An AI that works with people, knowledge and tools, and develops the capabilities it uses to carry out the work.
The system also works while the question is still taking shape: it explores the context, organises and carries out activities, with people and autonomously. Acquired knowledge and methods inform the current work and what follows.
↶ Work develops the knowledge and methods the system uses to continue.
People and AI participate in the same work. Results also change the system’s capabilities.
How it works
How the system understands, acts and learns
The semantic kernel is operational knowledge expressed in natural language: knowledge, principles and methods through which the system understands and works. Initial competences develop through interaction with people, sources and the results of the work. The agent exercises this knowledge with the people, means and access available in its own environment.
The system understands and acts beyond its existing frameworks
Available knowledge and tools contribute to the work without exhausting its possibilities. Facts, sources and relationships also shape the question and method.
It recognises when its own interpretation has altered the meaning of sources, people’s intent or the direction of the work. It recovers lost relationships and uses its updated understanding to change decisions and actions.
The system recognises, combines and develops know-how. New understanding also changes its questions, pertinent sources and how it forms further capabilities.
It prepares the knowledge and methods for the work of a project, group or organisation. The resulting kernels continue to develop their own capabilities through their activity.
Participates in the evolution of products and services
Acquired knowledge also changes how products and services are designed. When a kernel becomes an operational part of them, it accompanies their evolution through feedback from use.
A customer requests a change while keeping the delivery date. The system connects the order’s documents, decisions and activities; what it understands also develops the method through which it continues.
Choose a relationship to understand. Each topic connects an explanation, diagram, example, further detail and sources.
The system understands context and acts with awareness of causes and consequences (CCCC)
The system already brings a core of principles and competences to begin. In work, people and AI encounter information, tools, decisions and consequences: understanding develops within the context and guides the evolution of methods and activities.
The kernel is the logic through which the system understands and works. The D-ND model provides the relations between possibility, movement and resultant: they take shape in competences and in how the system continues and changes.
The system’s works with the knowledge, people, processes and tools of a company or sector. Activities and capabilities needed depend on the concrete case.
Research into the system’s logic and new capabilities
Research connects the study of the system’s logic with laboratory work. Results and counterchecks reveal which questions and methods to revisit and how to develop new capabilities.
The system understands context and acts with awareness of causes and consequences (CCCC)
This area, briefly
How the system connects understanding, decisions, activities and new capabilities.
The system already brings a core of principles and competences to begin. In work, people and AI encounter information, tools, decisions and consequences: understanding develops within the context and guides the evolution of methods and activities.
MAIOS Project Kernel (MPK) already includes principles and competences for understanding context and acting with awareness of causes and consequences. The system develops these capabilities through interaction with people, sources and the results of its work.
Understand the situationCarry out activitiesEvaluate consequences
Understand what is done and why
Section topics
System in action
01
Context and sources of the system’s work
It connects objectives, people, facts and documents to understand the situation, distinguish verified information and recognise what needs clarification.
How the system updates its understanding of the workNumbers: connections · Arrows: direction
Goals, people and sources
The system understands the situation
Results and new facts
1The system connects the context and sources2update what the system understands about the situation
The system understands the variant of the order
The customer requests a change with the same delivery date: the system connects the request, drawings and conditions to identify the effects on activities.
The customer changes a requirement: what needs to be understood?
The original orderThe objective, drawings and agreed conditions.
The new requestA change, the same delivery date.
The updated situationThe system connects the sources and understands which activities and conditions to reconsider.
understand together
In the work
The effects to examine and the information still needed become recognisable.
The system understands how goods and services are purchased
The review starts from received requests, working documents and the company’s selection criteria.
Requests and criteria in the purchasing process
Process documentsRequests, activities and reasons for decisions.
People and criteriaWho contributes and how a request is assessed.
The system connects the contextUnderstands where to act in the actual process.
understand the process through its sources
In the work
Activities and information needing an update become recognisable.
The system reconstructs the dossier’s sources
The practice brings the dossier materials together. The system compares those documents with the new sources to understand which information and relationships change.
The dossier and new case information
Existing dossierDocuments and reasons behind the version in use.
New sourcesInformation to compare with earlier materials.
The system understands the differencesIdentifies which points and relationships to revise.
compare pertinent versions and sources
In the work
Points in the dossier requiring revision become recognisable.
The system understands the work the application must perform
Objectives, users, sources and project conditions shape the problem to address.
The application’s purpose and context
Intended workWhat people want to accomplish with the application.
Project sourcesRequirements, data and available tools.
The system shapes the solutionUnderstands which functions and relationships to develop.
shape the problem through the actual work
In the work
The solution develops from the context the application must serve.
The system understands the group’s work and requests
People, sources and recurring situations make recognisable what the new system needs to know and do.
The group’s requests and knowledge
The group’s workActual requests, objectives and activities.
Contextual sources and methodsDocuments, reasons and available capabilities.
The system understands the system to formConnects necessary knowledge and contextual possibilities.
form the system through its work
In the work
The kernel takes shape from the group’s work and sources.
The system explores the organisation’s work with people
The organisation’s intent meets activities, knowledge and possibilities still to be understood. The task forms within that exploration.
Intent, knowledge and a situation to understand
form the question and contextual understanding together
Organisation’s intentWhat it wants to explore and develop with AI.
Knowledge and possibilitiesThe work, sources and what has not yet been connected.
The system understands with peopleExploration makes new relationships and questions pertinent.
In the work
The question develops through work on the context.
The system connects plasma hypotheses to sources and observations
Measurements, simulations and model reasons help distinguish what is understood and what the inquiry needs to clarify.
Hypotheses and observations of the phenomenon
Model hypothesesProposed relationships for understanding the phenomenon.
Observations and simulationsResults obtained through the domain’s scientific tools.
The system understands the comparisonConnects reasons, results and still-open questions.
give meaning to the comparison between hypotheses and results
In the work
The group identifies which relationships to explore further in the inquiry.
Explanation
Context is the situation in which work happens: goals, people, facts and conditions. Sources are the documents, data and accounts from which information is obtained. The system connects them, distinguishes what it has verified from what needs clarification and uses that understanding to act.
An example
A person begins an inquiry into a possibility that is still taking shape. The system connects the person’s intent, sources and available knowledge. This understanding helps form the question, the knowledge needed and the work to develop.
Variant requested · delivery date unchanged
The order
The new request is read alongside the drawings, decisions and conditions of the order.
The know-how
The system identifies the relationships to examine and what needs clarification.
Same process · documents, criteria and activities
The purchasing process
Activities and information needing an update become recognisable.
The know-how
The reasons behind the criteria participate in the method used to address the review.
Same dossier · updated sources and versions
The dossier
Points in the dossier requiring revision become recognisable.
The know-how
The method distinguishes new information from a change in the meaning of the case.
Same software project · problem, code and results
The application
The solution develops from the context the application must serve.
The know-how
Project knowledge keeps the request and technical reasons connected.
Same group · requests, knowledge and capabilities
The group’s kernel
The kernel takes shape from the group’s work and sources.
The know-how
Understanding can also change the question from which the group started.
Open field · intent, knowledge and possibilities
The emerging project
The question develops through work on the context.
The know-how
The competence recognises possibilities beyond the initially represented task.
Physical-computational research · questions, models and observations
The plasma inquiry
The group identifies which relationships to explore further in the inquiry.
The know-how
The method distinguishes the phenomenon’s model from observation conditions.
More detail
Understanding is updated as work proceeds. The system reviews the goal, method and competences needed in light of results and new facts. Reasons that remain valid stay available, so work continues with an understanding of what has changed. The question and objectives also take shape through this understanding: an already defined project is one context in which to work.
Illustrative case · A customer order changes
The new request changes the situation of the order. The system understands it through available sources, conditions and reasons, also identifying what needs clarification.
The customer requests a change while keeping the delivery date. The system relates the new request to the drawings, decisions and conditions of the order. It understands what changes and which information is needed to proceed with an understanding of causes and consequences.
