Training course · Cursor · Go

Cursor for Go 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

“Cursor for Go Developers” is designed for roles such as Go developers in back-end and platform teams, Developers of cloud-native tools, operators and CLIs and Site reliability engineers maintaining their own Go code and shows step by step how to use Cursor productively, safely and transparently in Go – from the fundamentals to advanced workflows.

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.

Go is the language behind many cloud-native tools, microservices, CLIs and infrastructure components. Its strengths are simplicity, fast compilation and built-in concurrency – yet goroutines, channels, context handling and error handling all demand discipline. AI coding assistants and agents suit Go particularly well: the compiler, go vet and the race detector provide fast, unambiguous feedback that agents can iterate on. Typical tasks include table-driven tests, gRPC and HTTP handlers generated from specifications, tracking down race conditions or goroutine leaks and refactoring towards clean interfaces. This course shows you how to get idiomatic Go from AI and how to verify the results with Go’s own tooling.

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?

  • Go developers in back-end and platform teams
  • Developers of cloud-native tools, operators and CLIs
  • Site reliability engineers maintaining their own Go code
  • Software architects designing high-performance microservices

Typical challenges we address

  • Subtle concurrency bugs such as race conditions, deadlocks and goroutine leaks
  • Repetitive boilerplate in error handling, handlers and tests
  • Inconsistent project layouts and interface boundaries in growing codebases
  • Difficult performance analysis of memory allocations and latency

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.
  • Have AI agents produce idiomatic Go code, tests and services that follow Go conventions.
  • Use AI deliberately to analyse concurrency and performance problems.
  • Verify generated code with the compiler, go vet, the race detector, linting and benchmarks.

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: Go
  • Writing table-driven tests
  • Implementing gRPC and HTTP services
  • Finding concurrency bugs
  • Idiomatic refactoring
  • Profiling performance
  • Building CLIs and tools
Module 7 Data protection, quality & transfer to daily work
  • Go tooling often runs deep in the infrastructure, so keep kubeconfigs, tokens and certificates strictly out of an AI assistant’s context. Check new modules for provenance, licence and known vulnerabilities, for instance with govulncheck, and record dependencies in an SBOM as required under the Cyber Resilience Act for products with digital elements.
  • 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

Writing table-driven tests

The agent generates idiomatic table-driven tests with subtests, test helpers and fakes for interfaces, runs go test with the race detector and adds missing edge cases until coverage is where you want it.

Implementing gRPC and HTTP services

Protobuf definitions or OpenAPI specs become handlers, middleware for logging and authentication, context propagation with timeouts and clean error returns. Integration tests exercise the endpoints against realistic requests and failure cases.

Finding concurrency bugs

The AI analyses race detector output, goroutine dumps and code using channels or mutexes, explains the cause of deadlocks or leaks and proposes fixes using errgroup or context cancellation.

Idiomatic refactoring

Large packages are untangled, small consumer-side interfaces introduced, errors wrapped and checked with errors.Is, and code aligned with golangci-lint rules. Existing tests keep behaviour safe throughout.

Profiling performance

pprof profiles and benchmark results are interpreted, hotspots and unnecessary allocations identified, and optimisations backed by before-and-after benchmarks. Improvements become measurable rather than merely assumed.

Building CLIs and tools

The assistant creates command-line tools with Cobra or the standard library, including configuration, structured logging, cross-compilation and release automation. Tests, help texts and clear command documentation are included.

Possible hands-on projects

Health check aggregator

A Go service that polls the health endpoints of many services concurrently, merges the results and exposes them as JSON and Prometheus metrics.

Log shipper CLI

A lean command-line tool that tails log files, filters entries and ships them in batches to an HTTP endpoint – with backoff and graceful shutdown.

Kubernetes resource report

A CLI built on client-go that reads resource requests and limits across all deployments and presents anomalies in a clear table.

Prerequisites

You program regularly in at least one language and are familiar with Git and an IDE such as VS Code. Hands-on Go experience including goroutines, interfaces and modules, plus a working knowledge of Git and containers.

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

Go tooling often runs deep in the infrastructure, so keep kubeconfigs, tokens and certificates strictly out of an AI assistant’s context. Check new modules for provenance, licence and known vulnerabilities, for instance with govulncheck, and record dependencies in an SBOM as required under the Cyber Resilience Act for products with digital elements.

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
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Tue, 12 January 2027 – Wed, 13 January 2027 Kaiserslautern Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Online Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Bremen 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 AI really write idiomatic Go?

With good context, yes. Without guidance, models sometimes drift towards patterns from other languages, such as large interfaces or excessive abstraction. On the course you capture your Go conventions, linter configuration and example code so the assistant favours simple, idiomatic solutions, and you verify the output with golangci-lint.

Can AI reliably detect race conditions?

AI is a powerful analysis aid but no substitute for the race detector. The combination works best: the agent runs tests with the race detector, interprets the reports and proposes fixes. You learn to set up that loop and to critically assess any suggested synchronisation changes before accepting them.

How much does “Cursor for Go 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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