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In the age of AI, what makes what you do unique?¶
It is not just the result you deliver. It is also the ability to make what made the result possible legible to others.¶
Today, an AI can write a text similar to yours. Someone else can reach a solution similar to yours. When we look only at the result, everything may seem equivalent, but it is not.
The result alone does not reveal who identified the problem, who defined what mattered, which criteria guided the assessment of alternatives or who took responsibility for the decision to follow a particular path.
These differences become more important in the age of AI. As producing text, code, analyses and solutions becomes easier and cheaper, some of the effort and value of work shifts from execution to the choices that guide it. And those choices do not always accompany what is delivered.
These contributions have always existed. Some are already recorded in planning documents, reports and management tools. Others remain scattered across conversations, decisions and experiences that rarely accompany the result, especially when the work involves different people and tools.
The Legible Protocol is an open standard for recording what a person formulated, the criteria and choices they took responsibility for, and the relationships they declare with other work. These records describe the personal and cognitive provenance of their contribution and can accompany the result they deliver.
What you formulated, the criteria and choices you took responsibility for, and the relationships with other work can therefore accompany the result and be understood as an important part of the value you produce.
See how it works · Start with a draft
What you can do with Legible¶
You can start by recording individual work or organize an ongoing space for collaboration. The same record formats can relate work produced across company departments, independent projects or participants who are not yet part of a team.
| Context | A possible application |
|---|---|
| Your own work | Preserve your formulations, choices and evidence, and share a history of declarations under your control. |
| Companies | Bring together knowledge from different areas and consider problems and proposals before assigning their execution. |
| New projects | Present an idea or need and develop contributions before forming a team. |
| Open source | Make decisions, dependencies and consequences acknowledged by users of the work available for examination. |
| Independent professionals | Deliver work with its genealogy and preserve declarations and acknowledgments across professional relationships. |
| Collectives and cooperatives | Build a shared memory of contributions and their relationships to support collective decisions. |
| Public institutions | Formulate needs, consider external capabilities and preserve the origins of solutions adapted across institutions. |
| Foundations and funders | Examine contributions and consequences before choosing what to support, including work they did not commission. |
These applications depend on the practices, access arrangements and tools in each context. The final chapters of Open Legibility develop their implications; the site's guides show how to begin with records and exchanges, while the catalogue identifies available components.
Explore possible uses · Consult code and configurations
How work becomes legible¶
Legible distinguishes the work produced from the declarations its participants take responsibility for about it. A declaration can present the problem that guided an investigation, a criterion adopted in an analysis or a solution developed. Documents, code, tests and versions of the result can be referenced as evidence, retaining their own formats and access conditions.
Each participant can describe what they formulated and identify the work they drew on. Recipients then have material to examine those contributions, question their reasoning and develop another formulation, without attributing everything that made the final result possible to its author.
These records also preserve distinctions between work that reaches similar results. A conclusion may have arisen from independent analysis or from using an earlier formulation; similarity of content alone does not explain that origin. What Legible allows people to record is each author's declaration about what they did and the relationships they take responsibility for.
But isn't this information already recorded?¶
In many organizations, it is.
Engineering teams document architectural decisions. Companies record hypotheses and priorities in strategic planning. Researchers describe their methods and reasoning. Management tools preserve discussions, responsibilities and changes.
These practices matter, and Legible does not seek to replace them.
Legible adds the possibility for each participant to adopt a declaration through a verifiable digital signature, without requiring approval from a platform or the institution receiving the work.
A person can associate that key with the identity by which they are already known. That link can be checked through a known channel or direct relationships with the author; the signature alone does not establish it. Recipients can then verify the signature and consider the declaration in light of what they know about the author's history and relationships. The record can accompany the work across tools and organizations, preserving the content adopted and allowing its attribution to the same key to be verified.
You can begin with a draft and choose to sign a declaration later. The signature does not decide whether the declaration is true or the proposal deserves to be used; it allows verification of the attribution and integrity of the declaration on which that judgment will be based.
Understand how to preserve a formulation for other uses.
You can start with the work you already do.¶
The first step can be a genealogy draft: a document that accompanies work and describes what you formulated, the criteria and choices you took responsibility for, the references used and the questions that remain open.
You can prepare this draft yourself or with AI assistance. When reviewing it, check that the description matches what you actually did and distinguishes your participation from other people's formulations and AI suggestions. An unanswered question, incomplete analysis or partial solution can also be described.
You can begin with just your own records, preserving what you formulated, the choices you took responsibility for and the references needed to return to the work. By sharing them, you give others the means to understand your reasoning and develop another solution.
