Training course · Cursor · Mobile Apps

Cursor for Mobile Developers

Work productively with the AI code editor Cursor: agent mode, rules, codebase context, Tab completion, background agents and review.

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

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

Cursor is an AI code editor built on VS Code that weaves language models deeply into everyday development. Alongside context-aware Tab completion, it offers an agent mode that searches files on its own, plans changes across the whole project, runs terminal commands and fixes errors iteratively. In this two-day course you will learn to use Cursor with purpose: choosing the right interaction mode, steering context deliberately and combining AI assistance with your existing workflow of version control, automated testing and peer code review.

A key focus is making Cursor work for teams. Project rules let you capture architectural decisions, naming conventions and testing strategies so that the agent produces consistent results. You will learn to make good use of codebase indexing, targeted references to files, documentation and symbols, and MCP integrations. You will also delegate tasks to background agents, review their output as pull requests and set up a review process that takes quality, security and data protection seriously across the organisation.

Mobile development spans several worlds: Swift and SwiftUI for iOS, Kotlin and Jetpack Compose for Android, and cross-platform approaches with Flutter or React Native. On top come store guidelines, device fragmentation, offline capability, push notifications and demanding release processes. AI coding assistants and agents relieve teams of precisely these tasks: they build screens from designs, migrate UIKit or XML layouts to declarative UI frameworks, write UI and unit tests, analyse crash reports and automate build pipelines with Fastlane. Because mobile projects depend heavily on platform conventions, the AI needs precise context on architecture, state management and target platforms. This course shows you how to build that context and verify results on real devices.

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?

  • iOS developers using Swift and SwiftUI
  • Android developers using Kotlin and Jetpack Compose
  • Cross-platform developers using Flutter or React Native
  • Mobile teams in agencies and product companies
  • Tech leads responsible for app architecture and releases

Typical challenges we address

  • Maintaining several platforms in parallel with different languages and UI paradigms
  • Migrating from UIKit or XML layouts to declarative UI frameworks
  • Hard-to-reproduce crashes and performance issues across a wide range of devices
  • Laborious build, signing and store release processes

What you will be able to do

  • You choose the right Cursor mode for each task and use it efficiently.
  • You steer codebase context precisely and get more accurate suggestions as a result.
  • You write project rules that reliably enforce your team’s conventions.
  • You use agent mode and background agents for features and refactorings with verifiable results.
  • Use AI agents for screens, UI migrations and tests in native and cross-platform apps.
  • Diagnose crashes and performance issues faster and automate build and release processes with AI support.
  • Give the AI clear platform conventions and architecture rules and verify results on real devices.

Course outline

Day 1

Module 1 Setting up Cursor and understanding its modes
  • Installation and migration of VS Code settings and extensions
  • Differences between Tab completion, inline edits, Ask mode and Agent mode
  • Choosing a model per task: balancing speed, depth and cost
  • Privacy mode and organisation-level settings
Module 2 Steering codebase context
  • How codebase indexing works and where its limits lie
  • Referencing files, folders, symbols, documentation and web sources precisely
  • Using ignore files to exclude sensitive or irrelevant content
  • Avoiding overlong chats and restarting tasks with fresh context
Module 3 Rules for consistent team results
  • Creating and versioning project rules and scoping them by file pattern
  • Expressing architecture, style and testing conventions as effective rules
  • Separating user rules from team rules
  • Refining rules iteratively based on the agent’s typical mistakes
Module 4 Agent mode in practice
  • Building features step by step with plan, implementation and tests
  • Running multi-file refactorings safely with checkpoints
  • Approving terminal commands deliberately and feeding error output back
  • Connecting MCP servers for issue trackers, databases or browser testing

Day 2

Module 5 Background agents, review and governance
  • Delegating tasks to background agents and running them in parallel
  • Reviewing results as branches or pull requests and steering follow-ups
  • Using AI-assisted code review alongside human review
  • Addressing security risks, secrets and licensing in enterprise use
Module 6 Practice lab: Mobile Apps
  • Turning designs into screens
  • Declarative UI migration
  • Testing mobile apps
  • Analysing crash reports
  • Offline capability and data storage
  • Build and release automation
Module 7 Data protection, quality & transfer to daily work
  • Apps often handle sensitive device data such as location, contacts or health information, so generated code must request permissions sparingly and manage consent in line with GDPR. Signing keys, API keys and store credentials do not belong in prompts, and new SDKs and packages should be checked for licensing, tracking behaviour and supply-chain risk.
  • 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

Turning designs into screens

From screenshots or design specs, the assistant generates SwiftUI, Compose, Flutter or React Native screens that reuse your components, themes and navigation and respect dark mode and dynamic type.

