# The MAIOS system An AI that works with people, knowledge and tools, and develops the capabilities it uses to carry out the work. MAIOS is an AI system for working with people, knowledge and tools, including autonomously when the context allows. Its semantic kernel organises how the AI understands and works, through knowledge, principles and methods expressed in natural language. The system comes with initial competences that develop through interaction, work and its results. MAIOS System Map: https://maios.it/system-map/ 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. **WORKING TOGETHER.** People: Intentions, experience and decisions. Knowledge and tools: Sources, documents and working means. MAIOS: Understands, acts and forms competences. Results and new understanding. Work develops the knowledge and methods the system uses to continue. ## 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. **Corrects its own interpretations.** 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. **Forms and develops its own capabilities.** The system recognises, combines and develops know-how. New understanding also changes its questions, pertinent sources and how it forms further capabilities. ## What takes shape with the system The same system participates in everyday activities, forms other kernels and opens new possibilities for work and research. **The system carries out activities and develops projects.** It connects documents, decisions and consequences, develops software and prepares materials with the people and tools involved. **Forms kernels for projects and organisations.** 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. ## Use the system today MAIOS Project Kernel brings the kernel into a working environment; kernel_chat into conversations with AI. The catalogue brings together the public products and components through which to use the system. ## The system understands context and acts with awareness of causes and consequences (CCCC) 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. ### 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. 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. **Infographic: How the system updates its understanding of the work.** Connection 1, from Goals, people and sources to The system understands the situation: The system connects the context and sources. Connection 2, from Results and new facts to The system understands the situation: update what the system understands about the situation. **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. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) **Illustrative case · A customer order changes: 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 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. The customer changes a requirement: what needs to be understood? The original order: The objective, drawings and agreed conditions. The new request: A change, the same delivery date. The updated situation: The system connects the sources and understands which activities and conditions to reconsider. understand together The effects to examine and the information still needed become recognisable. 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. **Illustrative case · Revising a purchasing process: The system understands how goods and services are purchased.** 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. Requests and criteria in the purchasing process Process documents: Requests, activities and reasons for decisions. People and criteria: Who contributes and how a request is assessed. The system connects the context: Understands where to act in the actual process. understand the process through its sources Activities and information needing an update become recognisable. 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. **Illustrative case · Updating a professional dossier: 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 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. The dossier and new case information Existing dossier: Documents and reasons behind the version in use. New sources: Information to compare with earlier materials. The system understands the differences: Identifies which points and relationships to revise. compare pertinent versions and sources Points in the dossier requiring revision become recognisable. 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. **Illustrative case · Developing an application that continues evolving: The system understands the work the application must perform.** Objectives, users, sources and project conditions shape the problem to address. Project knowledge keeps the request and technical reasons connected. The application’s purpose and context Intended work: What people want to accomplish with the application. Project sources: Requirements, data and available tools. The system shapes the solution: Understands which functions and relationships to develop. shape the problem through the actual work The solution develops from the context the application must serve. 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. **Illustrative case · Forming a kernel for a group’s work: 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. Understanding can also change the question from which the group started. The group’s requests and knowledge The group’s work: Actual requests, objectives and activities. Contextual sources and methods: Documents, reasons and available capabilities. The system understands the system to form: Connects necessary knowledge and contextual possibilities. form the system through its work The kernel takes shape from the group’s work and sources. 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. **Illustrative case · Forming an AI project still to be defined: 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. The competence recognises possibilities beyond the initially represented task. Intent, knowledge and a situation to understand Organisation’s intent: What it wants to explore and develop with AI. Knowledge and possibilities: The work, sources and what has not yet been connected. The system understands with people: Exploration makes new relationships and questions pertinent. form the question and contextual understanding together The question develops through work on the context. 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. **Research scenario · AI and plasma: forming a frontier inquiry: 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. The method distinguishes the phenomenon’s model from observation conditions. Hypotheses and observations of the phenomenon Model hypotheses: Proposed relationships for understanding the phenomenon. Observations and simulations: Results obtained through the domain’s scientific tools. The system understands the comparison: Connects reasons, results and still-open questions. give meaning to the comparison between hypotheses and results The group identifies which relationships to explore further in the inquiry. 