Because your authority is scattered and the machine can’t stitch it into a single entity. You’ve spent years piling up talks, interviews, mentions, and projects. To a human, that makes you a reference. To the AI, they’re loose pieces that don’t always point to the same name, the same topic, or the same person. Without that stitching, the machine won’t risk citing you as an authority.
Why am I well known but the AI doesn’t cite me?
Because being known and being readable aren’t the same. People connect the dots on their own: they know the one from the talk, the one from the interview, and the one from the project is you. The machine doesn’t. And today the recommendation is made by the machine, not by the person who already knew you. If your name shows up in three different forms, your topic under three different labels, and your work spread around without consistency, the AI sees three half-people, not a reference.
What is triangulated presence, and why am I missing it?
It’s showing up consistent and verifiable across several places the machine can cross-check, the recognized authority that makes you citable. You have presence, but not triangulated: you have volume, not consistency. Many loose mentions don’t add up, and sometimes they even confuse. The AI cites by consistent mention frequency, not by how many times you appear.
How do I make the authority I already earned count for the machine?
By consolidating it. You don’t need new achievements, you need the ones you already have to read as a single source. It’s ordering and triangulating what you already built so the machine recognizes it.
That’s being the source the AI cites: so the authority you already earned with people also counts with the machine.
The concrete work of that consolidation is in how do I connect what I’ve already done.