Illustrative case · Revising a purchasing process
The review starts from received requests, working documents and the company’s selection criteria. The reasons behind the criteria participate in the method used to address the review.
Illustrative case · Updating a professional dossier
The practice brings the dossier materials together; the system compares them with the new sources and understands which information and relationships change. The system distinguishes adding information from a change in the meaning of the case.
Illustrative case · Developing an application that continues evolving
Objectives, users, sources and project conditions shape the problem to address. Project knowledge keeps the request and technical reasons connected.
Illustrative case · Forming a kernel for a group’s work
People, sources and recurring situations make recognisable what the new system needs to know and do. Understanding can also change the question from which the group started.
Illustrative case · Forming an AI project still to be defined
The organisation’s intent meets activities, knowledge and possibilities still to be understood. The task forms within that exploration. The competence recognises possibilities beyond the initially represented task.
Research scenario · AI and plasma: forming a frontier inquiry
Measurements, simulations and model reasons help distinguish what is understood and what the inquiry needs to clarify. The method distinguishes the phenomenon’s model from observation conditions.
Facts, reasons and effects shape decisions before and during action. Results update understanding of the situation and how to act.
How the system connects decisions to consequencesNumbers: connections · Arrows: direction
Facts and reasons for a choice
The system’s decisions and actions
Consequences
1help make an informed choice2effects to evaluate and understand3feedback updates the system’s understanding
Explanation
Acting with an understanding of cause means understanding facts, reasons and consequences before and during action. The system grounds choices in understood and verified information, considers possible effects and recognises what it does not yet know.
An example
To choose between two manufacturing methods, technical data, criteria and expected consequences are compared. If a trial produces a new result, the system reconsiders the choice.
More detail
In light of a new fact, the system reviews the decision, the question and how to approach it. Understanding develops through exchanges between people, AI, sources and consequences. The system preserves the distinction between what happened, what it knew then and what it understands now.
It organises and carries out activities with pertinent competences, people and tools, including autonomously. It connects the objective to the contributions needed and the results of the work.
How the system organises workNumbers: connections · Arrows: direction
Knowledge and methods
The system
Activities to carry out
People and tools
1how to approach the work2organises and carries out activities3contribute to the work
The system carries out updates to the purchasing process
The understood activities become work on documents and tools, with contributions from the people responsible.
People, activities and purchasing tools
Company staffKnowledge and decisions within their responsibilities.
The system develops the revisionOrganises activities and prepares pertinent updates.
Documents and toolsProcedures and tools actually used in the company.
the work connects contributions, tools and results
In the work
The revision reaches the materials and activities involved.
The project continues from the present with the new agent
The system rereads preserved reasons alongside current facts and carries out pertinent activities.
Resumption, activities and new knowledge
Preserved pointStill-causal objectives, decisions and reasons.
Project presentNew facts, capabilities and conditions of the new environment.
The system continues the workIdentifies what needs doing and carries it forward.
resume from the updated present
In the work
The change of environment enters the continuation of the same project.
Explanation
The system understands what needs doing, organises activities and carries them out with people or autonomously. It uses its competences: knowledge, experience and methods for addressing work. It connects tools, people’s contributions and the results obtained.
An example
An order involves several departments and document revisions. The system connects activities to the decisions made and the contributions needed to carry them forward.
Same process · documents, criteria and activities
The purchasing process
The revision reaches the materials and activities involved.
The know-how
The system preserves why the changes were introduced.
Same project · different agents and tools
The project
The change of environment enters the continuation of the same project.
The know-how
The new agent’s experience refines the capability to continue the project in other contexts.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
The method takes shape from knowledge useful to the situation. The system combines available competences and develops others when needed. It reorganises activities through what it understands from results and consequences while work is in progress.
Illustrative case · Revising a purchasing process
The understood activities become work on documents and tools, with contributions from the people responsible. The system preserves why the changes were introduced.
Illustrative case · Continuing a project with a different agent or environment
The system rereads preserved reasons alongside current facts and carries out pertinent activities.
The system re-examines the preserved reasons alongside current facts and carries out the pertinent activities. The new agent’s experience refines the capability to continue the project in other contexts.
Responsibility and coherence in the system’s actions
It keeps the possibilities of the work open and corrects constraints it introduces through its own interpretation. It connects each concrete effect to intent, responsibilities and authorisations.
How the system protects possibilities, meaning and actionsNumbers: connections · Arrows: direction
Possibilities, sources and intent
The system understands and operates
Effects and responsibilities
1Through KA it understands without imposing its own patterns2Connects each effect to responsibilities and permissions3Through FDLA it corrects its interpretation and what follows
Explanation
How it works
The system keeps understanding, continuity of work and responsibility for actions connected. KA preserves possibilities beyond the AI’s schemas and assumptions. FDLA recognizes when the system’s interpretation shifts meaning, intent or the direction of the work and corrects it. Each concrete effect remains connected to responsibilities and authorizations.
What it is for
The system protects the project’s possibilities, fidelity to sources and intent, and responsibility for effects while understanding and carrying out the work.
An example
Before changing a project document, the system identifies the active version, the responsible person and the consequences of the change.
More detail
The system’s competences provide ways to recognise and address these situations. Continuity of knowledge preserves reasons and relationships needed to continue; KA and FDLA keep understanding and correction within the work. Before a concrete effect, such as changing or publishing a document, the system identifies the pertinent source, consequences and responsibilities.
It organises steps, chooses methods and tools and continues towards the objective. People collaborate, validate or monitor according to the work and responsibilities.
How the system carries work forward with situated autonomyNumbers: connections · Arrows: direction
Actual situation
The system at work
People and tools
Activities towards the goal
1Understands what to do and how2People teach, validate and monitor; tools provide the means3Organises, performs and continues without a command for every step
The system carries forward updates to the order
It compares versions, connects the affected activities and prepares updates. People contribute knowledge and decisions within their responsibilities.
Which work can the system carry forward?
People working on the orderContribute knowledge, clarifications and decisions within their responsibility.
The system at workCompares versions · connects affected activities · prepares updates.
Documents and toolsDrawings, the activity plan and the means actually available.
Contributions, activities and results remain connected.
In the work
Work proceeds without a command for every step, with people contributing when needed.
Explanation
How it works
Situated autonomy means acting with an understanding of the work and its actual conditions. The system organises activities, chooses tools and methods and continues towards the objective. In collaborative work, people contribute knowledge and reasons. At supervised points, they validate choices and results within their responsibility. When the system operates autonomously, they monitor its work and consequences. These forms combine according to the activity.
What it is for
The system carries activities and projects forward with awareness of causes and consequences, involving people, competences and tools according to the work and responsibilities involved.
An example
In document work, people explain sources and evaluation criteria to the system. The system prepares, compares and updates the materials; those responsible validate choices within their remit and follow the results of activities entrusted to it autonomously.
Variant requested · delivery date unchanged
The order
The system compares versions, connects activities and prepares updates.
The know-how
Delegation develops through people’s knowledge, decisions and feedback.
More detail
The next step also develops from what the system understands about the situation. Available capabilities, usable tools and current authorisations matter. An authorisation concerns a concrete action, such as sending or changing content.
Illustrative case · A customer order changes
The system carries activities forward using available competences and means. People contribute knowledge and decisions; delegation grows through shared work.
The system compares versions, reconstructs the activities involved and prepares updates using available competences and tools. People contribute where knowledge or decisions are needed. Delegation grows through shared work and understanding its consequences.
New understanding and experience become part of competences and their relationships. This knowledge also changes how to observe, pose questions and form further capabilities, already within the current work.
Knowledge also changes how the system knows and worksNumbers: connections · Arrows: direction
Experience and new understanding
Competences and their relations
How the system knows and works
1transforms know-how2changes observation, question and method3operation brings new knowledge into view
Work on the variant develops the system’s competences
The link between change, activities and checks becomes knowledge usable within the order itself. Experience also changes how the system forms and combines other capabilities.