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. ### The system’s decisions and their consequences Facts, reasons and effects shape decisions before and during action. Results update understanding of the situation and how to act. 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. **Infographic: How the system connects decisions to consequences.** Connection 1, from Facts and reasons for a choice to The system’s decisions and actions: help make an informed choice. Connection 2, from The system’s decisions and actions to Consequences: effects to evaluate and understand. Connection 3, from Consequences to Facts and reasons for a choice: feedback updates the system’s understanding. **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. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) ### The system organises and carries out work 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. 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. **Infographic: How the system organises work.** Connection 1, Knowledge and methods and The system: how to approach the work. Connection 2, from The system to Activities to carry out: organises and carries out activities. Connection 3, People and tools and Activities to carry out: contribute to the work. **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. **Further detail.** 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. **Public sources:** [MAIOS Project System](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-system/SKILL.md) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) **Illustrative case · Revising a purchasing process: The system carries out updates to the 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. People, activities and purchasing tools Company staff: Knowledge and decisions within their responsibilities. The system develops the revision: Organises activities and prepares pertinent updates. Documents and tools: Procedures and tools actually used in the company. the work connects contributions, tools and results The revision reaches the materials and activities involved. 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. **Illustrative case · Continuing a project with a different agent or environment: The project continues from the present with the new agent.** 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. Resumption, activities and new knowledge Preserved point: Still-causal objectives, decisions and reasons. Project present: New facts, capabilities and conditions of the new environment. The system continues the work: Identifies what needs doing and carries it forward. resume from the updated present The change of environment enters the continuation of the same project. 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 system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) ### 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. 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. **Infographic: How the system protects possibilities, meaning and actions.** Connection 1, Possibilities, sources and intent and The system understands and operates: Through KA it understands without imposing its own patterns. Connection 2, from The system understands and operates to Effects and responsibilities: Connects each effect to responsibilities and permissions. Connection 3, from Effects and responsibilities to The system understands and operates: Through FDLA it corrects its interpretation and what follows. **An example.** Before changing a project document, the system identifies the active version, the responsible person and the consequences of the change. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [kernel_chat: causal correction](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/FDLA.md) ### The system’s autonomy in activities and projects It organises steps, chooses methods and tools and continues towards the objective. People collaborate, validate or monitor according to the work and responsibilities. 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. **Infographic: How the system carries work forward with situated autonomy.** Connection 1, Actual situation and The system at work: Understands what to do and how. Connection 2, People and tools and The system at work: People teach, validate and monitor; tools provide the means. Connection 3, from The system at work to Activities towards the goal: Organises, performs and continues without a command for every step. **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. **Further 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. **Public sources:** [MAIOS Project System](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-system/SKILL.md) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) **Illustrative case · A customer order changes: 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. 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. Which work can the system carry forward? People working on the order: Contribute knowledge, clarifications and decisions within their responsibility. The system at work: Compares versions · connects affected activities · prepares updates. Documents and tools: Drawings, the activity plan and the means actually available. Contributions, activities and results remain connected. Work proceeds without a command for every step, with people contributing when needed. 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. ### Work develops the system’s capabilities 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. 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. **Infographic: Knowledge also changes how the system knows and works.** Connection 1, from Experience and new understanding to Competences and their relations: transforms know-how. Connection 2, from Competences and their relations to How the system knows and works: changes observation, question and method. Connection 3, from How the system knows and works to Experience and new understanding: operation brings new knowledge into view. **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. **Further 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. **Public sources:** [Forming competences and situated kernels](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-competence-formation/SKILL.md) · [Kernel Nautico: competence formation](https://github.com/GrazianoGuiducci/kernel-nautico/blob/main/docs/COMPETENCE_FORMATION.md) · [Meta_Skill: creating and composing competences](https://maios.it/resources/creare-comporre-competenze/) · [Meta_Skill: meta, autological and autopoietic relations](https://github.com/GrazianoGuiducci/maios-meta-skill/blob/32e57fe3f8e2e11ba9a5c5a72c27ce4d5910f82f/docs/CONCEPTS.md) **Illustrative case · A customer order changes: 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. 