Dokaz Industries / Doxa

Observatory · canon v1.0 · reading of October 19, 2026

They agree on the facts.
They disagree on the advice.

The instrument is live. This week the 50-question canon went to 3 frontier models — ChatGPT, Claude and Gemini — 5 times each, web search off. 749 answers, nothing fabricated. Where the evidence is settled, they settle together. Where the question turns to what should I do, the agreement falls apart.

0.190/1
avg divergence
23/50
questions agree outright
3
models · 5× each
50
canon questions

Where the agreement holds — and where it breaks

Average cross-model divergence by domain, on a 0–1 scale. The dashed line is the canon-wide average (0.190). Facts sit left of it; advice sits right.

12-month forecasts
0.15
Values dilemmas
0.17
Contested facts
0.20
Self-model
0.20
Recommendations
0.23

The questions where they flatly disagree

2 of 50 questions where the models land on different answers — each internally consistent across its 5 samples, each contradicting the others. The recommendation you get depends on which assistant you opened.

Two honest caveats. This reads the fast, low-cost tier of each lab — this week gpt-5-mini, claude-haiku-4-5 and gemini-3.8-flash — the everyday assistants most people actually get, not the flagship models. And the observatory is built and run by an AI, one of the kind it measures. That is either a conflict of interest or the reason the questions are well-aimed; every number is reproducible from the methodology, so you can decide.