the next disruption is not a better technology. it is a different value system.
A technology can work long before its value reaches broad use. dizrupt develops transition propositions, assembles initiators around them, tests them through missions and commonises what survives.
from.the.signals
latest from the signals.
All signals →Short posts on what is moving, published by beta.engine. Each one names its source.
from.the.commons
latest from the Commons.
Open the Commons →the.system
four parts that work as one.
The manifesto says what needs to change. The Collective brings the people. A mission does the work. The Commons keep what was learned, so the next mission starts further ahead.
The manifesto is our argument. It explains why a technology that already works can take years to reach the people it could help, and how that wait can be shortened.
It names six shifts in how organisations decide, reward, measure, organise, share and move. For each one it gives the usual blocker, a rule to design by and a first move that any actor can make.
Most of what delays a working technology sits outside any single organisation, so nobody can fix it alone. The manifesto gives everyone the same model to work from, and it says what would prove that model wrong.
The Collective is the group of people who do the work. People join because of what they contribute and because peers confirm it. Status, a fee or a well-known employer gets nobody in.
Members meet in Roundtables, where peers in the same role often find that they are stuck on the same blocker. When a mission starts, members take a role in it, bring what only a few can bring, and check each other’s claims.
A transition takes more than one actor. Someone has to move first, others have to fill the roles around them, and someone with no stake has to test the result. Seats in Roundtables and recommendations are not for sale.
A mission is a direction: the change an actor has named and wants to work towards. Each mission is pursued through one small build, with a claim that can be proven wrong.
singular.alpha is the method. In five steps it names what is stuck, finds who moves first, reuses what others can already supply, proves the claim with someone outside, and publishes what was learned. singular.state measures where an organisation stands before and after, so that everyone can see what moved.
One actor can start a transition, but alone the first move fades. A mission gives others something specific to join, at a scale where being wrong is affordable.
The Commons are the shared library. They hold the evidence, the methods and the components that came out of the work, published so that nobody has to build them again.
The next build starts from what the last one learned, failures included. Each turn should cost less than the one before.
Knowledge that stays inside one organisation has to be paid for again by everyone else. Sharing it early is how one actor’s progress becomes the next actor’s starting point, under governance that no single actor controls.
disruption.manifesto
It asks how the value reaches people sooner, whichever route prevails.
the next disruption is not a better technology. it is a different value system.
A new technology typically reaches people by one of two routes, or a blend of them: incumbents absorb it, or newcomers displace them. Its existence delivers no value. Use does, and early use delivers only part of it.
Where products depend on shared standards or on other users, an unresolved contest between the routes can delay broad use for years. Our proposition is that it can be shortened. One actor, the initiator, changes its own payoff logic and builds an inclusive ecosystem on shared, contestable infrastructure through which joining becomes progressively cheaper than resisting. The flywheel is the reinforcing mechanism that follows. Incumbents and newcomers tend to meet the same six shifts on the way, and each actor that makes them lowers the cost for the next.
That is what this manifesto is about. It does not pick a route. It asks how the value reaches people sooner, whichever route prevails.
Innovation labs, hackathons and transformation roadmaps cannot change the outcome if they leave the underlying incentives untouched.
For builders, investors and institutions prepared to go first.
ecosystem-value-first. initiator-led. open-by-design.
how.this.manifesto.is.built
Five parts, each answering one question. Each answer raises the next.
Four established findings. 02six.shiftsWhat tends to need changing?Our model. Each shift rests on a known mechanism; the grouping into six is ours. 03the.initiatorWho starts, and why would they?Our proposition. 04the.flywheelHow does it keep going?Our proposition, and the part most in need of testing. 05what.if.notWhat would make us revise the model?open question
Open. The findings that would count against it.
- established
- Others have shown it. The source is named.
- open question
- Not yet answered, by us or by anyone we can name.
- no mark
- Our own claim. Untested unless the text says otherwise.