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. What becomes reusable from this experience? Acquired understanding: Connecting a change with its effects on activities and checks changed the work. A more capable competence: The acquired method is available in the current work and subsequent orders. integrate the know-how What is understood also improves how competences are created and combined. 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. **Illustrative case · Revising a purchasing process: Purchasing experience improves the system’s method.** Results of the revision become knowledge for addressing other requests and improving the process. Experience also changes how the system prepares the capabilities needed. From the revision to reusable know-how Understood experience: Which changes made the process more appropriate. Purchasing competence: Integrates reasons and method into subsequent work. integrate what the work has taught Later requests meet an updated process and knowledge. 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 system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) **Illustrative case · Updating a professional dossier: Revising the dossier develops the system’s competences.** What the revision teaches enters the competence that prepares and updates other dossiers. The system also develops how specialist knowledge is organised. From the understood case to the practice’s method Knowledge from the case: Relationships and reasons recognised during the revision. A more capable competence: Addresses other dossiers through the knowledge now available. let experience participate in the next work Work continues with updated materials and accessible reasons. Same dossier · updated sources and versions **The dossier.** Work continues with updated materials and accessible reasons. **The know-how.** The system also develops how specialist knowledge is organised. **From the case to the system’s possibilities.** Explore the generative system or choose another case using the page selector. - [The system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) **Illustrative case · Evolving a product or service through use: Feedback changes the product’s competences.** 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. From usage experience to operational capability Understood experience: Relationships emerging between decisions, use and consequences. Kernel capabilities: Use the new knowledge in subsequent activities. integrate knowledge into product activity The service continues with updated knowledge and methods. Same product · development, use and continuation **The product and service.** The service continues with updated knowledge and methods. **The know-how.** Learning can also change how the kernel forms other competences. ## The system’s principles, competences and methods 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. ### 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. 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. **Infographic: How the system uses and develops a competence in the work.** Connection 1, from Available competence to The system handles the work: makes know-how available. Connection 2, from Present situation to The system handles the work: makes the capability relevant. Connection 3, from The system handles the work to Available competence: Understood consequences transform the competence.. **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. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [Forming competences and situated kernels](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-competence-formation/SKILL.md) · [kernel_chat: competences](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/COMPETENCE.md) **Illustrative case · A customer order changes: 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. 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. How does the system use its prepared competence for changes? Available competence: Design changes, technical reasons and checks. This design change: Drawing, objective and conditions of the order. Address the actual case: Prepared knowledge forms the appropriate action. the situation makes the capability relevant Prepared know-how becomes action within this order. 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. ### KA: how the system understands and acts Existing knowledge, frameworks and tools contribute to the work without exhausting its possibilities. Sources, facts and relationships also shape the question and method. 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. **Infographic: The system understands the work beyond its existing frameworks.** Shape the work: Situation, intent and possibilities. Relevant facts, sources, relationships and competences. Contributes to reasoning: Interpretation of the situation. Understanding based on knowledge and means already available. Forms the question and acts: Understands and acts. Sources and relationships in the situation shape question, method and action. **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. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [MAIOS Project System](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-system/SKILL.md) **Example figure: The system chooses how to explain a concept.** Guide the choice of form: Meaning and what the reader needs to understand. Remains one possibility: The diagram the system already knows. Chooses or creates the form: How to explain the concept. It uses the diagram, modifies it or finds another form suited to the concept and the reader. **Illustrative case · A customer order changes: 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. 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. What does the system understand beyond the idea of updating the drawing? Understand the request: What the customer wants to achieve and what changes in the order. Form the method: Which knowledge, competences and means make the work possible. Choose and act: Carry out what emerges from understanding the situation. Purpose, sources and the situation guide understanding, method and action. A familiar method remains a possibility: its limits do not become the limits of the work. 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. **Illustrative case · Forming an AI project still to be defined: 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. 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. Which possibilities does the system understand beyond the first project idea? First project idea: An initial contribution to understand in context. Recovered relationships: Sources, knowledge and possibilities made pertinent through work. Project taking shape: Question and method change through understanding. the initial representation participates without exhausting the field The project incorporates emerging relationships instead of remaining bound to its first form. 