Writing

Notes from
the studio.

Short essays on AI engineering, product strategy, and what's actually moving the needle when teams try to ship AI-native software.

Shipping a demo with an LLM is easy. Shipping something that holds up at production scale, audit, and cost is the actual job.

Most AI projects don't fail because the model is bad. They fail because nobody knew how to measure 'good' before they shipped.

Got a sharper take?

We like good arguments.
Tell us where we're wrong.

If something here lands wrong (or right), tell us. The studio runs on conversations more than broadcasts.