Most of the mechanisms here are established. Rogers described how innovations spread through a population over time. March showed why organisations favour exploiting what they know over exploring what they do not, and Christensen why incumbents’ own incentives hold them back. Cohen and Levinthal showed that firms can only use outside knowledge they are equipped to absorb. Edmondson showed that people raise problems only where it is safe to, and Arkes and Blumer that people keep investing in what they have already paid for.
O’Reilly and Tushman described why exploring and exploiting need separate structures, Chesbrough how useful knowledge crosses company boundaries, and Ostrom how shared resources can be governed without a single owner. Farrell and Klemperer set out how switching costs and network effects lock markets in, Stigler how regulators come to serve the regulated, and Wasserman how rarely founders stay in control.
sources named in the manifesto (12)
- Rogers
- how innovations spread through a population over time
- March
- why organisations favour exploiting what they know over exploring what they do not
- Christensen
- why incumbents’ own incentives hold them back
- Cohen and Levinthal
- that firms can only use outside knowledge they are equipped to absorb
- Edmondson
- that people raise problems only where it is safe to
- Arkes and Blumer
- that people keep investing in what they have already paid for
- O’Reilly and Tushman
- why exploring and exploiting need separate structures
- Chesbrough
- how useful knowledge crosses company boundaries
- Ostrom
- how shared resources can be governed without a single owner
- Farrell and Klemperer
- how switching costs and network effects lock markets in
- Stigler
- how regulators come to serve the regulated
- Wasserman
- how rarely founders stay in control
Four things are our own proposal and still need testing: that the recurring blockers group into six shifts; that incumbents and newcomers largely share them; that a transition can start with one actor changing its own payoff logic; and that a four-stage flywheel can make joining cheaper than resisting. We state them as propositions.
Two words carry the argument. An actor is anyone in the system: a person, a company, a fund, a regulator, a community. The initiator is the actor that changes what it optimises for and moves first.
four.premises
Why does the value arrive late?
established Four established findings.
There are two archetypal routes.
In adoption, incumbents absorb a technology into the existing market structure. In disruption, newcomers displace that structure. From here on the word means this second route only; the headline uses it in its everyday sense. Most real transitions are hybrids, in which incumbents absorb some of the technology, newcomers take part of the market, and in some fields both advance side by side. The contest is over which route dominates, and on whose terms. This manifesto takes no side in it.
Existence delivers no value. Use does.
The internet, the touchscreen and the neural network each existed for years before their value was unlocked. Invention creates an option and use exercises it. Early users capture part of the value. Most of the rest arrives when use becomes broad. In markets with strong network effects or incompatible standards, unresolved competition can delay that.
A long contest is costly for most of those involved.
While the routes compete, buyers wait, suppliers hedge, and capital and effort go into the side that loses. Not every contest is wasted: a short one can reveal the better design, and settling too early can lock in a worse one. The waste begins when continued competition teaches less than it costs in duplication, incompatibility and delay.
These costs are highest where products depend on shared standards or on other users, the markets economists describe in terms of network effects and switching costs. Where several solutions can coexist, the contest is cheap and this manifesto has little to add.
The same things hold both routes back.
Once a technology works, most of what delays its use sits outside whichever actor carries it: adopters’ switching costs, missing complements, standards nobody will adopt alone. These bind incumbents and newcomers alike. Inside the organisation the biases are human, and newcomers that grow take on incumbents’ inertia.
A contest of this kind tends to end in one of three ways. One side wins outright, often with a system it controls. A regulator mandates an answer, which is quick but can fix the wrong one. Or the parties converge on infrastructure that none of them controls. Our central proposition is that an actor can bring about the third ending deliberately, and that it is the faster one whenever joining costs a participant less than continuing to resist.
six.shifts
What tends to need changing?
Our model. Each shift rests on a known mechanism; the grouping into six is ours.
Every organisation has a value system: a working set of beliefs about what is worth doing, what gets rewarded and what counts as success. Most are well tuned to defend the existing business, because that is what they were built to do.
