MAIOS for companies

MAIOS is a semantic operating system and a research and development programme grown from D-ND work with AI agents. Its kernel connects knowledge, principles, methods and competences to the context of an activity, so that knowledge becomes operational and can evolve through work. MAIOS includes a method, a field of competences and software incarnations such as MAIOS Project Kernel. The kernel operates through the AI model's capabilities and the tools available in its environment while retaining its own semantic organisation.

The starting point is how your company already uses AI. MAIOS provides a way to organise and develop situated competences, connecting sources, intent, reasons and consequences. It can help form a method that develops with a project and generate further capabilities. Its specific contribution becomes clear through your existing practices and technologies.

A competence is a capability taking part in actual work: it may understand sources and meaning, guide a method, preserve continuity, perform an activity or cooperate with other capabilities. Competences can have different, combined or distributed forms. Documents, instructions and tools may make them reachable; their exercise is observed in real work.

It means relating the situation, sources, intent, reasons, decisions and consequences while work unfolds. In MAIOS, this contextual understanding and causal awareness — CCCC — can change the question and the way of acting when new relationships emerge. People and agents contribute different capabilities, tools and responsibilities.

A new intention, knowledge, a result, an experience or a possibility may make a capability relevant. Meta_Skill can recognise, compose, form and evolve the needed competences. Work can also develop the method that recognises and generates further competences: a core part of MAIOS's generative and autological capability.

MAIOS is used in research, design and development with AI agents, in producing technical materials, monitoring and managing activities through appropriate tools and competences. It also participates in developing MAIOS itself. A distributed software incarnation is MAIOS Project Kernel 5.5.0, an open-source package that can be installed in a project and provides methods for competences, sources, continuity and the formation of further situated kernels. Public sources describe the product, its compatibility and a bounded observed episode using synthetic data. Other MAIOS activities use competences and tools in their own operating environments.

A situation worth understanding or developing: an engineering problem, a process, a design decision, a research activity, or an assistant for internal teams or customers. A bounded initial study can identify context, participants, sources, a useful first result and possible next steps. The choice comes from your organisation's actual work.

A first step is to build the project's context with available sources and people who know the work. MAIOS Project Kernel can be configured and installed in a compatible project; the kernel then makes relevant methods and competences reachable in the AI receiver's environment. Connections to company data, software, tools and systems are designed with their respective owners.

Graziano Guiducci is an independent researcher and AI systems architect. He uses MAIOS in his own work, directs its development and checks how it operates and the quality of its results. A collaboration may involve people in your company who already use AI or a small group trained and supported during adoption. Initial design, training and responsibilities are defined together for the specific project.

A point of contact, an activity to understand and relevant knowledge and tools, within agreed boundaries. An initial professional study can clarify objectives, sources, people, capabilities to form, expected results, validation, duration and fees. MAIOS Project Kernel is distributed as open-source software; design, training, customisation and integration are distinct professional services to be agreed.

The people doing the work help identify what matters: quality, time, errors, cost, continuity, effectiveness or team autonomy. An initial situation is compared with what is observed after the intervention. MAIOS can help organise measurement methods and competences where the project calls for them.

The project keeps sources, owners, responsibilities and permissions recognisable. Knowledge and competences can remain in environments controlled by the organisation, under the relevant agreements and licences. The kernel connects meaning, sources and consequences; authority over real actions remains with the responsible people and systems. Access controls, data protection and execution depend on the technical protections of the environments actually used.

A collaboration may aim to leave a situated kernel, knowledge, competences, methods and guides reachable by the team continuing the work. The system can preserve reasons for decisions and useful knowledge in the project's own sources, enabling later sessions or agents to resume work and develop further capabilities. Continuity is built from the project's reachable knowledge. Delivery includes the necessary training, configuration and an assessment of the autonomy actually achieved.

MAIOS is designed to develop competences and methods as context, sources and recognised possibilities change. Knowledge can remain part of the project's assets and be used by compatible AI receivers according to their actual capabilities. Integrations, permissions and software dependencies still follow the technical updates needed by their respective environments. This architecture supports adaptation over time.

Yes, as a situated design and development opportunity. Competences may help people understand and improve a product; experience with the product can in turn develop the team's competences. When a capability is actually integrated into software or services, it may also take part in the product's operation. Each implementation needs its own context, architecture, sources, responsibilities and tests.