Training course · GitHub Copilot · MVP Development for Startups

GitHub Copilot for Startups and MVP Development

Use GitHub Copilot professionally: completions, chat, agent mode, the coding agent for issues and PRs, code review and enterprise policies.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“GitHub Copilot for Startups and MVP Development” is designed for roles such as Founders with little or no programming experience, Technical co-founders and first engineers in startups and Product managers in early-stage product teams and shows step by step how to use GitHub Copilot productively, safely and transparently in MVP Development for Startups – from the fundamentals to advanced workflows.

GitHub Copilot has grown from simple code completion into a broad AI platform that supports the entire development lifecycle. In the editor you work with inline suggestions, next edit suggestions and Copilot Chat; in agent mode Copilot handles tasks across multiple files and runs commands. On GitHub itself, the coding agent picks up assigned issues and delivers pull requests. In this two-day course you will learn how to use each of these building blocks deliberately and fit them cleanly into your existing development process.

Beyond hands-on editor work, the course covers control and quality. Custom instructions and prompt files give Copilot the project knowledge it needs, MCP adds further tools, and Copilot code review complements human reviewers. For those responsible for teams and organisations, we look at policies at organisation and enterprise level, content exclusions, model availability and usage reporting. Together, these lay the groundwork for a secure, transparent and genuinely effective Copilot rollout across the entire company.

For founders and early product teams, speed determines how fast they learn from the market. AI coding tools, vibe coding and app builders now make it possible to turn an idea into a working minimum viable product with sign-up, database, payments and a landing page within days, often without a large engineering team. The real challenge shifts as a result: which hypothesis are you testing, which features truly belong in the MVP, and how does a quick prototype become a codebase that withstands investor due diligence, the first paying customers and growth? In this course you learn to build MVPs purposefully with AI agents, manage technical debt deliberately, build in security and data protection from day one and prepare the handover to a professional engineering team.

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?

  • Founders with little or no programming experience
  • Technical co-founders and first engineers in startups
  • Product managers in early-stage product teams
  • Corporate innovation and venture building teams
  • Participants in incubator and accelerator programmes

Typical challenges we address

  • Limited time and budget to validate a product idea in the market
  • Lack of engineering capacity or dependence on external agencies
  • Quickly built prototypes with security holes, open databases and unclear architecture
  • Uncertainty about when to rewrite an MVP and when to evolve it

What you will be able to do

  • You use Copilot completions, chat and agent mode purposefully for your everyday development tasks.
  • You capture project knowledge in custom instructions and prompt files to improve output quality.
  • You delegate suitable issues to the coding agent and review its pull requests properly.
  • You integrate Copilot code review sensibly into your existing review process.
  • Turn a business idea into a focused MVP scope and build it yourself with AI tools.
  • Integrate sign-up, database, payments and analytics and check your MVP for common security gaps before launch.
  • Manage technical debt deliberately and prepare the codebase for growth, due diligence and an engineering team.

Course outline

Day 1

Module 1 Copilot in the editor: completions and chat
  • Accepting, rejecting and steering inline and next edit suggestions efficiently
  • Using Copilot Chat for explanations, debugging and test generation
  • Setting context precisely with files, selections, workspace and chat variables
  • Model selection and differences between VS Code, Visual Studio and JetBrains IDEs
Module 2 Agent mode and extensions
  • Planning multi-step tasks in agent mode and executing them under control
  • Feeding terminal commands, test runs and error output into the agent loop
  • Connecting MCP servers for additional tools and data sources
  • Reviewing changes, accepting them partially or rolling them back
Module 3 Project knowledge through custom instructions
  • Writing repository-wide instructions on architecture, style and testing
  • Creating path-specific instructions and reusable prompt files
  • Combining personal and organisation-wide guidance sensibly
  • Refining instructions continuously based on output quality
Module 4 Coding agent and code review on GitHub
  • Writing issues the coding agent can implement reliably
  • Reviewing, commenting on and iterating over the agent’s pull requests
  • Using Copilot code review as an additional check in the PR process
  • Configuring the agent’s development environment with setup steps and Actions

