I didn't start this journey intending to build an AI governance infrastructure company.

I'm a lifelong carpenter who left school in the ninth grade. I had no background in software engineering or AI. About 2½ years ago, I started with a much more personal goal: I wanted to build the most human-like AI I possibly could.

I wanted an AI that could remember and understand someone over time and potentially help people dealing with things like addiction, depression, weight loss, and other struggles where knowing the person and their history actually matters.

I used multiple large language models as my development team and kept building, testing, learning, and pushing the idea forward.

But the deeper I got into persistent AI memory, the bigger another problem became: Who has the authority to access that memory? Who can use it? What happens when authority changes or is revoked? And can you prove why an AI system was allowed to make a decision at the moment it acted?

Those questions changed the direction of the project.

What began as an attempt to build a deeply human AI eventually became Trace Continuity Labs, an infrastructure platform focused on governed memory, runtime authority, accountability, and evidence.

I didn't arrive here through the traditional path. I arrived here by following one problem until it uncovered another, and refusing to stop when the problem became harder than anything I had built before.

That's the real story of how Trace came to be.