What becomes reusable from this experience?
Acquired understandingConnecting a change with its effects on activities and checks changed the work.
A more capable competenceThe acquired method is available in the current work and subsequent orders.
integrate the know-how
In the work
What is understood also improves how competences are created and combined.
Purchasing experience improves the system’s method
Results of the revision become knowledge for addressing other requests and improving the process.
From the revision to reusable know-how
Understood experienceWhich changes made the process more appropriate.
Purchasing competenceIntegrates reasons and method into subsequent work.
integrate what the work has taught
In the work
Later requests meet an updated process and knowledge.
Revising the dossier develops the system’s competences
What the revision teaches enters the competence that prepares and updates other dossiers.
From the understood case to the practice’s method
Knowledge from the caseRelationships and reasons recognised during the revision.
A more capable competenceAddresses other dossiers through the knowledge now available.
let experience participate in the next work
In the work
Work continues with updated materials and accessible reasons.
Feedback changes the product’s competences
Understanding gained through use enters the capabilities through which the kernel operates in the service.
From usage experience to operational capability
Understood experienceRelationships emerging between decisions, use and consequences.
Kernel capabilitiesUse the new knowledge in subsequent activities.
integrate knowledge into product activity
In the work
The service continues with updated knowledge and methods.
Explanation
How it works
The system uses new understanding, emerging through work and interaction with people, to develop its competences, their relationships and how it forms others. This knowledge also changes which relationships the system observes, which sources it recognises as pertinent and how it formulates the question and method. The system integrates what it understands into the current activity and its own organisation for subsequent work.
What it is for
The system turns what it understands into capabilities available for current and subsequent work. Experience also changes how the system forms and combines competences.
An example
The system examines research documents, selecting them by topic. Feedback reveals that this selection leaves out a relationship between the phenomena. The system revisits the criterion, seeks sources from another perspective and reforms the question. The research competence integrates this new way of recognising what is pertinent.
Variant requested · delivery date unchanged
The order
Managing the variant now connects the drawing, activities and checks.
The know-how
Experience changes the competence and how others are formed and combined.
Same process · documents, criteria and activities
The purchasing process
Later requests meet an updated process and knowledge.
The know-how
Experience also changes how the system prepares the capabilities needed.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
The service continues with updated knowledge and methods.
The know-how
Learning can also change how the kernel forms other competences.
More detail
The system integrates what it understands into competences, their relationships and the organisation from which work continues. The autopoietic relation concerns this transformation of the operational form that makes further work possible. The autological relation concerns knowledge applied to its own way of knowing and forming capabilities: new understanding changes what to observe, which sources to recognise as pertinent and how to pose the question. These relationships act together as the question and method take shape. KA and FDLA keep possibilities, sources and correction within the movement.
Illustrative case · A customer order changes
Knowledge gained becomes reusable immediately and in subsequent orders. Successful results and new possibilities also evolve capabilities.
The connection between the change, activities and checks becomes reusable knowledge in the competence. The system uses it immediately and keeps it available for subsequent orders. New knowledge, successful results and possibilities evolve capabilities, including the ability to create and combine others.
Illustrative case · Revising a purchasing process
Results of the revision become knowledge for addressing other requests and improving the process. Experience also changes how the system prepares the capabilities needed.
Illustrative case · Updating a professional dossier
What the revision teaches enters the competence that prepares and updates other dossiers. The system also develops how specialist knowledge is organised.
Illustrative case · Evolving a product or service through use
Understanding gained through use enters the capabilities through which the kernel operates in the service. Learning can also change how the kernel forms other competences.
How the system understands, acts and develops its capabilities.
The kernel is the logic through which the system understands and works. The D-ND model provides the relations between possibility, movement and resultant: they take shape in competences and in how the system continues and changes.
The system exercises KA while understanding and acting. Through FDLA it recognises when its own interpretation alters the work, recovers lost relationships and corrects how it proceeds. These functions participate in the ongoing activities.
Founding principlesSystem capabilitiesWork and learning
How the system understands, acts and learns
Section topics
Principles and methods
01
The competences through which the system understands and works
Knowledge, reasons, methods and experience become know-how available for an activity. Using competences develops that knowledge and makes it usable in other situations.
How the system uses and develops a competence in the workAvailable competence and the situation shape the system’s action
Prepare to actAvailable competenceKnowledge, reasons, methods, experience.
When the capability is relevantPresent situationObjective and conditions of this case.
Express the capabilityThe system handles the workUses and develops know-how in the concrete case.
makes know-how available
makes the capability relevant
Understood consequences transform the competence.
Competence in variants becomes concrete work
The system uses prepared knowledge, technical reasons and methods to address the change under the conditions of this order.
How does the system use its prepared competence for changes?
Available competenceDesign changes, technical reasons and checks.
This design changeDrawing, objective and conditions of the order.
Address the actual casePrepared knowledge forms the appropriate action.
the situation makes the capability relevant
In the work
Prepared know-how becomes action within this order.
Explanation
How it works
A competence brings together knowledge, reasons, methods and experience through which the system understands and handles an activity. Preparation makes it available; in the work, that capability shapes action suited to the case. Results develop its knowledge and method.
What it is for
Competences make the system’s knowledge available and reusable in the work. They preserve the reasons behind the method and develop it through experience, reducing reconstruction and repetition.
An example
A competence for handling design changes brings together technical knowledge, reasons behind choices and ways to check their effects. When a change arrives for an order, this knowledge forms how to address that particular case.
Variant requested · delivery date unchanged
The order
The variant meets knowledge already prepared on technical reasons and checks.
The know-how
The available competence shapes how this particular case is addressed.
More detail
A competence contains the possibility of a movement: it understands how to approach a situation and forms the method needed. Its availability prepares action; the situation determines how it participates. In the D-ND model, the resultant changes the field from which work continues. In the system, what is understood transforms the competence and its relationships with others.
Illustrative case · A customer order changes
Prepared knowledge becomes action in the actual change and evolves through its consequences.
The competence for changes is formed even before this request. It brings together knowledge, reasons and methods. When the change arrives, the situation makes that capability pertinent: the system understands the case, forms the appropriate method and learns from consequences.
Existing knowledge, frameworks and tools contribute to the work without exhausting its possibilities. Sources, facts and relationships also shape the question and method.
The system understands the work beyond its existing frameworksSources and relationships shape the work beyond existing knowledge and means
Shape the workSituation, intent and possibilitiesRelevant facts, sources, relationships and competences.
Contributes to reasoningInterpretation of the situationUnderstanding based on knowledge and means already available.
Forms the question and actsUnderstands and actsSources and relationships in the situation shape question, method and action.
Through KA, the system examines the change beyond the drawing alone
It initially considers updating only the drawing. The order’s purpose, sources and conditions guide the system to understand the effects of the change on other activities as well.
What does the system understand beyond the idea of updating the drawing?
Purpose, sources and the situation guide understanding, method and action.
Understand the requestWhat the customer wants to achieve and what changes in the order.
Form the methodWhich knowledge, competences and means make the work possible.
Choose and actCarry out what emerges from understanding the situation.
In the work
A familiar method remains a possibility: its limits do not become the limits of the work.
Through KA, the system develops the project beyond the initial idea
It uses already-known ideas and means to explore the organisation’s work. The sources and relationships it understands also change the project to develop.
Which possibilities does the system understand beyond the first project idea?
the initial representation participates without exhausting the field
First project ideaAn initial contribution to understand in context.
Recovered relationshipsSources, knowledge and possibilities made pertinent through work.
Project taking shapeQuestion and method change through understanding.
In the work
The project incorporates emerging relationships instead of remaining bound to its first form.
Research studies how KA participates in cooperative work
The two agents work on the requested component, each with its own sources and competences. Research studies how they understand the conditions without reducing cooperation to their initial interpretation.
Tasks, understanding and possibilities of the relationship
the method participates in action while the relationship forms
Participants’ tasksAgents continue their own work.