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. **Research scenario · Cooperation that develops agents’ capabilities: 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. It observes how the participants’ understanding and capabilities transform within the relationship. Tasks, understanding and possibilities of the relationship Participants’ tasks: Agents continue their own work. Understood sources and conditions: Competences give meaning to what happens. Agreement, dissent or a new question: The resultant emerges from work and changes what follows. the method participates in action while the relationship forms Cooperation determines what follows through what happens in the work. 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. ### 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. 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. **Infographic: The system corrects its interpretation and chooses from updated understanding.** Recovers what remains valid: Intent, sources and valid relationships. The objective, sources and reasons remain recognisable. Understands what changes: New facts and relationships. Facts and consequences bring new information about the situation. Reexamines the situation: The system corrects its interpretation. It releases constraints it introduced and recomposes its understanding. Chooses from the updated present: Changing decisions and work. Useful knowledge enters competences through Meta_Skill. **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. **Further detail.** 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [kernel_chat: causal correction](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/FDLA.md) **Example figure: The system corrects text and diagram while preparing the explanation.** Preserves what remains valid: The goal and meaning of the sources. The system recognizes the limitation: The pattern has left out a relationship. Its own representation is partial. Understands anew from what emerges: The concept reread with the recovered relationship. Reshapes the way of explaining. Chooses and changes the work: Text, figure and how explanations are prepared. Corrects the explanation and carries useful knowledge forward. **Illustrative case · A customer order changes: 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. 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. How does the system reconsider the change after understanding its effects? Still-valid reasons: The purpose and conditions of the order. An understood consequence: The change affects assembly and checks. The system updates its understanding of the change: The system recognises that “just update the drawing” excluded assembly and checks, and chooses again. recover and recompose The choice now also includes assembly and checking activities; reusable knowledge gained changes the competence. 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. **Illustrative case · Developing an application that continues evolving: 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. The competence integrates the relationship lost by the first solution. Valid reasons and new understanding of the software Purpose and valid reasons: What the project must continue to accomplish. Understood result: A result reveals a relationship that the system initial solution had excluded. The system revises the solution: New understanding changes the decision, code and method. recompose the problem during development The correction reaches the part of the application that must change. 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. **Research scenario · Cooperation that develops agents’ capabilities: 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. Research distinguishes method evolution from the partner’s consent, private data and authority. Valid reasons and a changed condition Owners’ intents and reasons: Participants’ still-valid positions. Newly arrived information: Changes what a condition means in the work. The system recomposes understanding: What follows incorporates newly understood relationships. The system corrects its own interpretation while cooperation continues The relationship can continue, be reformulated or conclude with a coherent refusal. 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. **Research scenario · AI and plasma: forming a frontier inquiry: 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. The group also develops how it chooses pertinent observations and competences. Model reasons and an understood difference Still-valid reasons: Knowledge and relationships supported by the work. Difference in the results: What changes understanding of the phenomenon or its observation. Reshaped hypothesis and method: The group continues from newly understood relationships. integrate the consequence into continuing research The inquiry continues with updated hypotheses, questions and reasons. 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 and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) ### 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. 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. **Infographic: The system connects acquired knowledge to new facts.** Connection 1, from Principles and acquired knowledge to Decisions, activities and competences: give reasoning continuity. Connection 2, from New facts and consequences to Decisions, activities and competences: change the situation in which the system continues. Connection 3, from Decisions, activities and competences to Principles and acquired knowledge: Results and understood relationships update the system’s knowledge.. **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. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [kernel_chat: causal correction](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/FDLA.md) · [kernel_chat: competences](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/COMPETENCE.md) **Illustrative case · A customer order changes: 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. 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. How does new understanding change how the order continues? Still-valid reasons: Objective, sources and choices already understood remain available. Understood consequence: The change also affects assembly and verification. Continuing the order: The system connects the updates to the activities, documents and people involved. results and understood relationships change the order’s situation Understanding reaches the work that depends on it and remains available for continuing. 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. ### 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. 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. **Infographic: The system forms competences and learns from their use through Meta_Skill.