Training course · Prompt Engineering · Content & PR

Prompt Engineering for Content and PR Teams

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 Content and PR Teams” is designed for roles such as Press officers and PR managers, Content marketing managers and Editors and copywriters and shows step by step how to use Prompt Engineering productively, safely and transparently in Content & PR – from the fundamentals to advanced workflows.

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.

Content, communications and PR teams must tell relevant stories to journalists, customers, employees and search engines with limited resources. Generative AI is changing this daily work noticeably: AI assistants research topics, develop content strategies, structure articles and white papers, draft press releases, Q&A documents and interview briefings and optimise copy for search engines and AI-powered search. Automation supports media monitoring, topic tracking and repurposing content across formats. At the same time, the demands on credibility are rising: facts must be correct, quotes must be approved and crisis communication requires sensitivity. AI is therefore a tool for research, structure and variants, while stance, quality and accountability remain with communications professionals.

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?

  • Press officers and PR managers
  • Content marketing managers
  • Editors and copywriters
  • Internal communications teams
  • SEO and corporate publishing leads

Typical challenges we address

  • Producing high-quality expert content with little time and many review rounds
  • Drafting press releases and statements quickly and precisely
  • Repurposing content for search, social media and newsletters
  • Continuously monitoring and assessing media coverage and the topic landscape

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.
  • Develop content strategies and high-quality copy for different formats with AI support.
  • Produce press releases, Q&As and holding statements faster while checking facts systematically.
  • Automate media monitoring and content repurposing while respecting copyright and media law.

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: Content & PR
  • Topic research and content strategy
  • Press release drafts
  • Articles and white papers
  • Content repurposing
  • Media monitoring insights
  • Crisis and Q&A preparation
Module 7 Data protection, quality & transfer to daily work
  • AI-supported communication must respect copyright, quotation rules and personality rights; quotes must never be invented and must be approved by the person quoted. Confidential information such as unpublished financial results belongs only in approved AI environments, and the EU AI Act's transparency duties apply to AI-generated text on matters of public interest.
  • 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

Topic research and content strategy

An AI assistant analyses search intent, customer questions and industry trends, clusters topics and proposes a content plan with formats, audiences and key messages for the team to prioritise.

Press release drafts

From facts, quotes and background information, AI produces an inverted-pyramid draft including headline variants, boilerplate and a short version for social media.

Articles and white papers

AI creates outlines, summarises expert interviews, drafts individual sections and checks readability, flow and consistent use of technical terms, before subject matter experts sign off the content.

Content repurposing

A white paper or webinar is turned into blog posts, LinkedIn posts, newsletter sections and FAQ entries, each with adapted length, tone and call to action.

Media monitoring insights

Automations collect online media mentions; AI summarises tone, key statements and relevant journalists and drafts a daily or weekly press review.

Crisis and Q&A preparation

AI helps anticipate critical questions, draft Q&A documents and holding statements and run through crisis communication scenarios, which are then agreed with management and legal.

Prerequisites

Some initial experience with at least one AI assistant such as ChatGPT, Claude, Copilot or Gemini is helpful; no technical background is required. You work in communications, PR or content marketing and have experience in professional writing.

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

AI-supported communication must respect copyright, quotation rules and personality rights; quotes must never be invented and must be approved by the person quoted. Confidential information such as unpublished financial results belongs only in approved AI environments, and the EU AI Act's transparency duties apply to AI-generated text on matters of public interest.

Suggested dates

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

  • Thu, 26 November 2026 Online Request
  • Fri, 4 December 2026 Augsburg Request
  • Fri, 18 December 2026 Online Request
  • Thu, 7 January 2027 Online Request
  • Tue, 12 January 2027 Kaiserslautern Request
  • Tue, 26 January 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.

How do we prevent false facts in AI-generated copy?

AI assistants can produce convincing but incorrect statements. Work with supplied sources as context, ask for claims to be referenced and introduce a mandatory fact check before publication. In the course we develop prompt patterns and review routines that support exactly this.

Do search engines penalise AI-generated content?

Search engines primarily assess quality, usefulness and expertise, not how content was produced. Mass-produced thin content does harm rankings, however. Content that performs well combines genuine expertise, examples and data, with AI providing structure and efficiency and experts providing substance.

How much does “Prompt Engineering for Content and PR Teams” 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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