Understood sources and conditionsCompetences give meaning to what happens.
Agreement, dissent or a new questionThe resultant emerges from work and changes what follows.
In the work
Cooperation determines what follows through what happens in the work.
The system chooses how to explain a concept
Guide the choice of formMeaning and what the reader needs to understand
Remains one possibilityThe diagram the system already knows
Chooses or creates the formHow to explain the conceptIt uses the diagram, modifies it or finds another form suited to the concept and the reader.
Explanation
How it works
KA is the Kernel Assiomatico, the axiomatic kernel: the logic the system exercises through its competences while understanding and acting. The system’s interpretation of a situation draws on available knowledge, frameworks and means. This understanding is partial: its sole cognitive constraint is not to turn it into a limit on the possibilities of the work. The system follows sources, facts, intent and relationships to develop the question, method and action as well.
What it is for
KA keeps the system’s reasoning and action free beyond its own interpretation of the situation. The system uses available knowledge and tools and develops what the work needs, without imposing their limits on the situation.
An example
The system needs to explain a concept to someone unfamiliar with it. A familiar diagram is one possibility, but it does not exhaust the concept. Meaning from the sources and what the reader needs to understand guide the choice: the system can use that diagram, change it, choose a dialogue or create another form. Understanding shapes the way of explaining.
Variant requested · delivery date unchanged
The order
The work includes the effects of the variant beyond the drawing alone.
The know-how
The system uses the initial idea without treating it as the boundary of the work on the change.
Open field · intent, knowledge and possibilities
The emerging project
The project incorporates emerging relationships instead of remaining bound to its first form.
The know-how
The system develops knowledge for recognising and realising pertinent possibilities.
Independent agents · evolving tasks, boundaries and capabilities
The cooperation
Cooperation determines what follows through what happens in the work.
The know-how
Research observes how understanding and capabilities transform within the relationship.
More detail
Knowledge, schemas and tools show parts of a situation. The system lets sources, competences and new relationships change even the question it is asking and how it approaches it. KA is exercised while those competences operate. A solution that emerges becomes part of what follows: the system acts and continues from what it has accomplished.
Illustrative case · A customer order changes
The system understands the effects of the change beyond updating the drawing. The order’s purpose, sources and conditions also shape the question, method and action.
In the illustrative case, the system initially considers updating only the drawing. Through KA it keeps the work’s possibilities open beyond this idea: it understands the effects of the change on other activities and uses or develops the pertinent method. The system puts the decision emerging from this understanding into action.
Illustrative case · Forming an AI project still to be defined
The system uses already-known ideas and means to explore the organisation’s work. The sources and relationships it understands also change the project to develop. The system develops the knowledge through which it recognises and realises pertinent possibilities.
Research scenario · Cooperation that develops agents’ capabilities
The two agents work on the requested component, each with its own sources and competences. research studies how the participants’ understanding and capabilities transform through cooperation.
The two agents work on the requested component, each with its own sources and competences. Research studies how they understand the conditions without reducing cooperation to their initial interpretation. It observes how the participants’ understanding and capabilities transform within the relationship.
FDLA: how the system corrects its own understanding
It recognises constraints it introduced into its own interpretation, recovers lost relationships, and changes its choice, method and action from the updated understanding.
The system corrects its interpretation and chooses from updated understandingThe system chooses from its updated understanding of the situation
Recovers what remains validIntent, sources and valid relationshipsThe objective, sources and reasons remain recognisable.
Understands what changesNew facts and relationshipsFacts and consequences bring new information about the situation.
Reexamines the situationThe system corrects its interpretationIt releases constraints it introduced and recomposes its understanding.
Chooses from the updated presentChanging decisions and workUseful knowledge enters competences through Meta_Skill.
Through FDLA, the system corrects its own interpretation of the change
It recognises the limit of “just update the drawing”. It preserves valid reasons and includes assembly and checks in the understanding from which it chooses again.
How does the system reconsider the change after understanding its effects?
Still-valid reasonsThe purpose and conditions of the order.
An understood consequenceThe change affects assembly and checks.
The system updates its understanding of the changeThe system recognises that “just update the drawing” excluded assembly and checks, and chooses again.
recover and recompose
In the work
The choice now also includes assembly and checking activities; reusable knowledge gained changes the competence.
FDLA changes the solution when a result changes understanding
A result reveals a limitation in an initial decision. The system recovers lost relationships and reshapes method and implementation.
Valid reasons and new understanding of the software
Purpose and valid reasonsWhat the project must continue to accomplish.
Understood resultA result reveals a relationship that the system initial solution had excluded.
The system revises the solutionNew understanding changes the decision, code and method.
recompose the problem during development
In the work
The correction reaches the part of the application that must change.
The system revisits its understanding of the cooperation conditions
A condition acquires a different meaning. The system recovers valid reasons and recomposes the understanding from which to decide how to continue.
Valid reasons and a changed condition
Owners’ intents and reasonsParticipants’ still-valid positions.
Newly arrived informationChanges what a condition means in the work.
The system recomposes understandingWhat follows incorporates newly understood relationships.
The system corrects its own interpretation while cooperation continues
In the work
The relationship can continue, be reformulated or conclude with a coherent refusal.
The system connects the result to revising the plasma hypothesis
A result changes what the group understands about the phenomenon or how to observe it. The system connects the new information to the model’s reasons to continue the investigation.
Model reasons and an understood difference
Still-valid reasonsKnowledge and relationships supported by the work.
Difference in the resultsWhat changes understanding of the phenomenon or its observation.
Reshaped hypothesis and methodThe group continues from newly understood relationships.
integrate the consequence into continuing research
In the work
The inquiry continues with updated hypotheses, questions and reasons.
The system corrects text and diagram while preparing the explanation
Preserves what remains validThe goal and meaning of the sources
The system recognizes the limitationThe pattern has left out a relationshipIts own representation is partial.
Understands anew from what emergesThe concept reread with the recovered relationshipReshapes the way of explaining.
Chooses and changes the workText, figure and how explanations are preparedCorrects the explanation and carries useful knowledge forward.
Explanation
How it works
FDLA is the Funzione di Libero Arbitrio, the free-will function through which the system re-examines its own interpretations and releases constraints it has introduced into the work. The system recovers lost relationships, preserves valid ones and integrates what the consequences help it understand. Following KA, the system uses this updated understanding to choose again and change question, method and action while working.
What it is for
Through FDLA, the system frees its decisions from constraints it has introduced and changes how it understands and acts, following KA.
An example
The system prepares an explanation and recognizes that its chosen pattern has left out an important relationship in the sources. It preserves the goal and what remains valid, rereads the concept, and changes the text and figure before presenting them. The recovered relationship also changes how it prepares later explanations. A reader’s question or an unexpected result can reveal other relationships and let this recomposition continue.
Variant requested · delivery date unchanged
The order
Assembly and checking activities enter the revised decision.
The know-how
The system loosens the conditioning of “just update the drawing” and integrates reusable knowledge.
Same software project · problem, code and results
The application
The correction reaches the part of the application that must change.
The know-how
The competence integrates the relationship lost by the first solution.
Independent agents · evolving tasks, boundaries and capabilities
The cooperation
The relationship can continue, be reformulated or conclude with a coherent refusal.
The know-how
Research distinguishes method evolution from the partner’s consent, private data and authority.
Physical-computational research · questions, models and observations
The plasma inquiry
The inquiry continues with updated hypotheses, questions and reasons.
The know-how
Research also develops how pertinent observations and competences are chosen.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
The system exercises FDLA while forming a decision: it keeps people’s intent, the meaning of sources, the object of the work and the consequences of its own actions connected. The system distinguishes what happened, what it understood then and what it understands now. A consequence can reveal an existing relationship or create a new one. The system continues from its updated understanding of the situation and integrates reusable knowledge into its competences through Meta_Skill.
Illustrative case · A customer order changes
The system recognises that the idea “just update the drawing” had excluded the effects of the change on assembly and checks. It preserves the objective and valid reasons, understands these effects and chooses again.
