Training course – Prompt Engineering – Social Media

Prompt Engineering for Social Media Teams

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

Duration
6 hours, one session
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 Social Media Teams” is a hands-on course for roles such as Social media managers, Community managers and Content creators and editors. Rather than learning Prompt Engineering in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Social Media.

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.

Social media teams work at the pace of the platforms: constantly changing formats, trends and algorithms, and a community that expects quick responses. Generative AI becomes a daily sparring partner. AI assistants build content calendars, draft posts, captions, hooks and short-form video scripts, adapt content for LinkedIn, Instagram, TikTok or YouTube and suggest replies for community management. Automation gathers comments and mentions, summarises sentiment and creates reports. Image and video tools help with visuals and subtitles. The human touch remains decisive: authenticity, a feel for timing and crisis sensitivity cannot be automated. Used wisely, AI frees time for interaction, creative formats and a strategy based on real data rather than gut feeling.

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?

  • Social media managers
  • Community managers
  • Content creators and editors
  • Corporate influencers and employer branding teams
  • Social media agency staff

Typical challenges we address

  • Producing high-quality content regularly for several platforms
  • Responding to comments and messages quickly and in the right tone
  • Spotting trends and reacting in time with suitable formats
  • Measuring success and preparing reports for management and clients

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.
  • Plan and produce platform-specific content efficiently and on brand with AI.
  • Use AI for community management and social listening with clear escalation rules.
  • Observe labelling duties, copyright and data protection for AI-generated content.

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: Social Media
  • Content calendar
  • Platform-specific posts
  • Short-form video scripts
  • Community management
  • Social listening insights
  • Automated reporting
Module 7 Data protection, quality & transfer to daily work
  • Social media activity is subject to advertising disclosure and imprint rules, copyright and personality rights for images and music, and the EU AI Act's transparency duties for deepfakes and AI-generated content. Personal data from comments and messages must be processed in line with the GDPR.
  • 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

Content calendar

An AI assistant turns communication goals, topic clusters and seasonal moments into a content calendar with format ideas, platform allocation and posting frequency for the team to adjust and approve.

Platform-specific posts

One core message becomes several variants: an expert LinkedIn post, an Instagram caption with hashtags and a hook for short-form video, each in the appropriate tone.

Short-form video scripts

AI drafts scripts and storyboards for Reels, Shorts or TikToks with a strong opening, clear structure and call to action, and creates subtitles and descriptions.

Community management

Comments and direct messages are sorted by request and sentiment, reply suggestions prepared in the brand voice and critical posts highlighted for personal handling.

Social listening insights

Automations collect mentions and comments; AI summarises recurring topics, questions and sentiment trends and provides ideas for new content and product feedback.

Automated reporting

Metrics from platform exports are combined, top and bottom performing posts analysed and a monthly report with insights and recommendations drafted.

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 manage social media channels professionally and know the main platforms and their formats.

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

Social media activity is subject to advertising disclosure and imprint rules, copyright and personality rights for images and music, and the EU AI Act's transparency duties for deepfakes and AI-generated content. Personal data from comments and messages must be processed in line with the GDPR.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Mon, 14 December 2026 6 hrs Request
  • Salzburg Tue, 15 December 2026 6 hrs Request
  • Berlin Tue, 15 December 2026 6 hrs Request
  • Augsburg Mon, 14 December 2026 6 hrs Request
  • Hanover Wed, 16 December 2026 6 hrs Request
  • Bremen Tue, 15 December 2026 6 hrs Request
  • Stuttgart Mon, 14 December 2026 6 hrs Request
  • Kaiserslautern Fri, 11 December 2026 6 hrs Request
  • Online Tue, 15 December 2026 6 hrs 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.

Do AI-generated posts need to be labelled?

Under the EU AI Act, deepfakes in particular, as well as AI-generated text on matters of public interest that has not been editorially reviewed, must be disclosed. Platforms also have their own rules for labelling realistic synthetic content. In the course we draw up a clear labelling policy for your team.

Doesn't AI content feel generic?

It does when AI is used without context. With your own experiences, customer voices, data and a clearly defined brand voice as input, drafts become far more distinctive. AI provides structure and variants; you contribute the personal perspective and a feel for your community.

How much does “Prompt Engineering for Social Media Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you 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 and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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