- AI Workshops for Companies
Workshops after which your team can actually build with AI
I help leaders, product teams, and software teams use vibe coding and AI-assisted development in practical work - from the first prototype to safer workflows with clear quality rules.
KI-Strategie / Automatisierung / Enablement
Who it is for
The right workshop depends on the work, not the tool.
Some teams first need to understand what AI can realistically do. Others want to build a prototype in a day. Software teams need standards for specs, reviews, tests, and privacy. The format starts where your team is now.
Leadership
For CEOs, founders, and management teams who want to experience AI building themselves and make better decisions about opportunities, risks, and first pilots.
- What has substance, and what is hype?
- Which use cases are worth testing for our company?
- Where do data, quality, and expectation risks appear?
Product and domain teams
For product, operations, marketing, sales, or finance teams that want to turn ideas into prototypes, internal tools, and better requirements.
- How does an idea become a useful prototype?
- How do we describe workflows so AI can work with them?
- When does an engineering team need to take over?
Engineering
For CTOs, engineering leads, and development teams that want to use AI coding productively without weakening architecture, tests, or review quality.
- Which tools fit our codebase and security needs?
- What do good specs, prompts, and review routines look like?
- How do we avoid fast code that creates slow follow-up costs?
Workshop formats
From the aha moment to a reliable way of working.
The workshops are built so they do not stop at tool demos. Your team understands the possibilities, builds something real, and leaves with routines for everyday work.
Vibe coding for decision makers
A compact executive workshop with live demo, tool map, opportunity assessment, and risk check. Ideal when leadership first needs to understand what is possible now.
AI building workshop
Your team turns its own ideas into first prototypes, internal tool concepts, or automation workflows and learns how good specifications go beyond simple prompts.
AI coding for software teams
A practical format for professional development: ticket to spec, spec to implementation, AI-supported tests, code review, privacy, and team guidelines.
Follow-up prototyping sprint
When a use case is ready, the sprint produces a testable prototype with technical assessment, risk notes, and a clear roadmap for operation or further development.
Why this is different
Not a prompt course. Not a motivational talk. A building workshop.
Many AI workshops show tools. Afterwards the team is inspired, but alone in daily work. My workshops connect the fast experience of vibe coding with 15+ years of software engineering: practical, honest about limits, and always focused on quality.
Typical AI workshop
Einfach AI workshop
Outcome
Lots of examples, little transfer into the team's own work.
Your team works on real ideas, workflows, or code scenarios from its own context.
Depth
Tool demos, prompt tips, and generic productivity promises.
Spec writing, review, tests, privacy, handover to engineering, and realistic limits.
Afterwards
After the workshop, teams often still lack a shared standard.
You leave with workshop results, decision logic, and concrete team routines.
Possible workshop outcomes
Your team does not leave with theory.
The goal is visible progress: better decisions, a first prototype, clearer requirements, or a repeatable AI coding workflow.
Prioritize AI opportunities realistically
Leaders see which use cases are easy to learn from, where real value sits, and which rules are needed before a pilot.
- Opportunity map for first AI-building pilots
- Tool and risk assessment for decision makers
- Clear criteria for go, no-go, or sprint
Processes become prototypes
Teams translate recurring work into clear flows, build first internal tools, and learn what they can own themselves.
- Briefing, analysis, or reporting workflows
- Internal tool prototypes for real tasks
- Better requirements for later implementation
AI coding becomes team-ready
Development teams create shared standards for AI-assisted development instead of isolated individual experiments.
- Workflow from ticket to spec to pull request
- Review checklists for AI-generated code
- Guidelines for tool use, tests, and privacy
Content that matches real company questions.
Every workshop is adapted to the audience, maturity level, and data situation. The building blocks stay deliberately practical.
From idea to prototype
How teams describe a problem, shape the scope, iterate with AI, and see early whether an idea has substance.
- Use-case sharpening and scope
- Prompting vs. spec writing
- Prototyping without false production promises
Professional development workflows
How AI coding fits into existing engineering processes: with architecture guardrails, tests, reviews, and clear ownership.
- Position Cursor, Claude Code, Copilot, and ChatGPT
- Ticket, spec, implementation, review
- Quality control for AI-generated code
Security, data, and team rules
Which data can go into which tools, how to avoid shadow IT, and which rules teams will actually use.
- Make privacy and IP risks understandable
- Tool policy for daily situations
- First guidelines instead of long rulebooks
Common questions
What companies want to know before an AI workshop.
The main objections are valid. That is why the workshop combines speed with clear framing.
Not for every format. Leaders and domain teams mainly need a clear understanding of problems, processes, and decisions. For the AI coding workshop, developers should bring real tasks from their codebase.
Next step
Let us find the right workshop format.
In a short conversation we clarify the audience, maturity level, possible use cases, and whether an executive workshop, AI-building workshop, software-team workshop, or prototyping sprint makes the most sense.
- Recommendation for the right workshop format
- Assessment of suitable use cases
- Clarification of tool, data, and security questions
- Concrete proposal for agenda and next steps