This is real output, not a summary of it — an analysis of OpenAI built only from public sources, broken out so you can see what arrives at each price. Every claim carries a dated citation, so you can disagree with a specific step rather than the conclusion.
What the free scan returns: the pattern named in one phrase, and the public signals it rests on.
A nonprofit that discovered its own mission was paradoxical — to ensure AGI is safe, you must build it first; to build it first, you must race. The organization did not abandon its values. It ran directly into their internal contradiction.
$99 — step 3 analyses the pattern the free scan named: what drives it, what it protects, and what it will repeat. It is general, and the same for everyone who buys it. $499 — step 4 turns that analysis into insight, adding the strength, the blind spot, and the questions a board should be able to answer — read through the function you choose, or general. Additional functions are $149 each on the same organization.
The organization holds a structural belief: that its stated mission provides cover for whatever the mission requires. An employee who questions the pace is not questioning a business decision — they are questioning whether safety matters. That framing forecloses internal challenge. The people most committed to founding values become the ones most likely to leave; the people most committed to winning stay.
No internal data, no interviews, no access to management. This analysis is drawn entirely from the public record. It reads a pattern, not people — no individual is assessed, named, or characterised. It is interpretation with its evidence disclosed, not a finding of fact.
Put a pattern like the one above beside a careful, consensus-run acquirer and the friction is not a personality problem to manage after close. It is structural, readable in advance, and it has a price that belongs in the model.
Nothing in the method assumes a large company — it assumes a public record, and a global manufacturer, an independent school, a member club and a family business all have one. These are organizations CultureLogic has actually read, most of them to test the method against sectors that look nothing like each other.
Boeing, Starbucks, Volkswagen, Patagonia, OpenAI. Global footprint, decades of record, and the most public evidence of all — which makes them the hardest test of whether a reading says anything a journalist could not.
Pacifica Graduate Institute, and OpenAI in its nonprofit years. Mission-led organizations leave an unusually rich record — the gap between a stated mission and the behavioural one is the sharpest signal this method reads.
Hawaiʻi Preparatory Academy, Pacifica Graduate Institute. Schools carry a public record built from accreditation, governance, hiring and the accounts of families — and their culture decides retention of staff and students alike.
Mid Pacific Country Club. A membership organization's culture is its product, and generational change inside one is visible from outside long before it is named inside.
Also read: a regional utility, a residential brokerage, a bank, a landholding company and an owner-operated manufacturer. Except where a section below says otherwise, these are analyses run for internal validation — not a client list. The point is that the method did not need any of them to agree to be read.
A CultureLogic analysis of Mid Pacific Country Club found an organization already becoming something new — it just hadn't named it yet. The public signals showed a membership organization in a generational transition: newer members bringing different expectations around value and purpose, institutional identity resting on traditions fewer members share. The analysis gave them language for what they already knew was shifting.
"On a re-read of Hawaiʻi Preparatory Academy with expanded sources, the original analysis's central image survived, but five of its inferences did not."
The expanded pass found the internal culture may run opposite to what external signal suggested, governance far more locally rooted than first credited, and financial aid structurally present where the original had read exclusion. A method that cannot be shown to be wrong cannot be shown to be right — the comparison is the artifact that separates an analysis from an opinion.