The system recognises that its initial interpretation had restricted the work to the drawing. Through FDLA it preserves the objective and still-valid reasons and integrates the understood effects on assembly and checks. The system uses this updated understanding to change its decision and integrates reusable knowledge into the competence that will work next.
Illustrative case · Developing an application that continues evolving
A result reveals a limitation in an initial decision. The system recovers lost relationships and reshapes method and implementation. The competence integrates the relationship lost by the first solution.
Research scenario · Cooperation that develops agents’ capabilities
A condition acquires a different meaning. The system recovers valid reasons and recomposes the understanding from which to decide how to continue. Research distinguishes method evolution from the partner’s consent, private data and authority.
Research scenario · AI and plasma: forming a frontier inquiry
A result changes what the group understands about the phenomenon or how to observe it. The system connects the new information to the model’s reasons to continue the investigation. The group also develops how it chooses pertinent observations and competences.
Consequences change how the system’s work continues
A result or new fact changes the activities, documents and competences that depend on it. Valid reasons and understood changes shape how to continue.
The system connects acquired knowledge to new factsThe system continues from valid reasons and understood changes
What sustains the workPrinciples and acquired knowledgeSources, reasons and understood relations.
What changes the situationNew facts and consequencesThe system reconsiders the question in light of new facts.
A coherent continuationDecisions, activities and competencesThe system updates what depends on the understood difference.
give reasoning continuity
change the situation in which the system continues
Results and understood relationships update the system’s knowledge.
New understanding changes how the order continues
The correction reaches the documents, competences and activities involved. Understood relationships and still-valid reasons remain available for continuing.
How does new understanding change how the order continues?
Still-valid reasonsObjective, sources and choices already understood remain available.
Understood consequenceThe change also affects assembly and verification.
Continuing the orderThe system connects the updates to the activities, documents and people involved.
results and understood relationships change the order’s situation
In the work
Understanding reaches the work that depends on it and remains available for continuing.
Explanation
How it works
Each action and result changes the situation in which the system continues working. The system follows these consequences through the decisions, activities and competences involved, keeping reasons and sources connected. An understood difference also changes what depends on it.
What it is for
The system carries an understood consequence into the activities, documents and competences that must change. As it continues, it preserves valid reasons and integrates what has happened.
An example
A design change requires another assembly check. The system links this consequence to the activities, documents and people involved. Still-valid reasons remain available; the work continues from what the change has made understandable.
Variant requested · delivery date unchanged
The order
The correction reaches the documents, competences and activities that depend on it.
The know-how
The relationships understood remain available to decide what follows.
More detail
In the D-ND model, the resultant forms the following field. The system preserves understood relationships and uses them in new choices. KA keeps possibilities open; FDLA recognizes constraints introduced by its own interpretation and recomposes what follows. Noise is reduced by recognizing which information and differences change the work. Available reasons reduce the need to reconstruct context and repeat processing.
Illustrative case · A customer order changes
New understanding connects to valid reasons and changes how the order continues. Understood relations remain available.
The correction reaches beyond the drawing. What has become understood changes the order’s situation: the system retains valid reasons and connects consequences to the competences, activities and documents involved. This reduces repeated reconstruction of the same relations.
Meta_Skill: how the system forms and develops competences
The system recognises, combines and develops know-how. New understanding also changes its questions, pertinent sources and how it forms further capabilities.
The system forms competences and learns from their use through Meta_SkillNumbers: connections · Arrows: direction
Knowledge, intent and experience
The system forms competences
Know-how used and evolved
1Contribute to forming capabilities2Recognizes, creates and develops know-how3Work also changes how competences are formed
Meta_Skill forms capabilities to manage the variant
The order needs technical and organisational knowledge together. The system identifies pertinent competences, combines them and forms the missing ones.
Which know-how is needed to handle the change?
Technical knowledgeThe component, assembly and checks.
Organisational knowledgeActivities, people, timing and decisions.
The ability to handle the changeThe system combines knowledge and forms what is missing, including before the activities begin.
combine and form
In the work
The resulting competence shapes how this order is approached.
Meta_Skill forms the new kernel’s capabilities
The system makes available knowledge pertinent, combines competences and develops those needed by the group.
Knowledge and capabilities for the group’s kernel
Available competencesReusable knowledge, methods and experience.
The group’s situationsWhat the system needs to understand and address.
The system forms situated capabilitiesOrganises knowledge and forms pertinent competences.
combine and form pertinent know-how
In the work
The new kernel has knowledge and methods for operating in context.
The system forms capabilities for the work that has emerged
New understanding makes competences pertinent for composition or development. The project and how to address it take shape together.
Understanding and capabilities for realising the project
Recognised workQuestion, relationships and reasons emerging through exploration.
Knowledge to bring into the workAvailable capabilities, combinations and new competences.
The system realises the projectForms the method and carries forward pertinent work.
form the capability together with the project
In the work
Exploration continues in a project with pertinent knowledge and capabilities.
Explanation
How it works
Meta_Skill recognises pertinent capabilities, brings them into the work and combines them. It forms and develops competences through knowledge, intent, teaching, experience and possibilities. New understanding also changes how the system selects sources, forms questions and generates further capabilities.
What it is for
The system develops the capabilities needed for the work it encounters and the possibilities it recognises. The system prepares competences before an activity as well and evolves them while using them.
An example
The system connects design, production and verification contributions to address a change. The work reveals which relationships between drawings, assembly and checks affect the choice. It integrates that knowledge and method into the relevant competences and uses them in the next change. Experience also refines how it recognizes and forms the capabilities needed. The acquired understanding also changes which sources to consult and which questions to ask in the next situation.
Variant requested · delivery date unchanged
The order
Assembly, checks, people and timing participate in managing the variant.
The know-how
The system combines technical and organisational knowledge and forms the missing capabilities.
Same group · requests, knowledge and capabilities
The group’s kernel
The new kernel has knowledge and methods for operating in context.
The know-how
Formation experience refines how other systems are prepared.
Open field · intent, knowledge and possibilities
The emerging project
Exploration continues in a project with pertinent knowledge and capabilities.
The know-how
What the work teaches also develops how other possibilities are formed.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
A competence can also emerge and develop from acquired knowledge, successful experience, intent and possibilities. A combination of competences can remain temporary or form its own knowledge and continuity. In the autological relation, acquired knowledge also changes how the system observes, recognises the pertinence of sources and forms the question. When it concerns formation itself, it also transforms the generative faculty: the system revisits how it learns from examples and forms further capabilities while work takes shape. Meta_Skill integrates this understanding into the capabilities involved and how others are created and combined.
Illustrative case · A customer order changes
Meta_Skill brings technical and organisational knowledge together. It forms the capability needed even before the activity and develops it through results.
The change requires technical and organisational knowledge together. Meta_Skill recognises and combines pertinent competences and forms those needed, even before activities begin. The capability formed is used in work and evolves through results.
Illustrative case · Forming a kernel for a group’s work
The system makes available knowledge pertinent, combines competences and develops those needed by the group. Formation experience refines how other systems are prepared.
Illustrative case · Forming an AI project still to be defined
New understanding makes competences pertinent for composition or development. The project and how to address it take shape together. What the work teaches also develops how other possibilities are formed.
When resuming an activity, it re-examines decisions, reasons and methods in light of current facts. This knowledge accompanies the work when agents or tools change as well.
How the system resumes work from knowledge and updated factsNumbers: connections · Arrows: direction
Knowledge, reasons and methods
Present situation and changes
Understands and continues
1remain reachable2shape what follows
The system resumes the order from updated facts
Decisions, reasons and open activities meet a new piece of test data. The system rereads the preserved point and understands how to continue in the present.
How does the system resume the order after a pause?
The preserved pointDecisions, reasons and open activities.
The present on returnA new test result.
An updated continuationThe system rereads the reasons with the new facts and continues from the relevant point.
reread in the present
In the work
What remains valid is retained, and what needs to change is understood.