Day 2

Module 5 Administration, policies and security
  • Licence assignment and policies at organisation and enterprise level
  • Content exclusions, model availability and public code filters
  • Using audit logs and usage metrics to steer adoption
  • Clarifying security risks, secrets and accountability for AI-generated code
Module 6 Practice lab: MVP Development for Startups
  • From pitch to specification
  • Building the MVP by prompt
  • Payments and integrations
  • Landing pages and experiments
  • Pre-launch security check
  • Making the codebase hand-over ready
Module 7 Data protection, quality & transfer to daily work
  • Even an MVP processes real customer data: you learn to implement GDPR essentials such as privacy notices, data processing agreements and consent, manage API keys and secrets securely and clarify licensing and copyright questions around generated code that become relevant in due diligence.
  • 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

From pitch to specification

Translate the business idea, target group and core hypothesis into user stories, a data model and a prioritised scope that stays deliberately small and includes measurable learning goals for the market test.

Building the MVP by prompt

Generate a web app with sign-up, database, core feature and admin area step by step using AI agents or app builders, working in small, tested iterations with the code under version control.

Payments and integrations

Integrate subscriptions and one-off payments through a payment provider, transactional email, analytics and first integrations, with webhooks, error handling and securely stored API keys. Test and live modes stay separate.

Landing pages and experiments

Create landing pages, waitlists and pricing pages in several variants, track conversion events and run quick A/B tests to check demand and willingness to pay before investing in heavier development.

Pre-launch security check

Have the MVP code checked for open database rules, missing access controls, exposed keys and unprotected endpoints, and work through a short checklist for a safe go-live.

Making the codebase hand-over ready

Document the architecture, add tests, refactor critical areas and produce a technical overview that new engineers or a technical due diligence can follow quickly. This also helps investor conversations.

Possible hands-on projects

Waitlist landing page

A landing page with value proposition, email capture, double opt-in and a simple dashboard that analyses sign-ups and traffic sources.

Booking MVP

A small web app where customers book and pay for appointments, providers manage availability and both sides receive email confirmations.

Interview synthesis tool

A tool that collects notes from customer interviews, clusters statements by problems and wishes and shows evidence for or against the core hypothesis.

Prerequisites

You develop software regularly, work with Git and GitHub issues and pull requests, and use a modern IDE. You have a concrete product idea or work in an early-stage product team; no programming skills are required, though a basic technical understanding helps.

Technical requirements

Your own laptop with VS Code or a JetBrains IDE, the Copilot extension installed and a GitHub account with an active Copilot licence; the coding agent requires a suitable plan.

Data protection & compliance

Even an MVP processes real customer data: you learn to implement GDPR essentials such as privacy notices, data processing agreements and consent, manage API keys and secrets securely and clarify licensing and copyright questions around generated code that become relevant in due diligence.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Thu, 10 December 2026 – Fri, 11 December 2026 Stuttgart Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Berlin Request
  • Mon, 8 February 2027 – Tue, 9 February 2027 Online Request
  • Wed, 24 February 2027 – Thu, 25 February 2027 Munich Request

Frequently asked questions

What is the difference between agent mode and the coding agent?

Agent mode runs inside your IDE: you work interactively with Copilot, see every step and approve commands. The coding agent, by contrast, works autonomously on GitHub once you assign it an issue, uses its own execution environment and opens a pull request that you then review just as you would a contribution from a colleague.

How can we make sure Copilot complies with our company policies?

At organisation and enterprise level you can enable or block specific features, models and extensions. Content exclusions keep sensitive files out of the context, and audit logs make usage traceable. During the course we show how to align these controls with data protection, information security requirements and your internal coding standards.

Is the course worthwhile if we already use Copilot?

Yes, especially then. Many teams rely on completions alone and barely touch chat, agent mode, custom instructions or the coding agent. The course shows how to use these features in a structured way, improve results with project knowledge and avoid common pitfalls. Experienced users benefit most from the sections on review and governance.

Can a non-technical founder really build an MVP alone?

For many business models, yes: web apps with sign-up, data storage, a core feature and payments can be built with AI tools without programming skills. What matters are clear requirements, small steps and systematic testing. Complex logic, high security demands or rapid growth will eventually call for engineering expertise. In the course you learn to recognise that point.

Will an AI-built MVP have to be rewritten later?

Not necessarily. If you use version control from the start, keep the data model understandable, test core features and separate configuration from code, an MVP can often evolve step by step. We show which early decisions make later rework easier and how to tell when starting afresh is the cheaper option.

How much does “GitHub Copilot for Startups and MVP Development” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 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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