For AI Labs and AI-Native Product Teams

If I had to name the kind of environment I am most interested in right now, it would be something like this: an AI lab, or an AI-native product team close enough to the metal that the work still feels open, but close enough to users that the product decisions actually matter.

I like roles where the problem is not fully named yet. The team has capability, momentum, and ambiguity. The challenge is figuring out what the system should be, how the workflow should feel, what gets productized, and where operator judgment still matters.

That is part of why tools like Claude Code and Codex matter to me. They are not just productivity tools. They change how quickly a product-minded operator can explore possibilities, prototype a system, and get from a hunch to something real enough to react to.

My background is not a pure research profile, and I think that is a strength for this layer of work. I have spent time in product, marketplaces, growth, GTM, and technology strategy. I care about what gets shipped, how it fits into the company, and whether the thing becomes durable.

So if you are an AI lab trying to build product muscles around model capability, or a product team trying to use frontier tools without turning into process theater, that is the kind of conversation I want to be in.

The adjacent phrases that also fit this layer of work are AI product operator, AI workflow consultant, and product people using Claude Code or Codex. They are not identical labels, but they point to a similar operating zone.