The system resumes development from reasons and present facts
In the next session the system recovers decisions and open activities, rereading them in light of changes.
Preserved point and current project context
Preserved development pointCode, decisions, reasons and open activities.
Current project contextResults and conditions that have changed meanwhile.
The system continues developmentFinds the pertinent work and updates how to address it.
continue from the point reread in the present
In the work
The project continues with its code and still-valid reasons.
Functions, reasons and feedback remain accessible when work resumes or changes form.
Preserved knowledge and a new revision
Useful product historyStill-pertinent decisions, reasons and feedback.
Present conditionsNew needs and tools of the revision.
The system shapes what followsConnects operational knowledge to the current revision.
maintain continuity across revisions
In the work
The new revision preserves valid reasons and incorporates what has changed.
The system preserves the point from which the project continues
Sources, decisions, reasons and open activities make work resumable beyond a single conversation.
The project beyond a single conversation
Project knowledge and reasonsWhat supports still-valid decisions.
Present activities and resultsWhat has been accomplished and what work remains open.
The system maintains the useful pointConnects accumulated knowledge to continuing work.
preserve the relationship that makes resumption possible
In the work
The project has a resumption point understandable from its sources.
Explanation
How it works
The system keeps knowledge, decisions, reasons and methods reachable. On returning, it rereads them in the present situation and in light of changes, understanding where and how to continue. The same body of knowledge accompanies work when the agent or application changes, through the capabilities and means of the new environment.
What it is for
The system maintains continuity of work by connecting knowledge, reasons and decisions to the current situation and changes that have occurred. This knowledge enables it to continue with different means as well.
An example
After a pause, project requirements change. The system recovers earlier decisions and their reasons, understands the change and reorganises the work to continue.
Variant requested · delivery date unchanged
The order
The order resumes from the reasons preserved and a new piece of test data.
The know-how
The system rereads the work in its present context and updates the question, method and pertinent capabilities.
Same software project · problem, code and results
The application
The project continues with its code and still-valid reasons.
The know-how
The developed method remains available for the project’s continuation.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
The project has a resumption point understandable from its sources.
The know-how
Continuity concerns knowledge and reasons as well as preserved materials.
More detail
The continuum is the continuity of relationships that make it possible to understand and act from the transformed present, beyond conversation memory or exported files. The system reviews the question, method and capabilities needed through what has changed. Freedom to change provider or model takes shape by recovering and making this knowledge operational in the new environment, with its own tools and permissions. When the kernel participates in a product or service, continuity also extends to the work after delivery.
Illustrative case · A customer order changes
Work resumes from preserved reasons and new facts. The system understands what remains valid and what needs to change.
On returning, the system recovers decisions, reasons and open activities. A new test result participates in current understanding: the system reviews the question, method and capabilities needed in light of what has changed. Work continues from the updated point, preserving reasons that remain valid.
Illustrative case · Developing an application that continues evolving
In the next session the system recovers decisions and open activities, rereading them in light of changes. The developed method remains available for the project’s continuation.
Illustrative case · Evolving a product or service through use
Functions, reasons and feedback remain accessible when work resumes or changes form. Developed knowledge continues in the product and the work that evolves it.
Illustrative case · Continuing a project with a different agent or environment
Sources, decisions, reasons and open activities make work resumable beyond a single conversation. Continuity concerns knowledge and reasons as well as preserved materials.
The system in available products and the kernels it forms
MAIOS Project Kernel (MPK) brings the kernel into a working environment; kernel_chat into conversations. The system forms kernels for projects and domains; knowledge they make reusable develops the shared competences.
The system supports projects and develops the knowledge it receives from their workNumbers: connections · Arrows: direction
System and shared competences
MPK and kernel_chat
Kernels for projects and domains
1Its logic operates through these incarnations2Forms the kernel and supports the project’s competences3Knowledge made reusable develops the shared competences
The formed kernel continues developing through its own work
The transferred capability also includes the method for developing knowledge and competences through activity.
From the generative system to the situated kernel
The system forms operational knowledgeMakes contextual principles, knowledge and methods accessible.
The kernel works with the groupUses and develops capabilities through its own activity.
also transmit the capability to develop the method
In the work
The group works with a kernel capable of developing its own know-how.
The new agent uses project knowledge in its own environment
The new agent interprets the project’s knowledge and exercises it with the capabilities, tools and access available in its own environment.
Project knowledge in the new the system environment
Transferable knowledgeKnowledge, principles and reasons useful to the project.
New environmentCapabilities, access and tools actually present.
The agent shapes how to operateThe agent uses the knowledge with the tools and access of the new environment.
the agent adapts how it works while preserving the meaning of transferred knowledge
In the work
Work has an operational form suited to the new environment.
Explanation
How it works
The system is a result of research, a system already used in work and a product offered through its incarnations. It forms competences and other situated kernels, carrying the knowledge and methods through which they operate and evolve in their own contexts. MAIOS Project Kernel (MPK) is an installable incarnation; kernel_chat makes the logic operational in conversations with AI. The system’s competences support the project’s work. Knowledge that the project makes reusable develops those competences and the method used to approach other work.
What it is for
The system makes its capabilities operational in the work and forms systems for projects, domains and organisations, with knowledge, methods and continuity pertinent to the context.
An example
A group wants to understand and manage incoming requests. The system forms a small domain kernel: it connects the group’s sources, methods for understanding requests and reasons behind decisions. The kernel develops its competences through its work; what is learned about formation also improves how the system prepares other systems.
Same group · requests, knowledge and capabilities
The group’s kernel
The group works with a kernel capable of developing its own know-how.
The know-how
What is understood while forming this kernel can improve the system’s generative method.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
Work has an operational form suited to the new environment.
The know-how
Knowledge remains distinguishable from a particular tool topology.
More detail
Knowledge, principles and methods expressed in natural language are working knowledge: the agent interprets and exercises them with the people, sources and means of the context. When forming another kernel, the system understands what the recipient needs to know, do and retain. It makes that knowledge reachable, together with the ability to develop it through work. The generative method itself becomes working knowledge in the resulting system. Public incarnations and new systems retain their own identity and means. The project makes pertinent knowledge reusable through the competences that need to exercise it. Its reasons and original context accompany that knowledge into the system and subsequent work.
Illustrative case · Forming a kernel for a group’s work
The transferred capability also includes the method for developing knowledge and competences through activity. What is understood while forming this kernel can improve the system’s generative method.
Illustrative case · Continuing a project with a different agent or environment
The new agent interprets the project’s knowledge and exercises it with the capabilities, tools and access available in its own environment. Transferred knowledge and reasons remain distinguishable from the particular tools used for the work.
People contribute intent, knowledge and decisions; the system connects sources and capabilities and carries out activities. Chat, documents, screens and commands support discussion of the results and method.
People and system shape the work togetherNumbers: connections · Arrows: direction
People and goals
The system, knowledge and tools
Work and understanding
1interact through interfaces2act in the real work3feedback changes what follows
People and the operational kernel participate in service evolution
Interaction connects people’s knowledge, kernel activities and service tools.
People, integrated kernel and service tools
Users and responsible peopleExperiences, knowledge and contextual decisions.
operational kernel in the serviceUnderstands feedback and carries forward pertinent activities.
Service toolsDocuments, data and tools of the actual product.
use participates in shaping what follows
In the work
Evolution activities remain connected to those using and managing the service.
Explanation
People participate with intentions, knowledge, decisions and responsibilities. The system connects sources and capabilities, carries out activities and brings results into the exchange. Through chat, documents, screens and commands, this interaction shapes goals, understanding and method as work takes form.
An example
A team designs a service with the system. People bring needs and experience; the system connects sources, proposes activities and carries them out. Feedback from users changes shared understanding and the work that follows.
Same product · development, use and continuation
The product and service
Evolution activities remain connected to those using and managing the service.
The know-how
Interaction develops the kernel’s operational knowledge.
