Training course · Cursor · Internal Tools & Automation

Cursor for Internal Tools and Automation

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 Internal Tools & Automation. 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.

Almost every company has a long backlog of small tools nobody gets round to building: admin interfaces for master data, scripts for recurring data reconciliation, Slack or Teams bots, report generators and glue between SaaS systems. With AI coding assistants and agents, internal tools like these can be built in hours rather than weeks. Developers, ops and platform teams therefore shift their focus from writing code to clear requirements, secure access and reliable operation. Internal tools in particular often hold far-reaching rights over production data and quickly become business-critical. In this course you learn to build internal tools and automations rapidly with AI, implement authentication and permissions correctly from the start and design solutions that stay documented, tested and maintainable.

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?

  • Software developers maintaining internal applications and scripts
  • DevOps, SRE and platform teams
  • IT administrators with automation responsibilities
  • Operations and RevOps engineers
  • Business process automation teams

Typical challenges we address

  • A long backlog of internal tools that never get prioritised next to product work
  • Manual reconciliation between SaaS systems, spreadsheets and databases that is prone to error
  • Internal tools with excessive permissions, no logging and no clear owner
  • Undocumented scripts that only one person understands

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.
  • Build internal tools, bots and automations with AI agents quickly and to a solid standard.
  • Implement authentication, permissions, logging and secrets management correctly from the outset.
  • Design automations that are documented, testable and operable, so they do not depend on individual people.

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: Internal Tools & Automation
  • Generating admin interfaces
  • Automating data reconciliation
  • Chat bots for teams
  • Automating ops runbooks
  • Generating reports and exports
  • Building agent workflows
Module 7 Data protection, quality & transfer to daily work
  • Internal tools often access employee, customer and production data: you learn to grant permissions on a least-privilege basis, keep secrets in vaults rather than code, log access and take GDPR and works council requirements into account for tools that touch employee data.
  • 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

Generating admin interfaces

Create CRUD interfaces from a database schema or API with search, filters, validation, role-based permissions and an audit log, so business teams can maintain master data safely.

Automating data reconciliation

Write scripts that regularly pull data from CRM, ERP, ticketing systems and spreadsheets, reconcile it and report discrepancies, with retry logic, idempotency and clear error messages.

Chat bots for teams

Build Slack or Teams bots that answer status queries, trigger approvals, announce deployments or provide on-call information while only executing explicitly permitted actions. Every action is logged with the user ID.

Automating ops runbooks

Turn recurring operational tasks such as user management, certificate renewal or log analysis into reviewed scripts and workflows, safeguarded with a dry-run mode and logging.

Generating reports and exports

Automatically prepare regular analyses from databases and APIs as PDF, spreadsheet or email, including scheduling, parameters and traceable data sources. Manual copy-and-paste between systems disappears entirely.

Building agent workflows

Connect AI agents to tools such as the ticketing system, knowledge base and internal APIs, for example via MCP, to pre-qualify requests, gather data and prepare drafts for human approval.

Possible hands-on projects

Onboarding automation

A workflow that creates accounts in several systems for new starters, assigns groups and sends the line manager a checklist of outstanding steps.

Licence overview

An internal dashboard that pulls usage data from SaaS tools, flags unused licences and shows costs per team at a glance.

Deployment bot

A chat bot that announces deployments, summarises changes from pull requests and notifies the right people when a pipeline fails.

Prerequisites

You program regularly in at least one language and are familiar with Git and an IDE such as VS Code. You have programming experience in a language such as Python, TypeScript or Go and know the basics of APIs, databases and the command line.

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

Internal tools often access employee, customer and production data: you learn to grant permissions on a least-privilege basis, keep secrets in vaults rather than code, log access and take GDPR and works council requirements into account for tools that touch employee data.

Suggested dates

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

  • Mon, 23 November 2026 – Tue, 24 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Augsburg Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
  • Wed, 13 January 2027 – Thu, 14 January 2027 Online Request
  • Mon, 25 January 2027 – Tue, 26 January 2027 Bremen Request
  • Mon, 1 February 2027 – Tue, 2 February 2027 Online 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.

When is a custom internal tool better than an off-the-shelf product?

When a process is specific to your organisation, spans several systems or standard tools only fit after heavy customisation. AI cuts development cost considerably, but operation and maintenance remain. In the course you learn to weigh effort against benefit realistically and build tools that keep working with minimal upkeep.

How do we secure internal tools that were built quickly with AI?

With fixed guardrails: sign-in through your central identity provider, role-based permissions, no secrets in code, logging of every write action and a short review before go-live. These building blocks can be stored as a template so AI agents include them automatically in every new tool. You create exactly these templates in the course.

How much does “Cursor for Internal Tools and Automation” 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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