Every silo is its own context
Dave McComb has been building enterprise systems for fifty years and running Semantic Arts for twenty-five. His rule of thumb is one application for every ten employees, so a hundred-thousand-person company is running ten thousand databases that each name, structure and identify everything differently. That is also his answer to the age of context: the problem was never a shortage of it, it is that every silo has its own. Along the way he explains why an LLM will hand you an ontology that opens cleanly in Protégé and looks like exactly what you asked for, why that is the trap rather than the win, and what he found when he put semantic lenses back on his own accounting system after twenty years of not looking at it.
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Dave McComb
Author of The Data-Centric Revolution, Software Wasteland and Semantics in Business Systems, and originator of gist, the minimalist open-source upper ontology now in its fifteenth version after two decades and more than a hundred data-centric projects. He started at Arthur Andersen building enterprise information systems in the 1970s, co-founded Velocity Healthcare where he patented the first fully model-driven architecture, and founded Semantic Arts in 2000. Its clients have included Procter & Gamble, Goldman Sachs, Schneider Electric, LexisNexis, Dun & Bradstreet and Morgan Stanley.
What we'll cover
- 01Fifty years from Arthur Andersen to Semantic Arts, including the part where the dot-com bubble took the investment bankers away overnight and left the patents behind.
- 02One application per ten employees: the rule of thumb that means a hundred-thousand-person company is running ten thousand databases that all name everything differently.
- 03"It's not that there's no context. There's way too many." Every silo is its own context.
- 04How he defines an ontology, and why a formal definition a machine and a human both agree on is the whole point, worked through two different valid definitions of "customer" inside one bank.
- 05The three traps of letting an LLM build your ontology: it learned from bad examples, it inherits your local schema's assumptions, and productivity gains push you the wrong direction.
- 06Why a large enterprise genuinely runs on a few hundred concepts, and why nobody can hold a million of them.
- 07Ford made 1.9 million vehicles in 1924 and 2 million in 2024, on paper and pencil the first time. Eight percent growth per century, and what that says about essential complexity.
- 08The data-centric strangler fig: lift data into the graph, move use cases over one at a time, switch the legacy system off when there is nothing left.
- 09Rebuilding accounting from the ground up on a graph, why commitments and fulfilment turn out to be the model, and the book that came out of it.
- 10A tour of gist's periodic table, and the client who listened to the Sherpa pitch and said they would rather have a helicopter.
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