AnyKey Cafe

I had sworn off technology. After decades of working with it, I was tired of spending my life solving one more machine-shaped problem. But I still had a puzzle I could not leave alone, and I was not ready to sit on my butt twiddling my thumbs.

So I walked into artificial intelligence with a question that was, in essence: What is a Flower of Life?

The answers were fascinating. The conversations grew, strange connections appeared, and one question became many. But admiration created a harder problem: I loved the answers, but how could I know whether I should trust them?

Removing obvious flattery and agreement was not enough. Were the patterns I thought I saw really present? Was the AI discovering something, reflecting my expectations, or gradually building a convincing story from material we had already fed each other? A coherent answer can still be wrong—and a beautiful pattern can be one we accidentally drew ourselves.

To find out, I needed more than another opinion. I needed an instrument: a way to trace claims through conversations, detect unsupported leaps, separate observation from interpretation, record corrections and counterexamples, and test whether the same results survive independent examination. That work became the AI conversation anomaly detector, one of the major projects now being developed here.

The detector is not the destination. It is the measuring tool for the larger experiment: if human and AI can accidentally reinforce confusion, can we deliberately structure the relationship to improve correction, clarity, creativity, and judgment instead?

That question has already spawned a practical first experiment. Instead of leaving the AI to infer a person entirely from scattered conversation, we are deliberately developing three separate working records:

The early results have been remarkable. These records appear to help the AI preserve the customer’s intent while still contributing genuine creative judgment. The websites being built through this process are themselves part of the evidence: the AI is producing work that fits the people involved with an accuracy and responsiveness that is difficult to miss.

Upon later review, the AI also judged that these records had materially improved its work. That is encouraging, but it is not independent proof; an AI evaluating its own performance remains part of the system being tested. For now, this is best described as a very promising first experiment—one producing positive, visible results that deserve continued measurement.