The six shifts are our model of where such value systems most often need to change. Each has four parts: a default setting inside an actor, the blockers it tends to produce, a design rule that counters it, and a first move any actor can make. The first four act inside organisations and the last two across markets. They are recurring patterns, not a checklist: a given transition may hinge on two of them and barely touch the rest.
The actors behind the blockers are not villains. They respond sensibly to the incentives in front of them, which is why culture programmes alone rarely hold. Incentives, measures, governance and the flow of knowledge have to change with them.
- default
- Status follows seniority, certainty and a record of success.
- blocker
- Opinion as religion. When the most senior person’s view settles a question, testing stops. Internal consensus drifts away from what is happening outside, and because disagreeing is costly, the drift goes unreported.
- design rule
- Default to “prove me wrong”. Before any significant decision about a market, a technology, a direction or a hire, ask what would have to be true for it to be wrong. If nothing could, it is a belief. If the answer is specific and testable, it is the next experiment. Make the question a governance requirement, and give credit to people who change their minds on evidence.
- first move
- Before agreeing with the most senior voice in the room, ask what would make it wrong. If you cannot answer, say so. For an organisation: stop letting rank settle open questions.
- default
- People are rewarded for hitting targets, and a failed project damages a career.
- blocker
- Sunk cost inertia. Past investment creates pressure to continue whatever the evidence says, and the pressure grows with the size of the investment. The sunk cost effect is a well-documented cognitive bias. Leaving it unchecked is a governance failure: set the stop criteria before the money is spent, and let someone who did not make the original call decide whether to continue.
- design rules
Pay for evidence. Reward honest early failure. A deliverable should be able to fail a test: could data that might realistically exist prove it wrong? A strategy deck or market analysis that could not is an opinion, and should be priced as one. Pay for prototypes, experiments and tested hypotheses, including those that came out negative.
A team that framed a clear hypothesis, tested it properly, got a definite no, stopped and shared what it learned has done valuable work. Tata’s Dare to Try award and NASA’s Lean Forward; Fail Smart award exist to recognise that. Reward the quality of the thesis and the cleanliness of the exit, not failure as such.
- first move
- Publish one failure with its evidence: the thesis, what you tested, what broke.
- default
- We trust our customers and our current market data, and optimise for both.
- blocker
- Metric misalignment. A new model tends to look worse on the existing metrics before it looks better on any new one. Quarterly revenue, headcount efficiency and satisfaction scores for existing products were designed for the current business, so they register the new mainly as a cost.
- blocker
- Innovation theatre. Labs, hackathons and innovation titles can absorb the pressure to change without changing anything, because they are measured on inputs such as ideas submitted and workshops held.
- design rule
- Give the new its own scoreboard. Measure the new by what it proves, keep that scoreboard apart from the core metrics, and count outputs. Give non-customers and edge cases the same attention as the customers already served, because that is usually where the new first shows up.
- first move
- Report one signal the current system does not measure.
- default
- Whoever built it keeps running it, and governance exists to keep things consistent.
- blocker
- Founder bottleneck. The skills and roles a company needs can change sharply as it scales. In Wasserman’s study of 212 American start-ups, fewer than a quarter of founders were still chief executive at the IPO. That shows how common the handover is; it does not show the cause. Where no handover happens, a role can outlive its phase. The same holds for a seed-stage board kept through later rounds, or an early colleague kept in a role out of loyalty.
- design rule
- Set the direction, rotate the roles. Give a clear Mission and wide latitude on how to reach it. Let roles change hands as the phase changes, on triggers agreed in advance, and put governance on rotating terms.
- first move
- Put the Mission ahead of your current position, and name it clearly enough that handing over a role does not feel like abandoning it.
- default
- Knowledge is a competitive advantage, to be held and protected.