When this new work preserves its relationships with earlier work, your formulation can continue to inform other investigations and decisions. The habit that began as a way to understand and take responsibility for your own work also comes to support collaboration: others can add what they know, declare what they used and acknowledge the consequences they received.
Prepare your first draft · See the example files
What happens when the value you produce meets the value other people produce?¶
By sharing the formulation of a problem, you give those with access to the record the opportunity to understand what you observed, examine your criteria and see what still needs investigation. This reading can reveal complementary knowledge, a condition not previously considered or a different application for the same idea.
When another participant decides to respond, the exchange can change the problem itself. An experience adds context to the investigation, an objection leads to a criterion being revised and a hypothesis opens another possible solution. Collaboration begins to produce formulations that none of the participants had initially presented.
Legible allows what each person added, the choices they took responsibility for and the relationships they declared with earlier work to be preserved. These new formulations can, in turn, be examined and developed by other participants, even outside the project where they arose. To record these contributions and relationships, the protocol defines three fundamental types of declaration:
| Record | What its author declares |
|---|---|
| Appoint | A formulation they take responsibility for, such as a problem, hypothesis or solution. |
| Trace | Which other work a formulation or decision drew on, explaining the declared relationship. |
| Nod | A consequence they received and chose to acknowledge after it occurred. |
Someone deciding to invest in a proposal can also declare which work informed their choice, referencing the corresponding document. Authorization to commit resources remains within the organization's processes. Subsequent recognition by a beneficiary is a separate act, with its own author and circumstances.
This information matters to both sides of collaboration. Recipients can examine reasoning and evidence before deciding how to participate. Those who share can keep their participation identifiable and follow the uses and consequences others declare. Reading these records helps people understand what the work made possible and decide where continued collaboration is worthwhile.
Participants can develop a common proposal or follow different paths. An accessible formulation can give rise to new work even without a team, an assigned task or a prior agreement between its authors.
Understand how to share and develop work.
What if a contribution could exist before someone decided to use it?¶
Formulating a problem and deciding to invest in solving it are different acts. A proposal may not be adopted and still contain an observation, criterion or hypothesis relevant to other work. For this to be considered, the formulation needs to be preserved and accessible under conditions that allow it to be understood.
In many organizations, preserving information and deciding which information will be used are closely connected activities. A proposal tends to receive attention and remain in work processes when it is accepted or considered important enough.
There are economic reasons for this. Preserving large amounts of information, finding what is relevant and interpreting its meaning have always required resources.
AI can reduce some of these costs. If someone can record a formulation with little effort and others can find and examine it with AI assistance, preserving contributions before knowing which will be used becomes more feasible.
This can change not only how solutions are found but also how problems are identified. People from different companies may record similar difficulties and, on finding those observations, recognize an unmet need. Others may add criteria and develop alternatives without having previously belonged to the same project or organization.
The proposal is not to eliminate selection. Companies and individuals will still need to decide where to put their time, money and attention. The difference is that preserving a contribution and choosing to use it do not have to happen at the same time.
A formulation that found no application today may remain available to someone with different goals, criteria or resources tomorrow.
Understand how to operate in Open Legibility · Read The Economics of Legibility
An open protocol, so contributions do not depend on a platform.¶
Work can continue in the documents, repositories, management tools and AI interfaces you already use. Legible records present declarations about that work and reference relevant materials, allowing their relationships to be preserved across different environments.
It defines an open format for signed declarations and relationships between contributions. Records are identified by their content and can be preserved, shared and verified independently of a central server.
There is no requirement for a blockchain, token, account or mandatory platform. Different applications can implement the protocol, offering their own ways to create, find and examine records.
The protocol does not, on its own, make information public or guarantee that it will be found. Each person or organization remains responsible for deciding what to preserve, share and make available for consultation, respecting the applicable access conditions.
An open project under development¶
The Legible Protocol specification is at draft 0.4. Its formats, guidance and reference implementations are available for examination and testing. Not every envisaged capability is available in a ready-to-use application.
You can already try the central idea with a draft accompanying real work. Project status and the code and configuration catalogue explain what is available and what still needs development.
Start with a draft · Participate in a space · Create a space
To understand the ideas behind the protocol¶
Open Legibility — What Happens When No One Needs to Be in Charge? investigates how artificial intelligence is changing the costs of work, the importance of human choices and the conditions for collaboration between people and organizations.
The Economics of Legibility examines how the costs of preserving, finding and interpreting contributions influence the alternatives that come to be considered, and under what conditions that boundary can expand.