Training course · Vibe Coding · Rust
Vibe Coding for Rust Developers
Build software in natural language: from prompt to app, rapid iteration, quality and security checks, and turning prototypes into production.
- 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 Vibe Coding with the everyday processes of Rust. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.
Vibe coding is a new style of software development: you describe in natural language what an application should do, and AI tools generate the code for it. Instead of writing every line yourself, you steer through descriptions, examples and feedback, test the result and refine it in short loops. This dramatically speeds up prototypes, internal tools and experiments. This vendor-neutral course shows you how to use vibe coding productively with tools such as Claude Code, Cursor, Copilot or browser-based app builders.
Knowing the limits matters just as much as speed. Uncontrolled generated code can be unmaintainable, insecure or simply wrong. You will therefore learn to state requirements precisely, safeguard results with tests and reviews, spot typical security flaws and steer the architecture deliberately. Finally, you will map out a clear path from quick prototype to production-ready application, covering version control, deployment, documentation and a clean handover to the team that will run and maintain the solution over the long term.
Rust is gaining ground wherever memory safety and performance have to go hand in hand: in systems software, embedded projects, network services, WebAssembly and security-critical components. The learning curve is steep – ownership, lifetimes, traits and async runtimes challenge even experienced developers. AI coding assistants and agents prove to be patient sparring partners here: they explain borrow checker errors, suggest suitable ownership structures, write tests and property-based tests, port C or C++ modules incrementally and work through Clippy lints. Because the compiler gives very precise feedback, agents can iterate all the way to compiling, safe code. This course teaches you to exploit that feedback loop and to scrutinise unsafe code with particular care.
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?
- Rust developers working on systems and back-end projects
- C and C++ developers moving to Rust or porting modules
- Embedded and IoT developers using Rust
- Security and platform teams focused on memory safety
Typical challenges we address
- Hard-to-understand borrow checker and lifetime errors
- Complex trait hierarchies, generics and async code with Tokio
- Laborious porting of existing C or C++ codebases across FFI boundaries
- Handling unsafe blocks responsibly and justifying each one
What you will be able to do
- You build working applications in natural language with a suitable AI tool.
- You phrase requirements and constraints so that generated results meet your expectations.
- You iterate purposefully, fix errors efficiently and stay in control of the project state.
- You safeguard generated code with tests, reviews and security checks.
- Use AI agents as sparring partners for ownership, lifetimes, traits and async Rust.
- Generate tests, ports and services and verify them with the compiler, Clippy and Miri.
- Systematically assess generated unsafe and FFI code for memory safety.
Course outline
Day 1
Module 1 Vibe coding fundamentals
- What vibe coding is and how it differs from traditional and agentic development
- The tool landscape: AI editors, coding agents and browser-based app builders
- Good use cases: prototypes, internal tools, experiments, learning projects
- Roles: you as product owner, the AI as the one doing the typing
Module 2 From prompt to app
- Describing requirements as a short spec covering users, features and boundaries
- Choosing the tech stack and project structure deliberately rather than leaving it to the AI
- Generating user interfaces from descriptions, sketches and reference examples
- Adding data, APIs and persistence step by step
Module 3 Iterating and fixing problems
- Working in small, verifiable steps and committing regularly
- Feeding error messages, logs and screenshots back to the AI
- Recognising stuck sessions, rolling back and restarting with fresh context
- Creating project rules and context files to avoid repeating yourself
Module 4 Securing quality and safety
- Having the AI generate tests and critically assessing what they actually prove
- Reviewing generated changes for readability, duplication and needless complexity
- Spotting typical security flaws: secrets in code, missing validation, exposed endpoints
- Assessing dependencies, licences and data protection in generated solutions
Day 2
Module 5 From prototype to production
- Setting criteria for evolving a prototype versus rebuilding it
- Refactoring, cleaning up architecture and documenting with AI support
- Setting up version control, CI and deployment for generated applications
- Planning operations, monitoring and handover to a team or IT
Module 6 Practice lab: Rust
- Understanding and fixing compiler errors
- Tests and property-based tests
- Porting C and C++ modules
- Async services with Tokio
- Clippy and idiomatic code
- Reviewing unsafe code
Module 7 Data protection, quality & transfer to daily work
- Rust is often used in security-critical components for which the Cyber Resilience Act sets requirements on vulnerability handling and SBOMs. Check new crates for vulnerabilities and licences with cargo-audit or cargo-deny, and treat proprietary systems code as confidential when using cloud-hosted models.