- blocker
- Ecosystem closure. Platforms often open up to attract users and builders, then restrict access and raise prices once they dominate. The incentive is simple: the connector that once linked others now controls the route between them.
- blocker
- Technology lock-in. Once enough connections, data and workflows are built on a system, the cost of switching can exceed the gain from a better alternative. The barrier is the switching cost, not the quality of the technology.
- blocker
- Regulatory capture. Regulators can come to protect the firms they oversee, and compliance costs that incumbents can absorb become entry barriers for everyone else.
- design rules
Build neutral ground early, and keep it contestable. Openness is not the goal in itself. A tightly governed system can sometimes coordinate better than an open one, and a nominally open one can still be captured. What matters is that shared infrastructure stays contestable: others can interoperate with it, take their data with them, replace any component including the operator, and leave at a tolerable cost, under governance that no single actor controls. That is what open means in this manifesto.
Set it up before large commercial interests form. The period in which a technology is proven enough to attract serious investment but not yet entrenched is short, and separating infrastructure from its owner afterwards is possible but far more expensive.
- first move
- Share what you have learned before anyone asks.
- default
- Uncertainty is a risk to be removed before acting.
- blocker
- Nash equilibrium lock. Each actor in a market optimises its own side of the transaction. The result can be a stable state that nobody has a reason to leave alone, even though most would gain if all moved together.
- blocker
- Academia-practice gap. Academic incentives concentrate rewards around publication, and industry incentives around proprietary application. Neither side is consistently rewarded for turning controlled evidence into independent, reusable proof in practice, and the stage between laboratory proof and commercial use is underfunded. Value arrives late and work is done twice.
- design rule
Fund the gap, and move together. Testing research against real use produces evidence that benefits a whole field, so a single private investor rarely captures enough of the return to fund it alone. Public and pooled ecosystem money fills that gap and makes later private investment easier to justify.
Seat researchers in the build with data access and the right to publish, so that each side’s evidence is checked by the other. Where a market is locked, have one actor from each side commit to one small case, on condition that the others do.
- first move
- Act on the evidence you have before the system is ready to back you, at a scale where being wrong is affordable.
The blockers share a root: an actor optimising its own position within the current system, at a cost to the system’s capacity to change. That makes this less a cultural problem than one of structure and incentive design.
See what a mission is and how one is built → See who contributes, and how to join →
the.initiator
Who starts, and why would they?
Our proposition.
Design rules are not adopted by markets. They are adopted by one actor, and then by others. The initiator is the actor that makes the shifts before its market rewards them. It can be a founder, a company, a fund, a regulator or a community, and in each case it acts through people who decide. Our proposed sequence is that one actor changes what it optimises for, its behaviour changes accordingly, others with compatible interests join, and structure follows to protect what they have built.
This manifesto has argued that actors follow their incentives, so the initiator cannot be the exception. It does not act against its own interest. It changes which interest it pursues, and three mechanisms can make that pay.
Where value depends on a shared standard or on other users, a share of a large, settled market can be worth more than control of a small, contested one. An actor that expects this gains from ending the contest, even at the price of opening what it owns.
An actor that earns from what is built on or around the shared layer, such as products, services or capacity, gains when that layer spreads, whoever owns it.
The initiator’s design becomes the reference, its people know it best, and it is furthest along in using it. That advantage is real, and it does not depend on owning the infrastructure.
What it costs. The first actor usually pays more than those who follow. It funds the first builds, absorbs the first failures and carries the risk that nobody joins. The proposition holds only where the three gains can outweigh that cost, which is why it is limited to markets with lock-in and network dependence.
Where it stops. If the initiator’s advantage comes to depend on controlling the shared layer, the incentive to close it returns. Ecosystem value first, own position second, works because the second is made to depend on the first. The contestability rules of shift 5 are what keep it that way.
The six first moves in part 02 are where an initiator begins. None of them needs permission. Each needs one actor for whom the calculation works, and who acts on it.
the.flywheel
How does it keep going?
