Lingua franca

Natural language may be the shared language of computing, but language isn't shared until the meaning is.

I’ll admit it, I saw “lingua franca” in a Sequoia deck this week and had no idea what it meant.

So I looked it up.

It’s the trade language of the Mediterranean from roughly the 11th century. A pidgin language cobbled together from Italian, Spanish, Arabic, Turkish, Greek, and French. Used by sailors and merchants who needed to do business across borders.

The part that resonates: it was deliberately simplified. Stripped of grammar. Just enough vocabulary to close the deal. Not enough to write poetry or argue philosophy.

Sequoia Capital’s framing is that natural language is becoming the lingua franca or “shared language” of computing through AI.

Whilst this might work for pure computing, it often doesn’t for business or data.

When I say “property” and you say “property,” do we mean the same thing? When my agent says “active deal” and yours does, is that the same status? Probably not.

Many industries are full of this. Real Estate it’s particularly prevalent. Every firm, every department, every team can have its own definitions, its own ontology, its own quiet conventions about what a field actually means. The words look identical. The semantics are not.

LLMs paper over that gap. They sound fluent. They produce confident output. But without a consistent semantic layer underneath, they’re doing exactly what the original lingua franca did, closing simple deals on a thin “pidgin” of context, while the deeper meaning stays trapped in each side’s local deeper context.

The “everyone can finally talk to their data” future has a quieter prerequisite: whose definitions?

Because language isn’t actually shared until the meaning is.

First posted on LinkedIn.