A clear scope
The task, desired outcome and explicit limits. Not a promise to automate everything.
For AI that works with people and processes, not around them. Adaptable to your task. Built for practical testing. Designed to be built on.
Explore the applications
A Blueprint is a reusable plan for addressing a task with AI. That task may be developing a target picture, enabling a team or implementing a workflow. The plan connects the approach, responsibilities, suitable tools and quality criteria.
The task, desired outcome and explicit limits. Not a promise to automate everything.
Steps, roles, methods and suitable technical building blocks, adapted to the organisation.
Reference sources, test cases, human review and criteria for handover.
Documentation, open questions and reviewed lessons for the next version.
Open an example to see how people, processes and technology come together.
Use the eight P perspectives to develop a shared target picture. Connect the impact on people, value creation and collaboration, then agree priorities.

The prism on our homepage stands for this connected view. The eight P perspectives help surface dependencies and agree where change matters. They are not eight compulsory projects.
Your existing strategy framework can also provide the foundation. The Blueprint structures the application; 8P provides the perspectives.
A good fit: When leadership and teams need a shared direction, not another list of AI tools.
The intended result: An agreed target picture, traceable priorities and next steps with clear responsibilities.
Explore the 8P modelLearn on your own tasks through Promptathons and Agentathons. The planned Blueprints connect preparation, learning tasks, facilitation and transfer into everyday work.

A good fit: When people need to practise a useful way of working on their own tasks.
Planned format Blueprints, not yet developed. The descriptions below outline the intended approach; they are not fixed curricula.
Teams work on real tasks with AI, compare approaches and review results. The focus is thoughtful prompting and shared learning.
Teams design and test a simple AI assistant or agent-supported workflow. They learn to define tasks, access, boundaries and human approval points.
Promptathons are already part of our training offer. For an Agentathon, we first clarify the learning objective, prerequisites and approved tool environment with you.
The intended result: Depending on the learning goal: completed tasks, reusable ways of working or an initial agent prototype, with an agreed transfer plan. No automatic production approval.
Discuss learning formats and preparationClassify requests, process documents or prepare replies. With clear rules for when a person takes over.

A good fit: When recurring messages or documents create a clear bottleneck and people can review the output.
The intended result: A tested workflow for a bounded use case, with review and handover criteria.
Explore AI workflowsTurn distributed knowledge into a traceable process description. Understand and simplify first, then automate where it makes sense.

A good fit: When process knowledge is spread across people and documents, or an automation request is still unclear.
The intended result: A process description, open questions and justified improvement options.
Explore implementationWork on a current leadership challenge and build AI capability along the way. As a consulting sprint or strategic Promptathon: broaden perspectives, examine assumptions and weigh up alternatives.

The intended result: Traceable decision inputs with options, assumptions and open questions.
Explore the entry Blueprint in detailConcept illustrations, not product screenshots or customer photographs.
AI can help structure knowledge, apply methods and prepare results. Sustainable learning requires more: people who verify, decide and improve the shared foundation.
For example, AI can structure approved source material, draft a process description or prepare test cases. We use the Blueprint to define the task and quality criteria. People review the output; your process owners and IT agree what can be adopted.
Choose the scope, roles and permitted tools for your organisation.
Work on real cases. Review outcomes, exceptions and limits together.
Separate project-specific knowledge from potentially reusable lessons.
Only approved, generalisable improvements enter a new Blueprint version.
Customer data and internal knowledge remain in the agreed context. Only authorised, generalisable insights may be reused. There is no automatic release and no autonomous transfer into other organisations.
Blueprints do not replace our methods. They connect them with a concrete implementation task. A framework gives direction, a method structures the work and a format brings people together.
Top-down starts with strategic direction; bottom-up starts with team learning; a lighthouse project starts with a concrete use case. These are complementary entry routes, not stages or separate Blueprint categories. A Blueprint can support any of them.

The 8P target pictures help teams consider the organisation from multiple perspectives.
Explore target pictures →Strategic prompting supports analysis, perspectives and the critical review of results.
Strategic Prompting →Training, workshops and Promptathons give people space to practise on real tasks.
Explore learning formats →Our aim is to make suitable Blueprints usable with established partners, including partners already supporting small and medium-sized businesses. Close customer relationships and reusable SMC expertise can complement each other.
This capability is being developed. A Blueprint is only ready for transfer once its application, responsibilities and quality checks have been validated.
Discuss working together →