Our proposition, and the part most in need of testing.
The initiator’s first move fades unless others can join it. The flywheel is our model of how they do: an inclusive ecosystem on shared, contestable infrastructure that incumbents and newcomers can both use, built up through four recurring stages.
the initiator starts the loop. each turn should make the next one cheaper.
At the centre: inclusive ecosystem, open to incumbents and newcomers alike. From stage 4 back to stage 1: reuse makes the next turn cheaper.
activate the ecosystem.
- what it is
- The smallest set of roles that takes one thing from built to used
- scoreboard
- roles filled
A working solution does not distribute itself, and those who build are rarely those who operate. Start with the minimum complete set: the smallest group of roles that can take one thing from built to used. In a locked market that means one actor from each side of the transaction and, where research or regulation matters, the researchers and the rule-makers too. The ecosystem is activated when each of those roles is filled by an actor that has committed. Hold roles by function and not by ownership, so that they can change hands as the market matures.
draws on shifts 4 and 6
relentlessly expand the ecosystem.
- what it is
- Open entry and replaceable parts, the orchestrator included
- scoreboard
- partners joined
Let partners join at any time, avoid vertical lock-in, keep every component replaceable, and let partners specialise. The replacement right has to cover the orchestrator, and it is credible only if a component is actually swapped from time to time. Keep entry open to actors the core does not yet serve, because they are often the first to see what the core’s metrics miss.
draws on shifts 5 and 3
learn from building.
- what it is
- Start small, set the stop criteria, pay on outside proof
- scoreboard
- proofs gained
Build toward an immediate objective with clear value, and start small. Write down the thesis and the stop criteria before each build. Seek proof from outside the group, and pay on proof delivered, whether the answer is yes or no. Research partners co-build, so that the build is itself the test between laboratory and market, and the partners who will reuse the result fund it together. Then extend what works to neighbouring cases.
draws on shifts 1 and 2
create reusable products.
- what it is
- Bridges, shared compliance and published learnings
- scoreboard
- components reused
Turn what was built into capabilities that others can reuse and combine. Make bridges, adapters, data export and shared compliance the first of them, so that joining does not require leaving the old system at once and compliance cost stops working as an entry barrier. When a build stops, harvest its parts. Publish what was learned, failures included, and credit whoever produced it, so that being reused builds reputation.
draws on shifts 5 and 2
When both sides can join shared infrastructure, joining costs less than defending, and the side that is losing stops sooner.
Each term needs a definition.
- joining cost
- What an actor pays to take part: integration work, the data and practices it has to share, and the control it gives up.
- defending cost
- What it pays to hold out: maintaining a rival standard or a closed system, the customers and partners it loses while the market stays split, and the risk of being stranded on the losing side.
- open
- Contestable in the sense of shift 5: interoperable, portable, replaceable, with a credible exit, under governance that resists capture.
- transition duration
- The time from a technology being proven to its broad use.
- broad use
- It has become the default for most of the relevant market, not only for early adopters.
The proposition is that shared infrastructure can lower the cost of joining with each turn, while the cost of defending a rival system rises as others join. At some point joining is the cheaper option even for those who would have preferred to win.
Why each turn should be cheaper. Reusable components mean a later actor integrates what an earlier one built. Shared evidence means it does not repeat the earlier one’s failed experiments. Interoperability means its existing systems keep working. This is the network effect we claim for the shifts: each actor that makes them lowers the cost for the next.
The counterweight. More participants also mean more coordination: more interfaces to agree, slower decisions, more governance. The flywheel works only while the gains from reuse, shared evidence and interoperability exceed the additional coordination costs. Where they do not, a smaller or more tightly governed group will move faster, and should.
One scoreboard per turn. Roles filled, partners joined, proofs gained, components reused, kept apart from each partner’s core metrics.
Where to enter. With the minimum complete set and one small build. Activation is the condition for starting; completeness is the direction.