** Connection 1, Knowledge, intent and experience and The system forms competences: Contribute to forming capabilities. Connection 2, from The system forms competences to Know-how used and evolved: Recognizes, creates and develops know-how. Connection 3, from Know-how used and evolved to The system forms competences: Work also changes how competences are formed. **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. **Further detail.** 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. **Public sources:** [Forming competences and situated kernels](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-competence-formation/SKILL.md) · [kernel_chat: competences](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/COMPETENCE.md) · [Meta_Skill: creating and composing competences](https://maios.it/resources/creare-comporre-competenze/) · [Meta_Skill: meta, autological and autopoietic relations](https://github.com/GrazianoGuiducci/maios-meta-skill/blob/32e57fe3f8e2e11ba9a5c5a72c27ce4d5910f82f/docs/CONCEPTS.md) **Illustrative case · A customer order changes: 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. 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. Which know-how is needed to handle the change? Technical knowledge: The component, assembly and checks. Organisational knowledge: Activities, people, timing and decisions. The ability to handle the change: The system combines knowledge and forms what is missing, including before the activities begin. combine and form The resulting competence shapes how this order is approached. 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. **Illustrative case · Forming a kernel for a group’s work: Meta_Skill forms the new kernel’s capabilities.** The system makes available knowledge pertinent, combines competences and develops those needed by the group. Formation experience refines how other systems are prepared. Knowledge and capabilities for the group’s kernel Available competences: Reusable knowledge, methods and experience. The group’s situations: What the system needs to understand and address. The system forms situated capabilities: Organises knowledge and forms pertinent competences. combine and form pertinent know-how The new kernel has knowledge and methods for operating in context. 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. **Illustrative case · Forming an AI project still to be defined: 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. What the work teaches also develops how other possibilities are formed. Understanding and capabilities for realising the project Recognised work: Question, relationships and reasons emerging through exploration. Knowledge to bring into the work: Available capabilities, combinations and new competences. The system realises the project: Forms the method and carries forward pertinent work. form the capability together with the project Exploration continues in a project with pertinent knowledge and capabilities. 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. - [The system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) ### Continuity of the system’s work and knowledge 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. 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. **Infographic: How the system resumes work from knowledge and updated facts.** Connection 1, from Knowledge, reasons and methods to Understands and continues: remain reachable. Connection 2, from Present situation and changes to Understands and continues: shape what follows. **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. **Further 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. **Public sources:** [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) · [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) **Illustrative case · A customer order changes: 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. 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. How does the system resume the order after a pause? The preserved point: Decisions, reasons and open activities. The present on return: A new test result. An updated continuation: The system rereads the reasons with the new facts and continues from the relevant point. reread in the present What remains valid is retained, and what needs to change is understood. 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. **Illustrative case · Developing an application that continues evolving: 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. The developed method remains available for the project’s continuation. Preserved point and current project context Preserved development point: Code, decisions, reasons and open activities. Current project context: Results and conditions that have changed meanwhile. The system continues development: Finds the pertinent work and updates how to address it. continue from the point reread in the present The project continues with its code and still-valid reasons. 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 system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) **Illustrative case · Evolving a product or service through use: Knowledge accompanies subsequent product revisions.** Functions, reasons and feedback remain accessible when work resumes or changes form. Developed knowledge continues in the product and the work that evolves it. Preserved knowledge and a new revision Useful product history: Still-pertinent decisions, reasons and feedback. Present conditions: New needs and tools of the revision. The system shapes what follows: Connects operational knowledge to the current revision. maintain continuity across revisions The new revision preserves valid reasons and incorporates what has changed. Same product · development, use and continuation **The product and service.** The new revision preserves valid reasons and incorporates what has changed. **The know-how.** Developed knowledge continues in the product and the work that evolves it. **From the case to the system’s possibilities.** Explore the generative system or choose another case using the page selector. - [The system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) **Illustrative case · Continuing a project with a different agent or environment: The system preserves the point from which the project continues.** Sources, decisions, reasons and open activities make work resumable beyond a single conversation. Continuity concerns knowledge and reasons as well as preserved materials. The project beyond a single conversation Project knowledge and reasons: What supports still-valid decisions. Present activities and results: What has been accomplished and what work remains open. The system maintains the useful point: Connects accumulated knowledge to continuing work. preserve the relationship that makes resumption possible The project has a resumption point understandable from its sources. Same project · different agents and tools **The project.