Training course · Vibe Coding · Manufacturing

Vibe Coding for Manufacturing Teams

Build software in natural language: from prompt to app, rapid iteration, quality and security checks, and turning prototypes into production.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Vibe Coding for Manufacturing Teams” is a hands-on course for roles such as Production and plant managers, Shift leaders and supervisors and Manufacturing and process engineers. Rather than learning Vibe Coding in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Manufacturing.

Vibe coding lets business users without any programming knowledge build digital tools of their own. You describe in everyday language what a mini app, dashboard or form should do, and tools such as Lovable, Claude, ChatGPT Canvas or Replit generate a working solution. Helpers for your daily work can take shape quickly, without waiting for IT to free up capacity. This course shows you step by step how to make it work, which habits lead to good results, and what really matters along the way.

During the course you build applications drawn from your own work: a KPI overview, a data entry form, a small calculator or an automation for recurring chores. At the same time you learn to assess the risks realistically. Which data may go into such tools, who will run and maintain the solution, and when must IT be involved? With this knowledge you can create useful solutions that are accepted within the organisation and remain secure and sustainable in the long term.

Manufacturers face cost pressure, skills shortages, complex product variants and high expectations for on-time delivery. Generative AI adds a new layer to existing Industry 4.0 solutions: AI assistants make knowledge from manuals, fault logs and work instructions accessible, support shift handovers, summarise KPIs from MES and ERP exports and help with root cause analysis using methods such as 5 Whys or Ishikawa. AI agents and automation create shift reports, analyse machine breakdowns and prepare maintenance orders. Experienced staff in particular benefit when their knowledge is documented and made available to new colleagues. Adoption succeeds when it starts with concrete shop-floor problems, involves works councils and health and safety early and keeps production data secure.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Production and plant managers
  • Shift leaders and supervisors
  • Manufacturing and process engineers
  • Maintenance teams
  • Lean and operational excellence leads

Typical challenges we address

  • Capturing and passing on the know-how of experienced staff
  • Analysing breakdowns quickly and reducing downtime
  • Presenting KPIs such as OEE from various systems in an understandable way
  • Keeping work instructions current and clear across many variants

What you will be able to do

  • You build your own mini apps, dashboards and forms through vibe coding without programming skills.
  • You describe requirements clearly enough for AI tools to produce usable solutions.
  • You improve your applications step by step and check the results for accuracy.
  • You automate simple recurring tasks in your working environment.
  • Use AI for knowledge management, root cause analysis and shift reporting in production.
  • Analyse production KPIs with AI and derive improvement actions.
  • Take data security, co-determination and occupational safety into account in manufacturing AI projects.

Course outline

Day 1

Module 1 Understanding vibe coding as a business user
  • What vibe coding is and what you can achieve without programming skills
  • Tools at a glance: Lovable, Claude, ChatGPT Canvas, Replit and similar platforms
  • Spotting good candidates for your own tools at work
  • Realistic expectations: strengths, limits and common pitfalls
Module 2 Describing and building your own mini app
  • Capturing goal, users, inputs and desired outcome in plain words
  • Generating a first version and clicking through it together
  • Improving look, wording and flow with targeted feedback
  • Saving milestones and returning to an earlier version when things go wrong
Module 3 Dashboards, forms and calculators
  • Turning Excel or CSV data into an interactive dashboard
  • Building entry forms with required fields and plausibility checks
  • Creating calculators and decision aids for your team
  • Checking results for accuracy with test data and spot checks
Module 4 Automating routine work
  • Identifying recurring tasks that lend themselves to automation
  • Building simple automations for reports, notifications or file storage
  • Discussing connections to existing tools via approved interfaces
  • Documenting automations clearly and handing them over to colleagues