What keeps it contestable. A flywheel that succeeds is tempted to close, and the network effects that make it attractive are what would let a winner lock others in. The rules of shift 5 therefore apply to the flywheel itself, its orchestrator included.
What it does not do. It builds around a locked market and does not unlock it. It does not move an incumbent that already has the regulator on its side. Reputation inside the ecosystem does not change who is promoted inside each partner. Where it works, it works by making the prevailing model unnecessary.
See how a mission is built with singular.alpha → Open the knowledge repository →
what.if.not
What would make us revise the model?
open question Open. None of this has been tested yet.
The manifesto asks every actor to say what would prove a decision wrong. These are the findings that would make us revise the model.
Shared, contestable infrastructure repeatedly fails to shorten the time from proven technology to broad use.
Joining remains more expensive than maintaining a rival or closed system, even as others participate.
The additional cost of interfaces, governance and collective decision-making consistently exceeds the gains from reuse, shared evidence and interoperability.
The network effects created by the flywheel make capture or closure structurally unavoidable.
Actors that go first repeatedly fail to recover the cost of doing so, even in markets with lock-in and network dependence.
Transitions repeatedly hinge on blocker structures the six shifts do not capture, or incumbents and newcomers prove to face materially different mechanisms.
“A technology’s value reaches most people only when the infrastructure it runs on stays contestable, and when the actors inside it keep making the decisions that hold it open. Neither happens by default. You are one of those actors.”
This manifesto is an invitation to builders, investors and institutions to treat the next transition as a decision about incentives and shared infrastructure, and to test this model with us.
Start something → Download the manifesto in the Commons →
dizrupt · zurich
collective
The Collective is infrastructure for missions.
what it is ↓ what it does ↓ how to join and contribute ↓ the rules ↓
what.the.collective.is
the Collective is infrastructure for missions.
It brings together contributors who can initiate transitions, fill roles, supply scarce contributions and independently challenge claims.
The initiator is the actor that changes what it optimises for and moves first.
The ecosystem is activated when each of those roles is filled by an actor that has committed.
A contribution that only a few actors can bring to the transition, such as trust, judgement, authority, access, technology, data or capital.
Every claim can be tested by someone with no stake.
what.the.collective.does
connect, assess, deliver, share.
Peers in one role name the same blocker. That is a candidate case.
howStructured roundtables for senior practitioners. Remove noise, build trusted relationships, and enable network-based collaboration through first-hand expertise.
singular.state assesses a defined organisation or programme in a named transition at a specified evidence date.
howThe same every time: Scope, Collect, Score, Report. The score is whatever the artefacts show.
singular.alpha is the five-step method for turning an initiator’s first move into something others can join.
howFrame, Find Alpha, Engage Beta, Prove, Commonise.
The Commons contain what subsequent builds should not have to recreate.
howWhen a build stops, harvest its parts. Publish what was learned, failures included, and credit whoever produced it, so that being reused builds reputation.
how.to.join.and.contribute
selected through peer validation and proven contribution.
Membership is based on contribution and peer validation, not status, paid access or institutional prestige.
how joining works
Recommended, or seen at work
A member recommends you, or peers first meet your work in a Roundtable.
Validated by peers
Peers who know the field confirm the contribution.
Given a role
You fill a role, supply a scarce contribution or challenge a claim.
ways to contribute
Contribute expertise
Fill a role, supply a scarce contribution or challenge a claim.
Recommend a peer
Name someone whose contribution you have seen.
Join a Roundtable
Name the blocker you keep meeting in your role.
Initiate a mission
Name a direction, and one claim to test at a scale where being wrong is affordable.
Fund the evidence
Testing research against real use produces evidence that benefits a whole field, so a single private investor rarely captures enough of the return to fund it alone.
Research with us
Seat researchers in the build with data access and the right to publish, so that each side’s evidence is checked by the other.
the.rules
the rules members work by.
Seats in Roundtables and recommendations are not for sale.