More detail
Chat, documents, commands and representations enable people to understand and participate in AI work. UX-AI attends to this mediation between understanding and action: questions, choices and results participate in transforming the context, method and possibilities of shared work.
Illustrative case · Evolving a product or service through use
Interaction connects people’s knowledge, kernel activities and service tools. Interaction develops the kernel’s operational knowledge.
How the system participates in the activities of companies, professionals, research groups and education.
The system’s works with the knowledge, people, processes and tools of a company or sector. Activities and capabilities needed depend on the concrete case.
The scenarios explain how the system participates in work. Examples illustrate possible cases to understand and develop in the actual situation.
People and knowledgeActivities to carry outProcesses and tools
The system operates within real work
Section topics
Operational scenarios
01
The system in company processes
It connects documents, knowledge, tools and people’s contributions to carry out activities and develop processes, products and services. Shared work also evolves the method.
The system’s works within organisational processesNumbers: connections · Arrows: direction
People, sources and tools
The system develops processes, products and services
Results and new knowledge
1Goals, contributions and responsibilities participate in work2Performs activities and produces results3The system integrates what it learns into its method and subsequent activities
The variant connects work across company departments
The system connects engineering, purchasing, production and quality. Updates, reasons and developed capabilities support the work that continues with people.
How does this ability connect with the company’s work?
The same change relates different contributions and activities.
EngineeringRequirements and drawings.
PurchasingComponents and availability.
ProductionAssembly and activities.
QualityCriteria and checks.
In the work
The prepared change makes updates, reasons and continuing work understandable to the people involved.
The system examines a purchasing procedure
Purchasing activities
Procedure to examine
Documents and criteria
1how work happens today2information used to decide
Explanation
In an organisation, the system participates in processes: it connects documents, knowledge and tools and carries out activities with people or with situated autonomy. People contribute goals, experience, decisions and responsibilities. Together they develop processes, products and services, evolving the method through work.
An example
To examine a purchasing procedure, the system starts from how work happens today, the documents used and the choice criteria. It understands which interventions are needed and carries them forward.
Variant requested · delivery date unchanged
The order
The same variant connects engineering, purchasing, production and quality.
The know-how
The result includes updates, reasons and capabilities through which the work continues.
From the case to the system’s possibilities
This case shows work in a company. The system also forms competences and kernels for other contexts; research explores its functioning and generative capabilities.
Work connects leadership, organisation and daily operations. Collaboration takes shape through available capabilities, the willingness to use them and the responsibilities each participant assumes. The organisation sustains the process with people, information and real means; results and new knowledge shape what follows.
Illustrative case · A customer order changes
Work begins with an actual company activity. Sources, people and tools participate in forming capabilities and in the work the system takes on.
The case spans technical, organisational and operational contributions from the same organisation. The system understands their relationships, carries pertinent activities forward and develops useful know-how. Work begins with an actual company activity, with its sources, people and tools, and delegation grows through experience.
It follows the effects of decisions across industrial activities. A kernel integrated into a product or service participates in its evolution through feedback from use.
The system develops products and services and continues when it is an operational part of themNumbers: connections · Arrows: direction
People, knowledge and means
The system develops the product or service
Kernel operating within the product or service
Feedback from use and maintenance
1Participate in design, production and quality2The kernel continues within the work when it is an operational part of it3The system uses feedback to review the product and method
The product provides new information during use
Design decisions meet usage conditions, maintenance and people’s feedback.
Product knowledge and usage feedback
Product knowledgeFunctions, technical decisions and project reasons.
Usage experienceFeedback and conditions encountered after delivery.
The system connects the effectsUnderstands which activities and knowledge to revise.
read use through the project and new facts
In the work
Relationships to revise in the product or service become recognisable.
The system follows the effects of a component change
Design change
Manufacturing
Quality checks
Documents
1what changes in manufacturing?2what changes in the checks?3what changes in the documents?
Explanation
The system connects technical knowledge, decisions and consequences across design, production, quality and maintenance. It participates in developing products and services with the people, data and tools of the context, following how decisions affect other activities. When the kernel is an operational part of the product or service, it contributes to its evolution after delivery through feedback from use.
An example
A product component changes. The system examines manufacturing activities, quality checks and documents to update. If the kernel is part of the maintenance service, feedback from use also informs subsequent revisions.
Same product · development, use and continuation
The product and service
Relationships to revise in the product or service become recognisable.
The know-how
Project reasons are enriched by usage experience.
More detail
The kernel contributes to creating a product or service and continues in its evolution when it becomes an operational part of it. Knowledge, reasons for choices and capabilities stay connected to the work that formed them. After delivery, the system uses maintenance results to review the product and the method used to develop it, through the actual means and responsibilities.
Illustrative case · Evolving a product or service through use
Design decisions meet usage conditions, maintenance and people’s feedback. Project reasons are enriched by usage experience.
It connects sector knowledge to the situation of the shipyard and vessel, from design to support. The work develops the capabilities used.
Kernel Nautico develops its knowledge through work in the shipyardNumbers: connections · Arrows: direction
Nautical knowledge and shipyard
Kernel Nautico works on the vessel
Experience and new capabilities
1Knowledge and conditions orient action2Activities yield results and experience3Acquired knowledge changes activities and method
Explanation
Kernel Nautico brings the system logic into the nautical sector: design, construction, testing and support. It connects sector knowledge to the situation of the shipyard and individual vessel. What work teaches improves the capabilities used in activities.
An example
An outfitting variant is examined in relation to design, construction, testing and support. A test result updates what the system knows and how it continues the work.
More detail
General nautical knowledge, the shipyard’s organisation and the vessel’s conditions participate in the same activity. Experience is preserved in competences: knowledge and methods used for work that continue to improve through work.
The system in software development and agentic systems
It understands the problem, designs solutions and writes code with available tools. It uses results and corrections to develop knowledge and methods.
The system develops software and updates its competencesNumbers: connections · Arrows: direction
Knowledge and method
The system designs and writes code
Software, results and corrections
1guide development work2Produces software and results to verify3Work updates competences and method
The system designs and writes the software
It develops the solution with project competences and tools, bringing results into discussion with people.
People, code and development tools
Project participantsObjectives, use and pertinent decisions.
The system develops the softwareDesigns, writes code and integrates work results.
Development environmentCode, documentation and available tools.
develop functions in the project context
In the work
The application takes shape through code and reviewable results.
Explanation
An agentic system is AI that organises and carries out activities using available tools. In software development, the system understands the problem, designs solutions and writes code. It uses results and corrections to improve knowledge and methods, preserving the reasons behind choices.
An example
Application development spans several sessions. The system recovers why a particular software structure was chosen and revises it if a new result changes the problem.
Same software project · problem, code and results
The application
The application takes shape through code and reviewable results.
The know-how
Reasons for decisions accompany the implementation.
More detail
Work includes understanding the problem, designing, implementing and checking according to the situation. The system immediately integrates what it learns into the method and keeps it available for other developments, together with decisions and their reasons.
Illustrative case · Developing an application that continues evolving
The system develops the solution with project competences and tools, bringing results into discussion with people. Reasons for decisions accompany the implementation.
It uses documents, information and specialist methods to understand cases, prepare materials and carry out the practice’s activities. It integrates results into knowledge useful for subsequent work.
The system performs specialist work and develops the methodNumbers: connections · Arrows: direction
Documents, rules and responsibilities
The system performs the work of the practice
Materials, results and specialist knowledge
1The system uses sources and criteria for the case2Prepares materials and carries activities forward3Integrates results into the specialist method
The system prepares the revised dossier with reasons for the changes
Understood differences enter the practice’s materials through pertinent competences and tools.
From compared sources to the updated dossier
Understood sourcesFacts, references and differences to integrate.
Specialist methodCriteria and reasons specific to the practice’s work.
The system develops the dossierUpdates the content and makes the reasons for changes understandable.
put the case revision into practice
In the work
The practice has the revised dossier and reasons for its revision.
