Every decision is an ignition. From a field of possibility, one path commits to action, and a cascade unfolds. The biggest such ignition created the universe. The smallest commits an individual to a single act. The structure of the moment is the same at every scale. Four forces meeting multiplicatively. If any one approaches zero, the ignition fails. No action, no cascade.
Zurich, 2019. A whiteboard inside a crypto infrastructure firm, four years before any large language model went public. The same four forces kept appearing in every investor decision that mattered. They did not add. They multiplied. When any one of them dropped toward zero, the decision did not weaken. It collapsed. That collapse was the test. The claim was falsifiable, and it survived every attempt to break it. The four forces are now IADT, the Integrated Action-Driver Theory. The cascade by which IADT decisions aggregate into institutional outcomes is UCT, the Unified Cascade Theory. The cross-scale identity that lets the pattern carry across substrates is ISP, the Identical Scale Principle. The Three Laws of Decision-Making.
Foundational is where the laws are built and held to account. Each is stated in canonical form. The empirical record is curated and made public. The work is submitted to adversarial review, paper by paper, on the assumption that anything that survives the review has earned its place. The universal in three universal laws is not asserted by formal derivation. It is earned by cross-substrate replication, one substrate at a time. Human Decision-Making applies the laws back to the substrate where they were first observed. Six contexts where the empirical record runs deepest, where the multiplicative form meets actual consequence. Investor decisions. Voter decisions. Consumer choices. Healthcare choices under pressure. Educational choices. Workplace choices that shape careers.
Two further programs open in 2026. Agentic AI carries the laws into the artificial substrate, where machine learning's additive consensus meets its multiplicative correction at the moment AI governance is intensifying worldwide. Hard Problems carries the laws into the physical substrate, where long-standing unresolved questions in physics become tractable under the multiplicative cascade reading. Quantum measurement is the deepest empirical reach the research has attempted. The structure is being tested where physics has been stuck for a century.
The first program states the architecture and demonstrates the laws that govern it. The second tests those laws against the empirical record of human decision-making. Together they establish the studio's canonical core and its first empirical substantiation. Further programs are in active preparation.
The three laws at the micro, macro, and meta scales, derived and stated formally. Plus the empirical evidence that the multiplicative architecture holds across biological, artificial, and hybrid substrates. Every paper in every other program traces its structural claims back to this canonical core.
The laws tested against the empirical record from every sector, industry, and discipline where humans make decisions. From financial risk to clinical judgement to educational selection to electoral behaviour, the same multiplicative architecture governs the outcome. Every test in the program substantiates the structural finding the foundational program advanced.
Patrick Mehrhoff is a German entrepreneur, independent researcher, AI engineer, and author. He is the author of the three original theories that constitute the Mehrhoff Research Program. He built the work the studio carries.
Most practitioners spend a career inside one domain. He worked as a practitioner at six of the frontiers that redefined how society organises information, money, and value over the last two decades. The consumer internet, Swiss fintech, European monetary policy, Southeast Asian financial publishing, institutional crypto assets, and the first wave of applied AI.
The same structural observation appeared at every frontier. By 2019, on a whiteboard at crypto infrastructure provider Wyden in Zurich, the pattern had become visible to itself. It did not yet have a name. Four years before any AI language model became publicly available, the complete logic of the Three Laws of Decision-Making was already on the whiteboard.
The studio was built from Bangkok, without institutional affiliation and without external funding. The Rubens workshop model defines how it operates. The founder sets the intellectual direction at every decisive step. The tools and collaborators execute within it.
Decision outcomes are governed by structural forces, not by stable attributes. The same multiplicative logic recurs at three scales and across domains.
Action under complexity is determined by the dynamic interaction of four forces. The interaction itself is the mechanism. Additive models systematically under-perform because they cannot represent it.
How individual decisions aggregate into institutional outcomes through three sequential phases. Ignition. Polarisation. Institutionalisation.
A criterion for when a structural pattern recurs across scales and domains. The pattern transfers only where structural identity holds.
Tested against nine foundational scholars, three of them Nobel laureates, and across fifteen structural dimensions. Every cell is independently challengeable.
Every dimension independently challengeable.
Most frequently cited as predecessors.
Among the nine scholars tested.
Confirmed across all nine scholars.
The three laws describe the same multiplicative structure that governs decisions across scales. What each audience recognises in them is different. Each doorway below opens into the same set of laws, framed for the way you are most likely to find your own work inside them.
The literature in your field has been reporting tail-failure for decades. Outliers, noise, model misspecification. The three laws name a different culprit. The structural form of the model itself. Read the laws and find the place where the assumption you never questioned has been doing the work all along.
Every senior decision-maker has watched a model work on average and break where the decision mattered. The three laws name what is happening. The breakage is not an edge case the model failed to anticipate. It is the multiplicative architecture finding its zero. Read the laws and the pattern beneath every model break of your career becomes legible at once.
Each major institutional cascade of the past fifteen years was investigated as if it were unique. The reports document different operational failures in different sectors. The three laws read across the reports and recognise one structural pattern. Read the laws and the recurrence stops looking like coincidence.
Every philosophical tradition that has tried to describe the world has eventually arrived at the same conclusion. The three laws turn the conclusion into a working structural explanation. Decisions form. They cascade. Their patterns transfer across scales. Read the laws the way our studio reads them.
Most foundational research is finished before a student arrives. The three laws sit early enough in their life that the field around them is still to being created. A graduate student who reads them now enters a body of work inside its formative window. The reading path is curated for entry from any quantitative or social-science background.
Universities train within additive frameworks. Journals review within them. Regulators write rules under them. Funders evaluate against them. The three laws name the structural assumption beneath the entire foundational layer. It has been invisible because no curriculum, no review, no framework has ever required it to be examined. Read the corpus and the link your institution has been operating without becomes legible.
The first sketch of the Three Universal Laws. Drawn four years before any AI language model became publicly available.
Sketched at an office in Zurich. The board maps the direction of the markets, the forces driving them, the audiences they affected, the problems those audiences encountered, and the responses the market was developing. The structural logic that became the First, Second, and Third Laws is already on the board, in the language of practice.
Mehrhoff Research operates outside academia and outside industry. An independent science and research studio with no external funding, no board, and no university partnership. Founded 2019 in Zurich, domiciled in Tallinn, run from Bangkok.
The work is published open access. Every paper passes adversarial peer review before deposit. Every claim names the empirical conditions under which it would be falsified. Every citation traces to a primary source. The standard is not the institution. The standard is the work.
Deposited on Zenodo, permanently archived.
Data points analysed across all empirical validations.
Foundational and human decision-making.
No paywall, no journal embargo.
A horizon decades away. The daily practice of moving toward it. Seven principles the studio holds itself to, with or without anyone looking. Five codes the studio answers to when no external authority requires them. Each statement enforced internally. Each verifiable from outside.
Vision and mission, stated directly. What the studio is working toward, and what it does today.
Seven standards held against every paper, every conversation, every relationship the studio enters. Decision-making, rigour, independence, transparency, originality, curiosity, and courage.
Self-regulated science. Published standards, open methods, full results regardless of what they show.
Press, academic peers, conference organisers, policy bodies, industry practitioners, and readers reach the studio here.
Six formats, from public keynote to closed doctoral seminar. The full range is welcome; the substance of the questions decides the invitation.
Four positions, from visiting researcher to fellowship, with two scheduled per calendar year. A residency produces sharper work than a single talk because the conversation extends.
Press kit with bios, headshots, and topic briefs is ready to download. Lectures, learning materials, and the architecture itself are licensable.