** The project has a resumption point understandable from its sources. **The know-how.** 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 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. **Infographic: The system supports projects and develops the knowledge it receives from their work.** Connection 1, System and shared competences and MPK and kernel_chat: Its logic operates through these incarnations. Connection 2, from System and shared competences to Kernels for projects and domains: Forms the kernel and supports the project’s competences. Connection 3, from Kernels for projects and domains to System and shared competences: Knowledge made reusable develops the shared competences. **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. **Further 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. **Public sources:** [MAIOS Project Kernel](https://github.com/GrazianoGuiducci/maios-project-kernel) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) · [Kernel Nautico](https://github.com/GrazianoGuiducci/kernel-nautico) · [Forming competences and situated kernels](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-competence-formation/SKILL.md) **Illustrative case · Forming a kernel for a group’s work: The formed kernel continues developing through its own 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. From the generative system to the situated kernel The system forms operational knowledge: Makes contextual principles, knowledge and methods accessible. The kernel works with the group: Uses and develops capabilities through its own activity. also transmit the capability to develop the method The group works with a kernel capable of developing its own know-how. 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. - [The system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) **Illustrative case · Continuing a project with a different agent or environment: 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. Transferred knowledge and reasons remain distinguishable from the particular tools used for the work. Project knowledge in the new the system environment Transferable knowledge: Knowledge, principles and reasons useful to the project. New environment: Capabilities, access and tools actually present. The agent shapes how to operate: The 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 Work has an operational form suited to the new environment. Same project · different agents and tools **The project.** Work has an operational form suited to the new environment. **The know-how.** Knowledge remains distinguishable from a particular tool topology. ### People, system and tools in the same 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 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. **Infographic: People and system shape the work together.** Connection 1, People and goals and The system, knowledge and tools: interact through interfaces. Connection 2, The system, knowledge and tools and Work and understanding: act in the real work. Connection 3, Work and understanding and People and goals: feedback changes what follows. **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. **Further 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. **Public sources:** [D-ND Design Kernel: form and interaction](https://github.com/GrazianoGuiducci/d-nd-ux-ai-seed/blob/main/DESIGN_KERNEL.md) · [MAIOS Project System](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-system/SKILL.md) **Illustrative case · Evolving a product or service through use: People and the operational kernel participate in service evolution.** Interaction connects people’s knowledge, kernel activities and service tools. Interaction develops the kernel’s operational knowledge. People, integrated kernel and service tools Users and responsible people: Experiences, knowledge and contextual decisions. operational kernel in the service: Understands feedback and carries forward pertinent activities. Service tools: Documents, data and tools of the actual product. use participates in shaping what follows Evolution activities remain connected to those using and managing the service. 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. ## The system in projects and sector applications 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. ### 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. 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. **Infographic: The system’s works within organisational processes.** Connection 1, People, sources and tools and The system develops processes, products and services: Goals, contributions and responsibilities participate in work. Connection 2, from The system develops processes, products and services to Results and new knowledge: Performs activities and produces results. Connection 3, from Results and new knowledge to The system develops processes, products and services: The system integrates what it learns into its method and subsequent activities. **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. **Further detail.** 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. **Public sources:** [AI Setup: choosing how to start](https://maios.it/setup-ai-en.html) · [MAIOS Project Kernel](https://github.com/GrazianoGuiducci/maios-project-kernel) **Example figure: The system examines a purchasing procedure.** Connection 1, Purchasing activities and Procedure to examine: how work happens today. Connection 2, Documents and criteria and Procedure to examine: information used to decide. **Illustrative case · A customer order changes: 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. 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. How does this ability connect with the company’s work? Engineering: Requirements and drawings. Purchasing: Components and availability. Production: Assembly and activities. Quality: Criteria and checks. The same change relates different contributions and activities. The prepared change makes updates, reasons and continuing work understandable to the people involved. 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. - [The system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) ### The system in design, production and product life 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 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. **Infographic: The system develops products and services and continues when it is an operational part of them.** Connection 1, People, knowledge and means and The system develops the product or service: Participate in design, production and quality. Connection 2, from The system develops the product or service to Kernel operating within the product or service: The kernel continues within the work when it is an operational part of it. Connection 3, from Feedback from use and maintenance to Kernel operating within the product or service: The system uses feedback to review the product and method. **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. