Michael Carducci: AI Semantic Layer (Critical Infrastructure)

About this event

**Please take a moment to forward this information to co-workers, friends, and social networks. Be sure to register.** **This meetup is co-scheduled with AI Coding & Cloud, Boulder Java Users Group, and Denver Java Users Group.** **See location pictures below.** 5:30-6:00: Food, Soda, and Networking 6:00-6:15: Announcements & Raffles! **6:15-7:30:** **AI Semantic Layer (Critical Infrastructure)** Gartner just named the semantic layer a non-negotiable foundation for AI. Almost nobody in the industry knows what that means yet, or why it should worry them. **Every LLM response is a guess**, not a fact. Most of the time it's close enough that nobody notices. Then it's wrong, and there was no way to see it coming, because the model doesn't know what your data means—the model doesn't know anything. It's always guessing, based on patterns, every time. The guess is right often enough to feel like magic. It will never be right 100% of the time, and can't change that. **It's not a bug waiting on a fix. It's a hole in your architecture.** As one recent paper on the semantic gap puts it: \> “When AI systems enter the picture\, descriptive documentation is insufficient\. LLM\-based interfaces operate directly over data representation\. If meaning is not encoded structurally\, the model infers it probabilistically\.” Your systems are full of structured data (JSON, databases, APIs) that means something to the code that built it and nothing to anything else, including the AI you just pointed at it. A field called status: 3 means nothing outside your system. Multiply that by every field, every service, every team, and you get an enterprise fluent in nothing but itself. That's the wall every serious AI initiative eventually hits, and it's why so many AI initiatives are underdelivering. The fix isn't a bigger model or a new platform. It's a set of open standards that have quietly run major parts of the web for decades, built for making data mean something on its own,…