Training course · Prompt Engineering · Logistics & Supply Chain

Prompt Engineering for Logistics and Supply Chain 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 Logistics and Supply Chain Teams” is a hands-on course for roles such as Supply chain managers and planners, Logistics and warehouse managers and Transport dispatchers and freight forwarders. Rather than learning Prompt Engineering in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Logistics & Supply Chain.

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.

Logistics and supply chain management are under constant pressure: volatile demand, disrupted supply chains, rising freight costs, staff shortages and growing demands for transparency and sustainability. Generative AI offers new tools for planning and communication. AI assistants analyse inventory and shipment data, explain forecast deviations, create work instructions for warehouse and shipping, answer customer status enquiries and help clarify customs and Incoterms questions. AI agents and automation process delivery notifications, freight documents and order confirmations, monitor delays and suggest actions. This frees up time for exception management and optimisation. The prerequisites are clean master data, access to ERP, WMS and TMS data and clear ownership of decisions.

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?

  • Supply chain managers and planners
  • Logistics and warehouse managers
  • Transport dispatchers and freight forwarders
  • Customs and foreign trade specialists
  • Demand and inventory planners

Typical challenges we address

  • Detecting and communicating delivery delays and disruptions early
  • Balancing inventory between service levels and working capital
  • Processing large volumes of freight documents and notifications manually
  • Onboarding new warehouse and dispatch staff quickly

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 for inventory, forecast and disruption analysis in the supply chain.
  • Automate document processing and status communication with clear review steps.
  • Design AI-supported logistics processes that are secure, traceable and respect employee co-determination.

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: Logistics & Supply Chain
  • Managing disruptions and delays
  • Freight document processing
  • Inventory and forecast analysis
  • Work instructions and training
  • Customs and trade questions
  • Shipment status enquiries
Module 7 Data protection, quality & transfer to daily work
  • Logistics data contains personal information, for example about drivers and recipients, which must be processed in line with the GDPR; AI-based analysis of employee performance or location requires works council involvement in Germany. Customs and export control decisions remain governed by applicable trade regulations, and AI output must be checked by experts.
  • 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

Managing disruptions and delays

Automations compare shipment status with planned dates; AI summarises critical delays, assesses affected orders and drafts customer notifications and options for action.

Freight document processing

AI reads delivery notes, consignment notes, packing lists and customs documents, checks them for completeness and consistency with the order and passes structured data to the ERP or WMS.

Inventory and forecast analysis

Exports from planning and ERP systems are analysed, slow movers and stock-out risks identified and forecast deviations explained clearly as input for S&OP meetings.

Work instructions and training

Process descriptions become clear, multilingual work instructions for goods receipt, picking and shipping, including checklists and quiz questions for onboarding.

Customs and trade questions

An AI assistant explains Incoterms, rules of origin or tariff classification as a starting point for research and prepares questions for customs experts, who verify results against official sources.

Shipment status enquiries

An assistant answers status enquiries based on tracking data, explains delays transparently and routes complaints with complete information to the responsible team.

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 logistics, supply chain management or dispatch and know the processes and systems in your area.

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

Logistics data contains personal information, for example about drivers and recipients, which must be processed in line with the GDPR; AI-based analysis of employee performance or location requires works council involvement in Germany. Customs and export control decisions remain governed by applicable trade regulations, and AI output must be checked by experts.

Suggested dates

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

  • Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 Hanover Request
  • Tue, 15 December 2026 Online Request
  • Thu, 14 January 2027 Online Request
  • Wed, 27 January 2027 Munich Request
  • Thu, 4 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.

Will generative AI replace our planning software?

No. Specialised planning, warehouse management and transport systems remain the backbone. Generative AI complements them with analysis, explanation, communication and document processing. In the course we show how to analyse exports from these systems with AI and automate recurring workflows.

Is AI reliable for customs questions?

AI is a good starting point for research and structure, but it can be wrong about tariff codes, preference rules or sanctions lists. Binding decisions require official sources and expertise, such as binding tariff information. We practise checking AI output systematically against official sources.

How much does “Prompt Engineering for Logistics and Supply Chain 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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