Day 2

Module 5 Risks and coordination with IT
  • Which data may and may not go into AI tools: data protection and confidentiality
  • Managing access rights, sharing settings and public links deliberately
  • Avoiding shadow IT: clarifying operation, maintenance and ownership
  • Preparing a handover to IT when a solution grows or becomes critical
Module 6 Hands-on project: your own solution for Manufacturing
  • Shift log app – A tablet-friendly web app where shift leaders record events and which automatically generates a structured handover report.
  • OEE dashboard – An internal dashboard that imports machine data from CSV, calculates OEE per line and visualises the biggest loss drivers.
  • Fault knowledge base – A tool for recording faults with cause and solution that suggests similar past cases whenever a new fault is reported.
Module 7 Data protection, quality & transfer to daily work
  • Production data and engineering know-how are trade secrets and belong only in approved AI environments; in Germany, AI-based evaluation of employee performance or behaviour requires works council co-determination. AI components in safety-related machine functions fall under the EU Machinery Regulation and may be high-risk under the EU AI Act.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Shop-floor knowledge assistant

An AI assistant answers questions about machines, changeovers and fault patterns based on manuals, breakdown history and work instructions, always citing the source for verification.

Root cause analysis

AI structures breakdowns and quality issues using 5 Whys, Ishikawa or 8D, suggests possible causes from similar cases and helps document actions and responsibilities.

Shift reports and handovers

Notes, machine data and fault reports are turned into structured shift reports with output, breakdowns and open points, making handover to the next shift easier.

Work instructions

AI turns process descriptions, photos and expert interviews into illustrated, multilingual work instructions and checklists in plain language and keeps variants consistent.

KPI analysis

MES and ERP exports are analysed, OEE losses broken down by availability, performance and quality and anomalies explained clearly for shop-floor meetings.

Maintenance preparation

Automations collect fault reports; AI groups recurring failures, drafts maintenance orders and prioritises actions based on frequency and impact, before maintenance planning takes them over.

Possible hands-on projects

Shift log app

A tablet-friendly web app where shift leaders record events and which automatically generates a structured handover report.

OEE dashboard

An internal dashboard that imports machine data from CSV, calculates OEE per line and visualises the biggest loss drivers.

Fault knowledge base

A tool for recording faults with cause and solution that suggests similar past cases whenever a new fault is reported.

Prerequisites

No programming knowledge is required; confident use of a browser, office applications and spreadsheets is enough. You work in production, production planning or maintenance and know the processes at your plant.

Technical requirements

Your own laptop with an up-to-date browser, Git and an AI coding tool of your choice, such as an AI editor or coding agent with an active account.

Data protection & compliance

Production data and engineering know-how are trade secrets and belong only in approved AI environments; in Germany, AI-based evaluation of employee performance or behaviour requires works council co-determination. AI components in safety-related machine functions fall under the EU Machinery Regulation and may be high-risk under the EU AI Act.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Salzburg Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Bremen Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Online Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Augsburg Request

Frequently asked questions

Is vibe coding only suitable for quick prototypes?

Vibe coding shines with prototypes, internal tools and experiments. With the right practices, namely clear specifications, tests, reviews and sound version control, results can also be turned into production-ready applications. The course teaches you to manage that transition deliberately and to recognise early on when rebuilding is the wiser option.

Which tools are used in the course?

The course is vendor-neutral. We work with the main tool categories: AI editors such as Cursor or Windsurf, coding agents such as Claude Code or Codex, and browser-based app builders. You are welcome to use your preferred tool, as the principles of specification, iteration, quality and security apply to all of them.

How should I deal with security risks in generated code?

Generated code often contains typical weaknesses such as hard-coded credentials, missing input validation or overly open interfaces. You learn to check specifically for these patterns, build security requirements into the specification from the start, use automated scanning and require a deliberate human sign-off before every deployment.

Do we need to connect AI to our machines?

Not necessarily. Many use cases, such as knowledge assistants, work instructions or root cause analysis, work with documents and MES or ERP exports. Connecting directly to machine data is a later step that requires IT and OT security. In the course we start with use cases you can implement quickly.

How do we gain acceptance from the workforce?

By making AI visibly ease work, for example through faster troubleshooting or simpler documentation, rather than being perceived as a monitoring tool. Involve employees and their representatives early, start with pilot areas and clearly define which data will not be used for performance evaluation.

How much does “Vibe Coding for Manufacturing Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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