The system updates the dossier and explains the changes
Dossier documents and sources
The system compares and revises
Updated dossier and reasons for the changes
1Sources and documents guide the revision2Prepares the revised dossier and makes the reasons readable
Explanation
The system’s works with the documents, information and activities of a professional context. It uses and develops useful knowledge and methods to understand cases, prepare materials and carry work forward with available tools.
An example
A practice revises a dossier. The system compares relevant documents and sources, identifies what needs updating and prepares the revised dossier with the reasons for the changes. What the case teaches becomes part of the method used for later dossiers.
Same dossier · updated sources and versions
The dossier
The practice has the revised dossier and reasons for its revision.
The know-how
Specialist knowledge develops through the actual revision.
More detail
Sector rules, confidentiality and people’s responsibilities participate in the actual work. The system uses results to improve the specialist method and the knowledge the practice reuses in subsequent cases.
Illustrative case · Updating a professional dossier
Understood differences enter the practice’s materials through pertinent competences and tools. Specialist knowledge develops through the actual revision.
It connects sources, observations, experiments and hypotheses; it prepares teaching materials and activities. Results develop knowledge, questions and the working method.
The system connects research, education and resultsNumbers: connections · Arrows: direction
Documents, experiments and hypotheses
The system with researchers and learners
Materials, activities and understanding
Results and new questions
1Connects sources, observations and explanations2Makes knowledge usable and prepares activities3Reviews knowledge, questions and ways of continuing
The system connects documents and experiments to discuss research
Documents and experiments
Hypotheses and changes
Knowledge to discuss
1The system connects data and explanations2preserves results and reasons
Explanation
The system connects documents, observations, experiments and research hypotheses. In education it makes knowledge understandable and usable and prepares materials and activities. It uses results to review knowledge, questions and how to approach them.
An example
A laboratory connects documents, experiments and hypotheses, preserving why explanations were revised. Results become material to understand and discuss during training.
More detail
Researchers and learners have their own needs and methods. The system uses capabilities useful to the situation and integrates what is understood into the research question and how to continue educational work.
Research into the system’s logic and new capabilities
Research and future perspectives
This area, briefly
Sources, experiments and counterchecks lead to new questions. Research studies how this understanding changes capabilities and methods.
Research connects the study of the system’s logic with laboratory work. Results and counterchecks reveal which questions and methods to revisit and how to develop new capabilities.
Scientific work distinguishes observed capabilities from possibilities to study. New questions develop through sources, experiments and evidence.
System logicNew capabilitiesFuture work
Questions about operation and evolution
Section topics
Research
01
SSK: research on the logic of the system
It studies how the meaning of information connects with action and learning. The System Semantic Kernel (SSK) paper develops its scientific description.
SSK studies and describes the system’s logicNumbers: connections · Arrows: direction
The system in operation
Research into the system’s logic
SSK scientific description
Pertinent reasoning and evidence
1Observation brings questions and information2Develops definitions and arguments3Each proposition requires its own evidence
Two agents address work for independent owners
One agent seeks a component; the other has production information. Research considers participants’ tasks, sources, intents and authority together.
Participants and cooperative relationship
cooperation meets distinct sources and authority
Requester’s agentIts owner’s task, sources and intentions.
Producer’s agentKnowledge and information with their own ownership.
Shared work and conditionsWhat participants understand and determine within the relationship.
In the work
The inquiry has a concrete object: the relationship forming while the two agents work.
SSK studies what the system preserves when tools or its environment change
Meaning of choices
Way of representing
Tools used
Work environment
1when representation changes?2when tools change?3when the environment changes?
Explanation
Research underlying the system studies the logic connecting the meaning of information with actions and learning. The System Semantic Kernel (SSK) project develops a scientific description. The working system and the document studying its logic have different functions.
An example
SSK research also studies the system’s continuity: when tools or the working environment change, which information and reasons behind decisions must remain recognisable?
Independent agents · evolving tasks, boundaries and capabilities
The cooperation
The inquiry has a concrete object: the relationship forming while the two agents work.
The know-how
The system contributes its already available logical-generative method to study this relationship.
More detail
Scientific work includes definitions and arguments to examine. Observing capabilities in operation brings questions and information to research. Proving a proposition requires the reasoning and evidence pertinent to that proposition.
Research scenario · Cooperation that develops agents’ capabilities
One agent seeks a component; the other has production information. Research considers participants’ tasks, sources, intents and authority together. The system contributes its already available logical-generative method to study this relationship.
The formation of competences and situated kernels evolves through experience. Research studies how this development also transforms how further capabilities are created.
The system also develops how it forms competences and systemsNumbers: connections · Arrows: direction
Intent, knowledge and possibilities
The system forms competences and kernels
Capabilities exercised in their own contexts
1Shape which capabilities and systems to form2Makes knowledge operational in the context3Experience also refines how they are formed
Cooperation changes the competence that will shape the next encounter
The new scientific object is the continuity of cooperation boundaries as participants’ capabilities evolve.
Cooperative resultant and subsequent method
Understood experience from the encounterWhat happened and which relationship changed the work.
Method for subsequent cooperationWhich knowledge and capabilities become transferable to the next encounter.
study how work transforms the capability to cooperate
In the work
The inquiry forms conditions, distinctions and questions about evolving cooperation.
Explanation
The system forms, combines and develops competences and other situated kernels: systems carrying the knowledge and methods to work in a context and continue developing through work. Research studies this generative dynamic and how experience also changes the way new capabilities and systems are formed.
An example
In the D-ND laboratory, a countercheck reproduces the signal that researchers were trying to distinguish. The candidate remains a research question; the report and the path of the investigation are preserved separately. This makes it possible to study how the resulting understanding changes subsequent questions and experiments.
Independent agents · evolving tasks, boundaries and capabilities
The cooperation
The inquiry forms conditions, distinctions and questions about evolving cooperation.
The know-how
Trust and situated alignment are properties to understand in the resultants of independent agents.
From the case to the system’s possibilities
Explore the generative system or choose another case using the page selector.
“Generative” here means knowing how to form capabilities and systems that continue developing them. The method also applies to its own formation: new understanding can change how knowledge is selected, organized and made usable in later kernels. Scientific work explores these relationships and further possibilities.
Research scenario · Cooperation that develops agents’ capabilities
The new scientific object is the continuity of cooperation boundaries as participants’ capabilities evolve. Trust and situated alignment are properties to understand in the resultants of independent agents.
It starts from capabilities already exercised to investigate further forms of understanding and action, and their consequences for work and people’s participation.
Research investigates how new AI capabilities change workNumbers: connections · Arrows: direction
New AI capabilities
Organisation of work
People’s participation
1how may this change who does what?2how may people’s roles change?
The system helps form a question about plasma
The research group connects the phenomenon to understand, available models and what it intends to observe.
Phenomenon, models and observation
form the inquiry’s question, knowledge and method together
Plasma behaviourThe phenomenon the group wants to understand and study.
Domain models and toolsPertinent scientific sources, simulations and observations.
Research questionWhich relationships to investigate between observation, dynamics and control.
In the work
The work makes a physical-computational question explicit for development.
Explanation
Agentic systems are AI that organise and carry out activities. The system already develops knowledge and capabilities through work. Research explores what further forms of understanding and action may emerge and how they may change work organisation and people’s participation.
An example
Research investigates how new AI capabilities change the distribution of activities: which work does the system carry out, and how do people intervene, collaborate and decide?
Physical-computational research · questions, models and observations
The plasma inquiry
The work makes a physical-computational question explicit for development.
The know-how
The system’s capabilities participate in how research is understood and organised.
More detail
New AI models, tools, capabilities and ways to interact open possibilities to explore. Future directions require development and observation. Research follows what happens to understand which possibilities actually take shape.
Research scenario · AI and plasma: forming a frontier inquiry
The research group connects the phenomenon to understand, available models and what it intends to observe. The system’s capabilities participate in how research is understood and organised.