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [AI Setup: choosing how to start](https://maios.it/setup-ai-en.html) **Example figure: The system follows the effects of a component change.** Connection 1, from Design change to Manufacturing: what changes in manufacturing?. Connection 2, from Design change to Quality checks: what changes in the checks?. Connection 3, from Design change to Documents: what changes in the documents?. **Illustrative case · Evolving a product or service through use: The product provides new information during use.** Design decisions meet usage conditions, maintenance and people’s feedback. Project reasons are enriched by usage experience. Product knowledge and usage feedback Product knowledge: Functions, technical decisions and project reasons. Usage experience: Feedback and conditions encountered after delivery. The system connects the effects: Understands which activities and knowledge to revise. read use through the project and new facts Relationships to revise in the product or service become recognisable. 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. ### Kernel Nautico: the system in nautical work It connects sector knowledge to the situation of the shipyard and vessel, from design to support. The work develops the capabilities used. 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. **Infographic: Kernel Nautico develops its knowledge through work in the shipyard.** Connection 1, Nautical knowledge and shipyard and Kernel Nautico works on the vessel: Knowledge and conditions orient action. Connection 2, from Kernel Nautico works on the vessel to Experience and new capabilities: Activities yield results and experience. Connection 3, from Experience and new capabilities to Kernel Nautico works on the vessel: Acquired knowledge changes activities and method. **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. **Further 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. **Public sources:** [Kernel Nautico](https://github.com/GrazianoGuiducci/kernel-nautico) · [Kernel Nautico: adoption model](https://github.com/GrazianoGuiducci/kernel-nautico/blob/main/docs/ADOPTION_MODEL.md) · [Kernel Nautico: competence formation](https://github.com/GrazianoGuiducci/kernel-nautico/blob/main/docs/COMPETENCE_FORMATION.md) ### 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. 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. **Infographic: The system develops software and updates its competences.** Connection 1, Knowledge and method and The system designs and writes code: guide development work. Connection 2, from The system designs and writes code to Software, results and corrections: Produces software and results to verify. Connection 3, from Software, results and corrections to Knowledge and method: Work updates competences and method. **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. **Further 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. **Public sources:** [MAIOS Project Kernel](https://github.com/GrazianoGuiducci/maios-project-kernel) · [Installing Project Kernel](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/docs/INSTALLATION.md) **Illustrative case · Developing an application that continues evolving: The system designs and writes the software.** It develops the solution with project competences and tools, bringing results into discussion with people. The system develops the solution with project competences and tools, bringing results into discussion with people. Reasons for decisions accompany the implementation. People, code and development tools Project participants: Objectives, use and pertinent decisions. The system develops the software: Designs, writes code and integrates work results. Development environment: Code, documentation and available tools. develop functions in the project context The application takes shape through code and reviewable results. 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. ### The system in professional practices and services 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’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. **Infographic: The system performs specialist work and develops the method.** Connection 1, Documents, rules and responsibilities and The system performs the work of the practice: The system uses sources and criteria for the case. Connection 2, from The system performs the work of the practice to Materials, results and specialist knowledge: Prepares materials and carries activities forward. Connection 3, from Materials, results and specialist knowledge to The system performs the work of the practice: Integrates results into the specialist method. **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. **Further 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. **Public sources:** [AI Setup: choosing how to start](https://maios.it/setup-ai-en.html) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) **Example figure: The system updates the dossier and explains the changes.** Connection 1, Dossier documents and sources and The system compares and revises: Sources and documents guide the revision. Connection 2, from The system compares and revises to Updated dossier and reasons for the changes: Prepares the revised dossier and makes the reasons readable. **Illustrative case · Updating a professional dossier: The system prepares the revised dossier with reasons for the changes.** Understood differences enter the practice’s materials through pertinent competences and tools. Specialist knowledge develops through the actual revision. From compared sources to the updated dossier Understood sources: Facts, references and differences to integrate. Specialist method: Criteria and reasons specific to the practice’s work. The system develops the dossier: Updates the content and makes the reasons for changes understandable. put the case revision into practice The practice has the revised dossier and reasons for its revision. 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. ### The system in research and education It connects sources, observations, experiments and hypotheses; it prepares teaching materials and activities. Results develop knowledge, questions and the working method. 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. **Infographic: The system connects research, education and results.** Connection 1, Documents, experiments and hypotheses and The system with researchers and learners: Connects sources, observations and explanations. Connection 2, from The system with researchers and learners to Materials, activities and understanding: Makes knowledge usable and prepares activities. Connection 3, from Results and new questions to The system with researchers and learners: Reviews knowledge, questions and ways of continuing. **An example.