Training course · Prompt Engineering · Leadership & Management

Prompt Engineering for Leaders

Vendor-neutral prompt engineering: roles, context, few-shot examples, prompt chains, prompt libraries and systematic quality checks.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Prompt Engineering for Leaders” is a hands-on course for roles such as Managing directors and board members, Division and department heads and Team leaders. Rather than learning Prompt Engineering in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Leadership & Management.

Whether you use ChatGPT, Claude, Copilot, Gemini or Le Chat, the quality of the output depends largely on how the task is framed. Prompt engineering is the skill of conveying goal, context, constraints and desired format to a language model so that it reliably produces usable results. In this vendor-neutral practical day you learn proven techniques that work across all mainstream AI assistants: defining roles and audiences, selecting relevant context, working with examples and breaking complex tasks down into traceable steps. You try out every technique directly on tasks from your own working day.

The second part focuses on repeatability and quality across the team. You develop prompt templates with placeholders, build multi-step prompt chains for analysis, writing and review processes, and set up a shared prompt library. You learn to evaluate output systematically – with review criteria, test cases and targeted self-checks by the model – and to avoid typical pitfalls such as hallucinations, ambiguity and missing context. By the end you have a structured approach that works regardless of the tool you use and continues to pay off as new models arrive.

For leaders, generative AI matters in two ways: as a personal tool and as a strategic topic for the organisation. Personally, AI helps you grasp decision papers faster, structure strategy documents, prepare difficult conversations and sharpen your own communication. Strategically, leaders must judge where AI creates real value, what risks arise and how to support their teams in building skills. AI agents are changing roles, processes and responsibilities, which calls for clear guardrails, employee participation and an open learning culture. Leaders who have experienced AI hands-on can assess opportunities realistically, steer investment purposefully and lead change credibly.

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?

  • Managing directors and board members
  • Division and department heads
  • Team leaders
  • Strategy and transformation leads
  • Emerging leaders

Typical challenges we address

  • Information overload from reports, emails and decision papers
  • Uncertainty about where AI realistically adds value in your area
  • Teams with very different levels of AI knowledge and reservations
  • Legal, ethical and employee relations questions when introducing AI

What you will be able to do

  • You understand how language models process prompts and derive effective wording from this.
  • You structure prompts with role, context, task, constraints and output format.
  • You use few-shot examples and prompt chains for complex, multi-step tasks.
  • You create reusable templates and build a shared prompt library.
  • Use AI confidently in your day-to-day leadership work for analysis, communication and preparation.
  • Assess AI opportunities and risks in your area realistically and prioritise pilot projects.
  • Lead AI adoption in your team with clear guardrails, participation and upskilling.

Course outline

Module 1 How language models process prompts
  • Core principles of language models: probabilities, context window, limitations
  • Why wording, order and examples change the result
  • What causes hallucinations and how prompts reduce them
  • Differences and common ground between mainstream AI assistants
Module 2 Building blocks of an effective prompt
  • Defining role, audience, task, context and output format
  • Stating constraints, exclusions and quality criteria
  • Structured input with sections, delimiters and tags
  • Asking the model to raise questions instead of making assumptions
Module 3 Advanced techniques
  • Zero-shot, one-shot and few-shot: setting style and structure with examples
  • Requesting step-by-step reasoning for complex tasks
  • Prompt chains: separating research, drafting, review and revision
  • Using change of perspective, counter-arguments and model self-critique
Module 4 Templates and prompt libraries
  • Creating reusable templates with placeholders and variables
  • Storing persistent instructions in projects, custom assistants and agents
  • Building, naming, maintaining and sharing a team prompt library
  • Documenting templates: purpose, inputs, expected output, owner
Module 5 Quality assurance and responsible use
  • Defining review criteria and scoring rubrics for AI output
  • Setting up test cases and systematically comparing and improving prompts
  • Verifying facts, figures and sources; establishing the four-eyes principle
  • Data protection, confidential content and transparency under GDPR and the EU AI Act
Module 6 Practice lab: Leadership & Management
  • Condensing decision papers
  • Strategy sparring
  • Preparing one-to-ones
  • Leadership communication
  • Assessing AI potential
  • More effective meetings
Module 7 Data protection, quality & transfer to daily work
  • Introducing AI systems capable of monitoring employee behaviour or performance is subject to co-determination by works or staff councils where these exist, and employee data requires particular protection under the GDPR. The EU AI Act also requires organisations to ensure adequate AI literacy among staff and to scrutinise high-risk applications, for example in HR.
  • 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

