Training course · Claude · Product Management

Claude for Product Managers

Claude as an AI assistant for knowledge work: projects, Artifacts, long documents, analysis and precise writing for teams.

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

This course connects Claude with the everyday processes of Product Management. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Anthropic's Claude has become a go-to AI assistant for demanding knowledge work: it handles very long documents, reasons transparently and writes in a measured, easily steerable style. In this practical day you learn to exploit these strengths systematically. You analyse lengthy reports, contracts or policies, compare several sources and extract key findings with references to the exact passages. With Projects you store background knowledge and working instructions permanently, so Claude knows your terminology, templates and quality standards and you no longer start from scratch with every request.

We also show how to use Artifacts to produce standalone deliverables – structured documents, tables, charts or small interactive tools – and share them with your team. You analyse files with the built-in analysis capability, use research and connectors to company data, and put Claude to work as a critical reviewer of your own writing. A dedicated session covers Team and Enterprise plans, access management and data protection. By the end you have tested project set-ups and prompt patterns that you can apply straight away in your own function.

Product managers connect customer needs, business goals and technical delivery. Their day revolves around discovery, prioritisation, specification and alignment with engineering, design, sales and leadership. Generative AI speeds up almost every one of these steps: it analyses customer feedback, interviews and support tickets, helps write product requirements and user stories, structures competitor analyses and prepares roadmap communication for different stakeholders. With vibe coding, product managers can build clickable prototypes themselves and test ideas before committing engineering capacity. AI agents bring together signals from analytics, CRM and feedback tools. That leaves more time for product vision, decisions and conversations with customers.

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?

  • Product managers
  • Product Owners in agile teams
  • Heads of Product and product directors
  • Product marketing teams
  • UX researchers and product designers

Typical challenges we address

  • Large amounts of unstructured feedback from many channels
  • Heavy effort for specifications and stakeholder alignment
  • Prioritising under uncertainty and competing interests
  • Long lead times from idea to testable prototype

What you will be able to do

  • You write precise, structured instructions that let Claude handle complex tasks reliably.
  • You analyse long and multiple documents and obtain referenced, verifiable summaries.
  • You set up Projects with a knowledge base and style rules and share them with your team.
  • You use Artifacts and the analysis capability to produce usable documents, tables and evaluations.
  • Synthesise customer feedback and market information with AI into well-founded product decisions.
  • Produce specifications, user stories and roadmap communication faster and more precisely with AI.
  • Build clickable prototypes through vibe coding to validate ideas early with users.

Course outline

Module 1 Understanding and directing Claude
  • Model family, strengths and limitations compared with other assistants
  • Clear instructions with context, examples and the desired output format
  • Structured input using sections and tags for complex tasks
  • Extended thinking and step-by-step approaches for demanding questions
Module 2 Analysing long documents
  • Uploading and querying large PDFs, reports and contract sets
  • Comparing multiple documents and surfacing contradictions
  • Summaries with references to specific passages
  • Deriving checklists and review grids from policies and guidelines
Module 3 Projects and knowledge base
  • Creating Projects with knowledge documents and persistent instructions
  • Storing style and terminology rules for consistent results
  • Sharing Projects with the team and developing them together
  • Making good use of connectors to drives and business applications
Module 4 Artifacts, analysis and writing
  • Creating Artifacts for documents, tables, charts and interactive tools
  • Analysing files and spreadsheets with the built-in analysis capability
  • Drafting, shortening, rewording and tailoring text to audiences
  • Using Claude as a critical reviewer of arguments and gaps
Module 5 Team use, data protection and quality
  • Team and Enterprise plans: administration, roles and sharing
  • Handling confidential and personal data in line with GDPR
  • Checking output: verifying facts, figures and quotations
  • Defining internal guidelines and reusable prompt patterns
Module 6 Practice lab: Product Management
  • Synthesising customer feedback
  • PRDs and user stories
  • Preparing prioritisation
  • Competitor and market analysis
  • Prototypes via vibe coding
  • Roadmap and release communication
Module 7 Data protection, quality & transfer to daily work
  • Customer feedback and usage data often contain personal information and are subject to the GDPR; they should be pseudonymised before being processed in AI tools. Roadmaps and unreleased product information are trade secrets, and AI features in your own product must be assessed against the requirements of the EU AI Act.
  • 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

Synthesising customer feedback

Interviews, support tickets, app reviews and surveys are grouped by theme, problem and request and turned into an opportunity overview with supporting quotes for discovery.

PRDs and user stories

Problem statement, target users and goals become drafts of product requirement documents, user stories with acceptance criteria and edge cases, refined with engineering and design.

Preparing prioritisation

AI helps score initiatives using frameworks such as RICE or Kano, surface assumptions and prepare arguments for and against options ahead of prioritisation discussions. Disagreements become easier to resolve.

Competitor and market analysis

Feature comparisons, positioning and pricing models of competitors are structured and updated regularly; claims are backed by sources and checked critically. You keep track of market moves without lengthy manual research.

Prototypes via vibe coding

Product managers use AI coding tools to build clickable prototypes and simple functional demos to test concepts with users and make requirements tangible for the team.

Roadmap and release communication

Roadmaps, release notes, internal enablement material and customer communication are tailored to the audience – technical for engineering, benefit-led for sales and customers. Every audience gets exactly what it needs.

Prerequisites

Confident use of office applications and a web browser; prior AI experience is helpful but not required. Your own non-confidential documents are welcome as practice material. Experience in product management or as a Product Owner; no programming skills required.

Technical requirements

A laptop with an up-to-date browser or the Claude desktop app and a Claude account; we recommend Pro, Team or Enterprise access for Projects and larger files.

Data protection & compliance

Customer feedback and usage data often contain personal information and are subject to the GDPR; they should be pseudonymised before being processed in AI tools. Roadmaps and unreleased product information are trade secrets, and AI features in your own product must be assessed against the requirements of the EU AI Act.

Suggested dates

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

  • Fri, 27 November 2026 Online Request
  • Mon, 7 December 2026 Salzburg Request
  • Mon, 14 December 2026 Online Request
  • Tue, 12 January 2027 Online Request
  • Thu, 21 January 2027 Augsburg Request
  • Wed, 27 January 2027 Online Request

Frequently asked questions

How does Claude differ from ChatGPT in everyday work?

Both are capable general-purpose assistants. Claude particularly stands out with very long documents, careful reasoning and an easily steerable writing style, while Projects and Artifacts support structured work. Which tool fits better depends on your tasks, integrations and company policies – the course gives you criteria for an informed assessment.

What are Artifacts and why would I use them?

Artifacts are standalone deliverables that Claude creates in a separate panel next to the chat – a document, a table, a chart or a small interactive tool, for example. They can be revised in a targeted way, downloaded and shared. A conversation therefore produces ready-to-use results rather than scattered fragments of text.

Is my data used to train Claude?

On Team and Enterprise plans, business content is not used for model training as a matter of principle. For individual accounts this depends on settings you should review yourself. Regardless of the plan, GDPR and internal confidentiality rules apply. In the course we walk through the relevant settings and the questions to ask.

Can AI make product decisions?

No, but it improves the basis for them. AI condenses feedback, surfaces assumptions and prepares options. Product vision, weighing trade-offs and accountability for decisions remain with product management. In the course you use AI deliberately as an analysis and sparring partner without giving up critical judgement.

How far can I get with vibe-coded prototypes?

Very far for clickable interfaces, simple logic and user testing – often within a few hours. Production-ready software with security, scalability and maintainability remains engineering's job. The course shows how prototypes improve collaboration with the team rather than replacing it.

How much does “Claude for Product Managers” 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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