- 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
Understanding and fixing compiler errors
The assistant explains borrow checker and lifetime errors in plain language, deliberately proposes alternative ownership structures such as references, Rc or cloning, and iterates with cargo check until the build is clean.
Tests and property-based tests
The AI writes unit and integration tests, doc tests and property-based tests with proptest that check invariants over many generated inputs, uncovering edge cases in parsers or algorithms.
Porting C and C++ modules
Existing code is moved to Rust module by module, FFI bindings are created with bindgen or cbindgen and behaviour is safeguarded by shared tests run against the old and new implementations.
Async services with Tokio
Specifications become HTTP or gRPC services built with Axum or Tonic, including structured error types, graceful shutdown, tracing and sensible handling of cancellation and timeouts.
Clippy and idiomatic code
Clippy lints are worked through systematically, error handling standardised with thiserror or anyhow, and iterators, pattern matching and traits used idiomatically. Existing tests safeguard every change.
Reviewing unsafe code
The agent inventories unsafe blocks, documents their safety invariants, proposes safe alternatives and runs Miri to detect undefined behaviour. Each justification is recorded as a SAFETY comment in the code.
Possible hands-on projects
Fast log parser
A Rust CLI that streams large log files, detects patterns with regular expressions and outputs statistics – with benchmarks comparing it against a scripting-language version.
Axum microservice
A small REST service using Axum, SQLx, structured tracing and integration tests, planned and implemented end to end by an AI agent.
WebAssembly module
A compute-heavy function, such as image processing or validation, packaged as a WebAssembly module with wasm-bindgen and embedded in a simple web page.
Prerequisites
Basic programming knowledge and some Git experience are helpful; you should be able to read simple code and make sense of error messages. Basic Rust experience with Cargo, ownership and traits, plus experience in at least one other systems or back-end language.
Technical requirements
Your own laptop with an up-to-date browser, Git and an AI coding tool of your choice, such as an AI editor or coding agent with an active account.
Data protection & compliance
Rust is often used in security-critical components for which the Cyber Resilience Act sets requirements on vulnerability handling and SBOMs. Check new crates for vulnerabilities and licences with cargo-audit or cargo-deny, and treat proprietary systems code as confidential when using cloud-hosted models.
Suggested dates
All dates are suggestions – your preferred date is always possible.
- Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
- Tue, 8 December 2026 – Wed, 9 December 2026 Berlin Request
- Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
- Wed, 13 January 2027 – Thu, 14 January 2027 Online Request
- Wed, 27 January 2027 – Thu, 28 January 2027 Hanover Request
- Thu, 4 February 2027 – Fri, 5 February 2027 Online Request
Frequently asked questions
Is vibe coding only suitable for quick prototypes?
Vibe coding shines with prototypes, internal tools and experiments. With the right practices, namely clear specifications, tests, reviews and sound version control, results can also be turned into production-ready applications. The course teaches you to manage that transition deliberately and to recognise early on when rebuilding is the wiser option.
Which tools are used in the course?
The course is vendor-neutral. We work with the main tool categories: AI editors such as Cursor or Windsurf, coding agents such as Claude Code or Codex, and browser-based app builders. You are welcome to use your preferred tool, as the principles of specification, iteration, quality and security apply to all of them.
How should I deal with security risks in generated code?
Generated code often contains typical weaknesses such as hard-coded credentials, missing input validation or overly open interfaces. You learn to check specifically for these patterns, build security requirements into the specification from the start, use automated scanning and require a deliberate human sign-off before every deployment.
Can AI help me get started with Rust?
Very much so. AI assistants explain compiler errors patiently and in the context of your own code, show alternative approaches and explain why the borrow checker rejects a construct. The key is to understand the explanations rather than accept suggestions blindly, so the course relies on hands-on exercises in which you work out solutions together with the AI.
How reliable are AI ports from C++ to Rust?
They work well for clearly bounded modules when behaviour is protected by tests. The tricky parts are pointer arithmetic, shared mutable state or undefined behaviour in the original. On the course you learn to port incrementally, run differential tests against the old implementation and keep unsafe code to a deliberate minimum.
How much does “Vibe Coding for Rust 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.
More courses for Rust Developers
- Claude Code for Rust Developers
- Agentic Coding for Rust Developers
- Cursor for Rust Developers
- GitHub Copilot for Rust Developers
- OpenAI Codex for Rust Developers
- Windsurf for Rust Developers
- Model Context Protocol (MCP) for Rust Developers
- AI Agent Development for Rust Developers
- RAG & LLM Applications for Rust Developers
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