Condensing decision papers

Lengthy reports, business cases and analyses are distilled into key messages, assumptions, risks and open questions so you can form a sound judgement faster and ask targeted follow-up questions.

Strategy sparring

AI acts as a critical sounding board for strategic options, runs through scenarios, formulates counter-arguments and helps surface assumptions and blind spots in plans. The decision remains yours.

Preparing one-to-ones

Guides for feedback, objective-setting or conflict conversations are structured, wording is refined and possible reactions are rehearsed – without entering personal details into unapproved tools.

Leadership communication

Announcements, speeches, change messages and answers to tough questions are drafted for the audience and adjusted in tone, clarity and length for staff, boards or customers.

Assessing AI potential

Together with the team, processes are systematically screened for AI suitability, prioritised by benefit and effort and translated into concrete pilot projects. Success criteria are defined up front.

More effective meetings

Agendas, pre-reads and minutes are prepared with AI, making meetings shorter and more decision-focused while actions are tracked clearly. Recurring formats can gradually be standardised as well.

Prerequisites

Some initial experience with at least one AI assistant such as ChatGPT, Claude, Copilot or Gemini is helpful; no technical background is required. Leadership or management responsibility, or preparation for such a role; no technical background required.

Technical requirements

A laptop with an up-to-date browser and access to at least one AI assistant, ideally the tool approved within your organisation.

Data protection & compliance

Introducing AI systems capable of monitoring employee behaviour or performance is subject to co-determination by works or staff councils where these exist, and employee data requires particular protection under the GDPR. The EU AI Act also requires organisations to ensure adequate AI literacy among staff and to scrutinise high-risk applications, for example in HR.

Suggested dates

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

  • Thu, 26 November 2026 Online Request
  • Thu, 10 December 2026 Salzburg Request
  • Wed, 16 December 2026 Online Request
  • Wed, 13 January 2027 Online Request
  • Fri, 29 January 2027 Bremen Request
  • Fri, 12 February 2027 Online Request

Frequently asked questions

Do these techniques work with every AI assistant?

Yes, the course is deliberately vendor-neutral. The principles – a clear task, relevant context, examples, structured output and review steps – work equally well in ChatGPT, Claude, Copilot, Gemini, Le Chat and other tools. Where assistants differ in detail, for example with projects or custom assistants, we show the corresponding features in each.

Won't better models soon make prompt engineering obsolete?

Models are getting better at interpreting vague requests, but they still cannot know what you do not tell them: audience, quality standards, internal requirements or relevant background. Good prompts are therefore mainly good task descriptions. Templates, prompt chains and quality checks also keep their value for teams as new models arrive.

What is a prompt library and how do we maintain it as a team?

A prompt library is an organised collection of proven templates for recurring tasks, each with its purpose, required inputs, a sample result and an owner. It can live in a shared document, a wiki or directly in the AI tool's projects. In the course you set up a first library and agree simple rules for maintenance and approval.

Why should leaders use AI hands-on themselves?

Only those who have tried AI tools themselves can judge benefits, limits and effort realistically, steer investment sensibly and support their teams credibly. The course therefore combines practical exercises on your own leadership tasks with strategic questions about organisational adoption.

What about works councils and employee representatives?

Where AI systems can be used to monitor employee behaviour or performance, employee representatives usually have co-determination rights. Early involvement, transparent objectives and a framework agreement on AI use have proven effective. In the course we discuss typical provisions and steps towards a trust-based rollout.

How much does “Prompt Engineering for Leaders” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 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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