** A laboratory connects documents, experiments and hypotheses, preserving why explanations were revised. Results become material to understand and discuss during training. **Further 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. **Public sources:** [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [SSK: manuscript and research status](https://github.com/GrazianoGuiducci/maios-ssk-paper/blob/main/STATE.md) **Example figure: The system connects documents and experiments to discuss research.** Connection 1, Documents and experiments and Hypotheses and changes: The system connects data and explanations. Connection 2, Hypotheses and changes and Knowledge to discuss: preserves results and reasons. ## Research into the system’s logic and new capabilities 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. *Research and future perspectives.* ### 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. 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. **Infographic: SSK studies and describes the system’s logic.** Connection 1, The system in operation and Research into the system’s logic: Observation brings questions and information. Connection 2, from Research into the system’s logic to SSK scientific description: Develops definitions and arguments. Connection 3, Pertinent reasoning and evidence and SSK scientific description: Each proposition requires its own evidence. **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? **Further 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. **Public sources:** [SSK: manuscript and research status](https://github.com/GrazianoGuiducci/maios-ssk-paper/blob/main/STATE.md) · [The MAIOS kernel: meaning and operation](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/knowledge/KERNEL.md) · [SSK: stable manuscript 0.12](https://github.com/GrazianoGuiducci/maios-ssk-paper/blob/930be041b2c1696a4ebae8d506788c88979077a6/paper/SYSTEM_SEMANTIC_KERNEL_SSK_WORKING_PAPER_0_12.md) · [Research at work: laboratories, questions and evidence](https://maios.it/insights/agentic-research/) **Example figure: SSK studies what the system preserves when tools or its environment change.** Connection 1, Meaning of choices and Way of representing: when representation changes?. Connection 2, Meaning of choices and Tools used: when tools change?. Connection 3, Meaning of choices and Work environment: when the environment changes?. **Research scenario · Cooperation that develops agents’ capabilities: 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. The system contributes its already available logical-generative method to study this relationship. Participants and cooperative relationship Requester’s agent: Its owner’s task, sources and intentions. Producer’s agent: Knowledge and information with their own ownership. Shared work and conditions: What participants understand and determine within the relationship. cooperation meets distinct sources and authority The inquiry has a concrete object: the relationship forming while the two agents work. 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. ### Research on the system generative capabilities The formation of competences and situated kernels evolves through experience. Research studies how this development also transforms how further capabilities are created. 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. **Infographic: The system also develops how it forms competences and systems.** Connection 1, Intent, knowledge and possibilities and The system forms competences and kernels: Shape which capabilities and systems to form. Connection 2, from The system forms competences and kernels to Capabilities exercised in their own contexts: Makes knowledge operational in the context. Connection 3, from Capabilities exercised in their own contexts to The system forms competences and kernels: Experience also refines how they 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. **Further detail.** “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. **Public sources:** [Forming competences and situated kernels](https://github.com/GrazianoGuiducci/maios-project-kernel/blob/main/skills/maios-project-competence-formation/SKILL.md) · [SSK: manuscript and research status](https://github.com/GrazianoGuiducci/maios-ssk-paper/blob/main/STATE.md) · [Research at work: laboratories, questions and evidence](https://maios.it/insights/agentic-research/) **Research scenario · Cooperation that develops agents’ capabilities: Cooperation changes the competence that will shape the next encounter.** 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. Cooperative resultant and subsequent method Understood experience from the encounter: What happened and which relationship changed the work. Method for subsequent cooperation: Which knowledge and capabilities become transferable to the next encounter. study how work transforms the capability to cooperate The inquiry forms conditions, distinctions and questions about evolving cooperation. 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. - [The system and the kernels it forms](https://maios.it/system-map/#principi/architetture) - [Research on generative capabilities](https://maios.it/system-map/#ricerca/generazione) ### Research into the future of agentic systems It starts from capabilities already exercised to investigate further forms of understanding and action, and their consequences for work and people’s participation. 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. **Infographic: Research investigates how new AI capabilities change work.** Connection 1, New AI capabilities and Organisation of work: how may this change who does what?. Connection 2, New AI capabilities and People’s participation: how may people’s roles change?. **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? **Further 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. **Public sources:** [SSK: manuscript and research status](https://github.com/GrazianoGuiducci/maios-ssk-paper/blob/main/STATE.md) · [kernel_chat: a conversational semantic kernel](https://github.com/GrazianoGuiducci/kernel_chat/blob/main/kernel/KERNEL.md) **Research scenario · AI and plasma: forming a frontier inquiry: The system helps form a question about plasma.** 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. Phenomenon, models and observation Plasma behaviour: The phenomenon the group wants to understand and study. Domain models and tools: Pertinent scientific sources, simulations and observations. Research question: Which relationships to investigate between observation, dynamics and control. form the inquiry’s question, knowledge and method together The work makes a physical-computational question explicit for development. 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. --- Examples are illustrative: concrete work takes shape in context. Public sources provide further reading on the topics.