Dalton McBee

I get complex systems from the demo into the field.

Eight years deploying pharmacy robotics and vision systems inside hospitals, government sites, and regulated pharmacies — the places where "it worked in the lab" isn't good enough. Now applying the same discipline to AI systems.

Case studies

Work from the last hundred feet

Three stories about what it takes to make technology hold up in the environments it was actually built for.

About

The last hundred feet

I started as a field service engineer, installing and repairing pharmacy automation alone at hospitals and government facilities. Years of that teaches you something no roadmap can: the distance between a system that works and a system that works here — in this building, on this network, under these regulations, maintained by these people — is where most technology quietly fails.

Today I work in R&D as a technical product analyst across four hardware-software product lines, carrying that field knowledge into architecture and product decisions. On my own time I build and operate AI agent systems, data pipelines, and the occasional piece of hardware — because the deployment problem in AI right now looks exactly like the one I've spent my career solving.

Kansas City. CSPO. Builder of second brains, 3D prints, and one very opinionated disc golf app.

Contact

Find me

The best place to follow my thinking is LinkedIn, where I write about deployment, product, and applied AI. Code lives on GitHub.