When a team is already experimenting with AI but everyone works differently, it is difficult to separate a useful workflow from an impressive demo. I help you choose a meaningful business task, give AI the right context, test the output in practice and define where human review is essential. The engagement can be a leadership consultation, a hands-on team workshop or a talk with concrete examples; scope and format are agreed around your audience and problem.
When this work is useful
- Leaders see many AI opportunities but lack clear criteria for choosing the first task.
- Employees use different tools independently, with no shared workflow or output-review rules.
- Customer enquiries, documents, summaries, proposals or information transfers create repeated work.
- You want to assess one practical AI use case before planning an integration or automation pilot.
- An event or a wider team needs an accessible talk that explains both the opportunity and the limits without inflated promises.
Tangible outputs
What the agreed format can produce
A priority task
We select a task whose input, acceptable output, frequency and consequences of error can be described clearly.
An AI workflow draft
We combine the goal, context, examples, output structure and the actions a person must take after receiving an AI result.
A practical test
We use prepared or appropriately anonymized examples and examine not only a good answer but also ambiguous and incorrect cases.
Review criteria
The team defines what must be checked, when an output must be rejected and which decisions AI must not make on its own.
Usage guidance
We record practical instructions, data and access boundaries, responsibilities and the questions that remain unresolved.
A next-step decision
We separate what the team can apply immediately from a separate integration, automation or controlled-pilot project.
Working process
How the content and format are chosen
- 01
Preparation conversation
We discuss the audience, current experience, repeated work, available tools and information that must not be used in a demonstration.
- 02
One clear problem
The program is built around a real task or decision rather than a general tour of the latest AI features.
- 03
Explanation and practice
I demonstrate the workflow from input to review, then participants test it with agreed examples or we examine the demonstration together.
- 04
Boundaries and next action
We identify error risk, human accountability, account and data requirements, then decide whether the experiment is worth continuing.
Clear responsibility
Important service boundaries
A workshop is not a production integration
A learning workflow or demonstration does not include deployment, maintenance or system integrations unless those are scoped as a separate phase.
Outcomes depend on the task
AI may accelerate a draft or help structure information, but a specific saving, quality level or return is not guaranteed.
Sensitive data is used only by agreement
Synthetic or appropriately prepared data is suitable for practice; conditions for real documents, accounts and access are agreed before the engagement.
Applied AI work
What AI does in these systems
Processes content · extracts document dataTwo concrete examples from products I build. Each shows the AI task and where a person still reviews the result.
Breach.gg—prepares content for publishing
Breach.gg, a product I founded, first introduced simpler AI integrations in 2022. In 2026, I built an expanded workflow that detects activity, processes media and prepares source-linked summaries for publishing.
Inv01ce—extracts invoice data
AI converts invoice or receipt content into structured fields. A person reviews ambiguous values before they are used.
FAQ
Frequently asked questions
Is the program suitable for AI beginners?+
Yes. Business consultations, team workshops and talks do not require programming knowledge. We assess participants’ experience in advance; technical AI-agent workshops are offered separately for people who build or maintain software.
Can the content be tailored to our company?+
Yes. During preparation we select one task relevant to your audience, its examples and the criteria for a good result. If real data cannot be used, we prepare a safe synthetic scenario.
Will participants need paid AI accounts or other tools?+
That depends on the agreed program. Before the engagement, we confirm what the facilitator and participants will use, which access or costs may be required and who provides them. Account requirements are not left until the day of the session.
Can this be delivered remotely, on-site and in English?+
Format, location and language are confirmed in the specific proposal around the audience and practical component. Before publishing a date, I confirm availability, preparation needs and whether the program can be delivered well in the requested language.
What does a consultation, workshop or talk cost?+
Pricing depends on format, audience, preparation, tailoring and the scope of practical work. Send a short description of the need and I will define what is included before providing a proposal.
What will the team have after the engagement?+
We agree the output in advance. It may be a list of priority AI tasks, one workflow draft, its review criteria, usage guidance or a clear first-experiment plan. It is not a universal promise of productivity or financial return.