Before
Vague AI curiosity without a concrete target
After
A clear internal use case with sensible priority
Workshop for teams, departments, and independent professionals
Build internal tools with AI instead of talking about them for weeks
Learn how to use Cursor, Claude, Codex, and GitHub to shape realistic internal helpers, small automations, and first prototypes, even without a coding background. The focus is on sensible use cases, honest judgment, and a starting point that does not get lost in tool hype.
- You can start from zero
- Practice over tool hype
- Security and privacy included
Before / After
What changes after the workshop
Before
Tool confusion across Cursor, Claude, Codex, and GitHub
After
A cleaner mental model for which tool helps in which step
Before
Fear of technical complexity and breaking things
After
A safer starting point even without coding experience
Is this for you?
No coding required. A real reason helps.
You do not need developer experience. What helps is already having a problem, process, or internal tool idea that can be scoped more cleanly.
Good fit
- You have no coding experience and do not need any to join
- You are reasonably comfortable using a computer day to day
- You want to turn an idea into a useful first scope
Not ideal yet
- You only want broad AI inspiration without a real use case
- You want to build a large system immediately without clarifying limits or risks
- You do not yet know what problem should actually be solved
Who this is for, and who should wait
This workshop is for people who do not just want to play with AI for a day, but have a real use case, decision pressure, or automation need to sort through.
Independent professionals with a clear pain point
If you want to sort an internal helper, small automation, or prototype more quickly and more realistically.
Teams under process pressure
If repetitive work is painful and your team wants to understand what AI can sensibly unlock before it becomes a bigger project.
Decision-makers choosing between buy, build, and developers
If you want to decide more clearly when a tool is enough, when a small internal build makes sense, and when experienced developers are needed.
Examples + Demo
Three concrete cases that make the workshop tangible
Instead of talking abstractly about AI vibecoding, we look at small realistic cases that show up in real teams and small businesses.
Internal research helper
- Problem
- Knowledge is spread across docs, notes, and old tickets and wastes time every time it has to be reconstructed.
- Possible output
- A lightweight helper that bundles sources, pre-sorts them, and prepares structured answers.
- Realistic scope
- Not a magic system, but a bounded internal workflow with a small number of sources.
Form or approval workflow
- Problem
- Requests run through email, chat, and hallway conversations, and nobody has a clear overview.
- Possible output
- A small flow with input, status, ownership, and traceable handoffs.
- Realistic scope
- A small internal tool with clear fields, rules, and roles instead of a large platform build.
Small tool for recurring team tasks
- Problem
- The same steps are repeated manually and still stay inconsistent.
- Possible output
- An internal helper that structures routine tasks, prepares data, or generates reusable text output.
- Realistic scope
- A narrow starting point measured in hours or days, not a full product.
What people actually take away
Not more buzzwords, but better decisions
The goal is not to turn non-developers into engineers overnight. The goal is better judgment around what to build, how to start, and where the boundaries are.
What you can do better afterwards
- Recognize sensible first use cases and first scopes
- Make cleaner buy vs. build vs. developer decisions
- Plan next steps more realistically
What you finally understand technically
- Place frontend, backend, APIs, and cloud on a basic mental map
- Understand why prototype is not production
- See where JavaScript, Python, and packages usually fit
Which risks you spot earlier
- Handle secrets, API keys, and sensitive data more carefully
- Judge GitHub, reviews, and dependencies more realistically
- Think about privacy, data flow, and third parties earlier
Tools
Which tools we cover and where their limits are
The tools are not the point. The point is when they help, where they mislead, and what still needs disciplined working practice.
Cursor
Cursor
Useful for visible iteration and quick changes as long as tasks stay tightly scoped.
- Helpful for fast code changes
- Needs clear context and tight tasks
- Does not replace review or disciplined work
Claude
Claude
Strong for analysis, structure, documentation, and longer reasoning.
- Great for planning and explanation
- Helpful with longer context
- Does not remove human responsibility
Codex
Codex
Useful when requirements need to turn into concrete changes, terminal actions, and verifiable outcomes.
- Well suited for real implementation and debugging steps
- Useful when results can be checked
- Makes process quality more important, not less
GitHub
GitHub
Important to keep changes traceable, reviewable, and reversible.
- Keeps changes visible and recoverable
- Makes review and approval tangible
- Is not a secret vault
Formats
Formats that match your context and maturity
Whether team workshop, 1:1, or follow-up support, the right format is the one that fits your use case and risk profile, not the one with the most AI buzzwords.
For teams and departments
Live workshop for teams
Remote or on-site. A shared format for people who want to turn AI from a vague topic into concrete internal cases.
- Adapted to your context
- Beginner friendly and free of unnecessary jargon
- Real examples, Q&A, and concrete next steps
For individuals, leads, and decision-makers
1:1 enablement or sparring
For concrete cases, tool comparison, or a realistic first starting point when a team format would be too much.
- Strong for orientation, scope, and tool choice
- Direct feedback on risks and approach
- Compact and directly relevant to your case
For what comes after the first workshop
Support after the workshop
If the first orientation turns into a larger initiative, that can become more structured support.
- Turn workshop outcomes into clean next steps
- Plan larger internal tools more realistically
- Avoid fragile or overbuilt AI-driven solutions earlier
Pricing
Two clear starting points
In most cases, two options are enough: a team workshop or a focused 1:1 for one concrete use case.
For teams that need shared orientation
Team workshop
EUR 4,800
4 days
A shared format for teams that want a structured introduction and a realistic first scope they can act on.
- Designed for group alignment
- Remote or on-site
- Examples, Q&A, and concrete next steps included
For individuals and decision-makers
1:1 sparring
from EUR 100 / hour
usually 4 to 6 hours
For people who want to sort one concrete use case, compare tools, or shape a realistic first workflow.
- Direct feedback on your actual case
- Strong for scope, tool choice, and risk review
- Compact, focused, and practical
Jean-Luc Christoph Dittler
About
I am not selling an AI fairy tale here, but practical judgment
My background is real product and development work, not coaching for coaching's sake. I build software with Vue, Nuxt, and TypeScript and use AI-assisted development workflows in practical delivery work.
That means I know the difference between a good demo, a useful internal helper, and a system that actually has to hold up later.
That distinction is the core of this workshop: less buzzword gravity, more judgment and cleaner next steps.
- Experience shipping real software with technical ownership
- Strong background in frontend, tooling, and architecture
- Hands-on work with Cursor, Claude, Codex, and GitHub workflows
- Focus on judgment, responsibility, and practical next steps
FAQ
Frequently asked questions
Do participants need coding experience?
No. The workshop is explicitly built for people without a traditional developer background who still have a real goal or concrete use case.
Is this only for developers?
No. It is especially useful for independent professionals, specialist departments, operations, product roles, and decision-makers who need a clearer mental model for AI and automation.
Does it cover concrete tools like Cursor, Claude, Codex, and GitHub?
Yes. The tools are covered in practical terms. The point is not tool worship, but when they help, where they do not, and what teams still need to understand.
Does it also include security, company data, and privacy?
Yes. Security, sensitive data, access handling, data flows, third-party processing, and privacy risks are all core parts so that an early AI experiment does not quietly become business risk.
What does vibecoding mean in this context?
What often gets labeled vibecoding is usually just the attempt to build small software or automation pieces faster with AI. That is why this page deliberately uses clearer wording and focuses on what teams can actually do with it.
Contact
Let us use 15 minutes to see what actually fits
If you want to assess whether a compact workshop, 1:1 sparring, or broader support makes more sense for your case, book a short call or send me a short note with the use case, team context, and intended outcome.