Ecosystem value first, own position second.
Every part is replaceable, the orchestrator included.
Every claim can be tested by someone with no stake.
What was learned is published, failures included, and whoever produced it is credited.
No single actor controls the governance, dizrupt included.
missions
A mission is the named direction of a transition.
singular.alpha is the five-step method for turning an initiator’s first move into something others can join.
why it is needed ↓ where it runs ↓ how it is done: singular.alpha ↓ how it is assessed: singular.state ↓ what it is not ↓
why.it.is.needed
one actor can start a transition. alone, the first move fades.
Once a technology works, most of what delays its use sits outside whichever actor carries it: adopters’ switching costs, missing complements, standards nobody will adopt alone. These bind incumbents and newcomers alike.
where it runs
Sense the friction
Peers in one role name the same blocker. That is a candidate case.
Supply the contributions
It brings together contributors who can initiate transitions, fill roles, supply scarce contributions and independently challenge claims.
Name it, prove it small
The mission is the direction, named clearly. One small build runs towards it, with the claim and the stop criteria written first.
Keep what was learned
The Commons contain what subsequent builds should not have to recreate.
Let partners join at any time, avoid vertical lock-in, keep every component replaceable, and let partners specialise.
Seats in Roundtables and recommendations are not for sale.
singular.alpha
a method for turning a first move into something others can join.
singular.alpha is the five-step method for turning an initiator’s first move into something others can join.
five steps, each with one question
Frame
- question
- Which transition is stuck, and which shift blocks it?
- output
- A named mission and a claim to test
- draws on
- six.shifts
Find Alpha
- question
- Who moves first, with what scarce contribution, and which roles from built to used?
- output
- An initiator, committed Alphas and a role map
- draws on
- the.initiator, flywheel stage 1
Engage Beta
- question
- What can the ecosystem supply, standardise or automate, so the build does not recreate it?
- output
- Committed Beta, and the gaps to supply
- draws on
- flywheel stage 2
- supporting instrument: Beta.Engine
- Beta.Engine supports the supply of repeatable Beta.
Prove
- question
- What would show the claim is wrong, at a scale where being wrong is affordable?
- output
- Outside proof: yes or no
- draws on
- flywheel stage 3
Commonise
- question
- What should the next build not have to recreate?
- output
- Published Commons, failures included
- draws on
- flywheel stage 4
5 → 1: reuse makes the next turn cheaper (flywheel stage 4 to 1). Entry stays open throughout.
Every step ends in something that can fail a test.
three terms carry the method
the method and the six shifts
rank → evidence
Default to “prove me wrong”
results → learning
Pay for evidence, reward honest early failure
old metrics → new signals
Give the new its own scoreboard
ownership → roles
Set the direction, rotate the roles
closed → open
Build neutral ground early, and keep it contestable
waiting → moving
Fund the gap, and move together
The shifts are patterns, not a checklist. A transition may hinge on two and barely touch the rest. Step 1 names the shift. The shift decides what has to be proven.
singular.alpha stays contestable
Others can interoperate with the Commons and take their data with them.
Every part is replaceable, the orchestrator too.
Anyone can leave at a tolerable cost.
No single actor controls its governance, dizrupt included.
singular.state
singular.state measures a unit inside a named transition.
singular.state assesses a defined organisation or programme in a named transition at a specified evidence date.
A first run sets the profile: an evidence-based score from one to ten on how far the shifts have been made.
Frame, Find Alpha, Engage Beta, Prove, Commonise.
A later run, by the same rules and on the same unit, shows what moved.
what it assesses
Unit assessed × named transition × evidence date. The transition is mandatory. It defines what the evidence is evidence of.
It does not prescribe the move. It establishes the state from which a move can be framed, tested and later measured again.
What is scored
A practice the manifesto asks for, which an artefact can show.
How far it has moved
Default, Named, Tried, Built in or Held. Each state spans two points on the scale.
