On May 1, 2026, Bloomberg Television’s Wall Street Week aired a segment on how AI-assisted development is changing the way businesses work. The story featured a few very different examples. One of them was a warehouse in rural West Virginia.
That part was us, but the story matters because it is bigger than us.
Innovation does not only happen in large cities, venture-backed startups, or companies that call themselves technology firms. It can happen in Pendleton County, West Virginia when the people closest to the work have the tools to build what the work actually needs.
What Bloomberg Covered
The segment, reported by Ed Ludlow, explored the rise of “vibe coding” - using AI tools to build software through plain-language conversation rather than traditional programming. Bloomberg came to Upper Tract to see what that looks like when the person building the tools also runs the operation those tools are meant to support.
Bloomberg also published a dedicated cut of the segment under the title “Why Vibe Coding Isn’t the End of the Software Engineer,” which gives this story a cleaner standalone home outside the full episode.
Wall Street Week, Bloomberg Television - May 1, 2026. Our segment begins at 11:05.
The introduction set the scene:
“In Upper Tract, West Virginia, Jamie Grove owns a boutique warehouse helping clients ship out anything from dinosaur bones to board games. Last year, he built software that automates shipping out packages with help from AI.”
That is a fair description of the surface story. The more important point is what those tools do for clients.
What This Means for Clients
Bloomberg’s interest was practical: what did we actually build, and why does it matter?
We walked them through several kinds of systems we have built with AI helping us move faster:
Custom warehousing software. Order batching, inventory tools, receiving workflows, shipping automation, and other systems that fit the actual warehouse instead of forcing the warehouse to contort itself around generic software.
Business intelligence. Reporting, dashboards, and operational analysis that turn warehouse activity into decisions. That might mean understanding fulfillment velocity, identifying friction in a process, or helping a client see what is happening clearly enough to plan the next move with confidence.
Client-specific workflow design. Different clients need different things. Some need exact inventory reconciliation. Some need better shipping logic. Some need clearer reporting around sales events, launches, or convention activity. We build around the real problem instead of pretending every client has the same one.
That is the value of this approach. Our clients are not paying for software theater. They are getting tools that make their operation clearer, faster, and more dependable.
From the interview
“There’s absolutely no way I could have done any of this without AI. Even someone who is a very fast coder could not have built all these solutions. Impossible. If I were to do it with a team of programmers, I could have five programmers working on this full-time and still not deliver as many results.”
AI Is Powerful Because The Expertise Comes First
The key point is not that AI makes magic software appear out of nowhere. It does not.
AI is useful here because we already understand fulfillment, inventory movement, shipping exceptions, warehouse edge cases, and the practical consequences of bad tooling. We know what good looks like on the floor. We know where a process is wasting time. We know when a report is technically correct but operationally useless.
That is why AI feels like a superpower to us. It multiplies existing operational knowledge. It shortens the path from idea to working system. It lets a small team build and refine tools quickly because the people guiding the work already know what the work requires.
It is still human judgment. It is still warehouse knowledge. It is still experience. AI just lets that experience move faster.
Why Bloomberg Came Here
Bloomberg did not come to Upper Tract because we are trying to become a software company. They came because we are not one.
We are a fulfillment warehouse in Pendleton County, West Virginia. We handle unusual products, demanding workflows, international shipments, trade-show logistics, and high-stakes client moments. The reason the segment resonated is simple: it showed that practical innovation can emerge from a place like this, from people doing this kind of work, far from the usual map of where “technology” is supposed to happen.
That matters to us, and it should matter to clients too. When software, reporting, and process design are being shaped by people inside the operation, the result is usually better than what comes from a distant template.
The Part Bloomberg Could Only Touch Briefly
The television segment focused on a few visible examples, but the pattern is broader than that.
We use the same approach across warehouse operations and analytics work:
- Build tools that fit the client, not just the category
- Use business intelligence to turn activity into decisions
- Keep workflows adaptable as products, channels, and events change
- Let AI accelerate implementation without replacing judgment
That is true whether the problem is batching orders, reconciling inventory, preparing for a convention, understanding fulfillment velocity, or making sense of messy operational data.
We are not interested in building software for its own sake. We are interested in solving the actual problem in front of us.
Watch the full segment
Bloomberg published a dedicated video cut of this story here: Watch the Bloomberg video. The full Wall Street Week episode is also available on YouTube, where our segment begins at the 11:05 mark and returns for a deeper dive around 18:31: Watch the full episode here.