't. Early on: skepticism and limited use. Later: more integration, but with a clear sense of where his judgment still has to do the work.

This maps to my own experience. The tools are genuinely useful for a specific category of tasks — anything that's well-defined, where the output can be verified quickly, and where the bottleneck is typing rather than thinking. For everything else, the model might speed you up or it might send you sideways.

What I took from it

The most valuable thing in the post isn't a specific workflow or tool recommendation. It's the posture: someone with strong opinions and deep expertise taking the technology seriously enough to keep revising their view as they use it.

That's the right way to engage with tools that are still changing fast. Not "this is great" or "this is overhyped" — but "here's what I thought six months ago, here's what I think now, and here's why."