Training course – Prompt Engineering – Legal

Prompt Engineering for Legal Professionals

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 Legal Professionals” is designed for roles such as Lawyers and partners in law firms, In-house counsel and corporate lawyers and Paralegals and legal assistants and shows step by step how to use Prompt Engineering productively, safely and transparently in Legal – 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.

Legal departments and law firms work with large volumes of text: contracts, pleadings, statutes, judgments and correspondence. That is why generative AI is changing legal work so profoundly. AI assistants summarise case files and judgments, draft contracts from model clauses, compare contract versions, identify risks in clauses and prepare outlines for submissions. AI agents and automation support due diligence reviews, deadline management and answering recurring questions from the business. Diligence remains essential: language models can invent citations or misstate the law, and client confidentiality and professional rules set clear limits on data processing. Lawyers who combine AI with verified sources, clear review steps and secure environments gain time for strategy, negotiation and advice.

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?

  • Lawyers and partners in law firms
  • In-house counsel and corporate lawyers
  • Paralegals and legal assistants
  • Legal operations and legal tech leads
  • Contract managers

Typical challenges we address

  • Reviewing large numbers of contracts and files in a short time
  • Ensuring consistent quality for standard contracts and recurring requests
  • Keeping track of case law and legislative changes efficiently
  • Protecting client and business secrets when using digital tools

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 contract review, drafting and file summaries with systematic source verification.
  • Automate recurring legal workflows such as standard contracts and requests from the business.
  • Use AI while upholding client confidentiality, professional rules and the GDPR.

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: Legal
  • Contract review
  • Contract drafting
  • Summarising files and judgments
  • Due diligence support
  • Structuring submissions
  • Legal self-service for the business
Module 7 Data protection, quality & transfer to daily work
  • Lawyers are bound by professional secrecy, in Germany under the Federal Lawyers' Act and Section 203 of the Criminal Code; client data may only be shared with service providers bound to confidentiality and processing data in line with the GDPR. Otherwise, facts must be anonymised, and AI output must always be checked against primary sources.
  • 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

Contract review

An AI assistant checks contracts against an internal playbook, flags deviating or missing clauses such as limitation of liability, jurisdiction or termination rights and suggests alternative wording for lawyers to evaluate.

Contract drafting

Approved model clauses and a structured questionnaire produce a draft contract, for example a non-disclosure or services agreement, including explanations for the business team.

Summarising files and judgments

AI condenses extensive files, submissions or judgments into facts, issues, arguments and outcome and creates chronologies that are checked against the originals.

Due diligence support

Contracts in data rooms are searched for change-of-control clauses, exclusivities, terms or liability risks, and findings are prepared in an overview for the due diligence report.

Structuring submissions

AI proposes outlines and lines of argument for submissions, opinions or memos, drafts individual sections and checks texts for contradictions and clarity.

Legal self-service for the business

A knowledge assistant answers standard questions from business units, such as contract approval or signing authority, based on internal policies and routes complex requests to the legal 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 a legal role, for example at a law firm or in-house legal department, and regularly handle contracts or submissions.

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

Lawyers are bound by professional secrecy, in Germany under the Federal Lawyers' Act and Section 203 of the Criminal Code; client data may only be shared with service providers bound to confidentiality and processing data in line with the GDPR. Otherwise, facts must be anonymised, and AI output must always be checked against primary sources.

Dates & locations

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

  • Munich Tue, 15 December 2026 6 hrs Request
  • Salzburg Mon, 14 December 2026 6 hrs Request
  • Berlin Thu, 10 December 2026 6 hrs Request
  • Augsburg Fri, 11 December 2026 6 hrs Request
  • Hanover Mon, 14 December 2026 6 hrs Request
  • Bremen Mon, 14 December 2026 6 hrs Request
  • Stuttgart Fri, 11 December 2026 6 hrs Request
  • Kaiserslautern Mon, 14 December 2026 6 hrs Request
  • Online Wed, 16 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.

May lawyers enter client data into AI tools?

Only if the provider has been carefully selected, is bound to confidentiality, is contractually integrated under data protection law and does not use inputs for training. Otherwise, work with anonymised facts. In the course we develop clear, practical guidelines for this.

How do we deal with invented citations?

Language models can invent case numbers, sections or quotes. Use AI with supplied sources as context or with legal databases that provide verified references, and check every citation before using it. We practise this review routine in the course with realistic examples.

How much does “Prompt Engineering for Legal Professionals” 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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