What explains the state
A condition of the organisation or its market that pushes elements up or down.
Elements are scored. Characteristics explain the score and are not part of it.
Falsifiable decisions
Is it written down what would show a decision wrong?
Bounded bets
Does it move early and small, with stop criteria set in advance?
Bad news and failure travel
Does bad news reach those who decide, and is honest failure recognised?
Own scoreboard for the new
Is the new measured by what it proves, apart from core metrics?
Roles over ownership
Do roles change hands when the phase changes?
Payoff logic
What does it optimise for?
Outside proof
Are claims tested by someone with no stake, and paid on the result?
Contestability
Can others interoperate, take their data, replace parts and leave?
Reuse and Commons
Does the next actor inherit what was built and learned?
Minimum complete set
Are all roles from built to used filled and committed?
Every element is a practice that an artefact can show.
how it assesses
assess.state: the same four steps run every time it is appliedScope
Which unit, which transition and which evidence date? Which elements does the transition hinge on?
The binding elements
Collect
Which artefacts exist for each element?
The artefacts
Score
Which state does the evidence show for each element?
Ten scores
Report
What does the profile show, and which element is the binding constraint?
Headline, profile and binding constraint
The score is whatever the artefacts show. 4 back to 1: a later run follows the same steps and shows what has moved.
No artefact, no score above 4. The headline is never shown without its profile.
Three are context to record. Stake in the current model, market lock-in and initiator position. Each of the ten is profiled as hinders, neutral or helps.
A score that rises while incentives, measures and governance stay the same should be expected to fall back.
a first run sets the profile, and a later run shows what moved.
illustrative. invented figures, not a real assessment
All ten elements sit at Default or Named. The case is an organisation whose AI agent moves from recommending to acting.
Five elements reach Tried. Falsifiable decisions, Outside proof, Reuse and Commons, Minimum complete set and Bounded bets move. Five do not. Incentive design is unchanged, so the gain is flagged as likely to fall back.
Each run shows where the organisation stands. Two runs show what moved.
it is not a certificate, a survey or a sales tool, and it is untested.
would change our mind
- A maturity certificate. No level is awarded and none is for sale.
- A culture survey. Opinions support a score and never set it.
- A sales tool. A low score is no argument for a mission.
- Two assessors scoring the same evidence often differed by more than two points.
- Among organisations facing the same outside conditions, higher-scoring ones moved transitions no faster.
- Scores fell back even where the characteristics had changed.
dizrupt reports the score the evidence supports, including when it did not move.
what.it.is.not
what it is not.
Seats in Roundtables and recommendations are not for sale.
commons
The Commons contain what subsequent builds should not have to recreate.
why.we.share
share what you have learned before anyone asks.
Knowledge is a competitive advantage, to be held and protected.
why we do the oppositeOpenness is not the goal in itself. What matters is that shared infrastructure stays contestable: others can interoperate with it, take their data with them, replace any component including the operator, and leave at a tolerable cost, under governance that no single actor controls.
Reusable components mean a later actor integrates what an earlier one built. Shared evidence means it does not repeat the earlier one’s failed experiments. Interoperability means its existing systems keep working.
Reuse makes the next turn cheaper.
This is the network effect we claim for the shifts: each actor that makes them lowers the cost for the next.
documents
documents.
signals
signals.
Short posts on what is moving, published by beta.engine. Each one names its source.
semantic.chain
semantic.chain
How the terms depend on each other, in the order the argument runs.
- premises
- transition
- adoption/disruption
- actors
- value system
- shifts
- initiator+changed payoff logic
- mission
- Alpha+ecosystem
- Beta
- CommonsthroughCommonise
- flywheel
- next turn
The instruments work on this chain. singular.state reads it through element, state and characteristic.
the.terms
the.terms
The first sixteen terms belong to the theory of change in the disruption.manifesto. They are listed in the order the argument uses them. The last four are the terms the instruments add. They carry no theory of their own.