Declarative UI migration

The agent moves UIKit view controllers or Android XML layouts to SwiftUI or Jetpack Compose step by step, wraps legacy parts via interop layers and protects behaviour with snapshot and UI tests.

Testing mobile apps

The AI writes unit tests for view models and repositories, UI tests with XCTest, Espresso or Flutter widget tests, and sets up mocks for networking and persistence.

Analysing crash reports

Symbolicated stack traces from crash reporting services are interpreted, likely causes such as threading or lifecycle issues narrowed down and fixes proposed alongside reproducing tests.

Offline capability and data storage

The assistant designs local persistence with Room, Core Data, SwiftData or SQLite, sync logic with conflict handling and robust networking layers with retries and caching.

Build and release automation

Fastlane lanes, Gradle configuration and CI workflows for builds, signing, beta distribution and store uploads are created or repaired, including versioning and release notes. Expiring certificates are flagged early.

Possible hands-on projects

Stocktake app with barcode scanner

A Flutter or React Native app that scans barcodes, records items offline and syncs them with a REST API once a connection is available.

SwiftUI habit tracker

An iOS app with SwiftUI, local persistence, widgets and local notifications, developed entirely with an AI agent. Habits and progress are displayed in clear charts.

Compose feedback form

An Android app built with Jetpack Compose that captures forms with photo attachments, caches them offline and submits them to a back end – with UI tests.

Prerequisites

You program regularly in at least one language and are familiar with Git and an IDE such as VS Code. Hands-on app development experience with Swift, Kotlin, Dart or React Native, plus Xcode or Android Studio and Git.

Technical requirements

Your own laptop with Cursor, Git and your usual development environment installed; a Cursor account with access to agent features is recommended.

Data protection & compliance

Apps often handle sensitive device data such as location, contacts or health information, so generated code must request permissions sparingly and manage consent in line with GDPR. Signing keys, API keys and store credentials do not belong in prompts, and new SDKs and packages should be checked for licensing, tracking behaviour and supply-chain risk.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Berlin Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Online Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Stuttgart Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Online Request
  • Mon, 15 February 2027 – Tue, 16 February 2027 Hanover Request

Frequently asked questions

Do I need prior VS Code experience to use Cursor?

It helps, but it is not essential. Cursor is built on VS Code, so navigation, shortcuts and extensions feel familiar and existing settings can be imported. If you currently work with JetBrains IDEs or other editors, a short introduction during the course gets you up to speed quickly so you can concentrate on the AI features.

How do I prevent confidential code from reaching third parties?

Cursor offers a privacy mode and organisation settings that restrict how code is stored by the provider. You can also use ignore files to exclude sensitive areas from indexing and context. In the course we discuss how to align these options with internal policies, data protection requirements and sound handling of secrets.

What do rules add compared with well-written prompts?

A prompt applies to one request only, whereas rules persist and apply to the whole team. They capture architectural decisions, preferred libraries, testing strategies and style guidelines, so nobody has to repeat that information and the agent produces code that fits your codebase. Rules are versioned with the project and evolve together with it.

Does the course cover iOS, Android and cross-platform equally?

Yes. Working with AI assistants follows the same principles on every platform: provide context, scope tasks and test the results. In the exercises you choose your focus – Swift, Kotlin, Flutter or React Native – and tackle typical tasks for your platform, so mixed teams benefit just as much as specialists.

Can AI work with Xcode and Android Studio?

Many AI assistants can be used inside Android Studio or alongside Xcode, and agents also work from the command line with xcodebuild, Gradle or the Flutter CLI. We show you how to drive builds, tests and simulators so that the agent can check its own results and fix errors iteratively.

How much does “Cursor for Mobile Developers” 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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