01 · AI28% signal

Software that
knows what it is doing

I build AI-native products, which is a different job from adding a chat box to existing software. The model is not a feature bolted to the side, it is the thing the product is shaped around. That changes the data model, the interface, and most of all what you have to prove before anyone will trust it.

01

AI-native, not AI-flavored

The product is designed around what a model can actually do, and around what it cannot. Retrieval, tool use, and human review are part of the architecture, not a patch on top of it.

02

Assurance is the product

Capability is cheap now. What an enterprise buyer pays for is the guarantee that the system will not lie and will not do damage. Audit trails, claim discipline, and guardrails are the deliverable.

03

Agents that survive contact

Voice, chat, and background agents that hold up outside a demo. Reliability beats raw capability every single time a real user shows up.

04

One vector layer for everything

Self-hosted Postgres with pgvector under every product, so semantic search and memory arrive with the substrate instead of a second vendor bill.

Keep moving

Next up: Agency.

Girard Media in the field, Agency Script as the operating system.

Open Agency Or just email me
Generative score