Training course · Vibe Coding · Software Architecture

Vibe Coding for Software Architects

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 Software Architecture. 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.

When AI agents write large parts of the code, architecture becomes more important, not less: clear module boundaries, documented decisions and verifiable quality goals are the frame that keeps generated code consistent. AI assistants also support architects directly, for example by analysing existing codebases, producing C4 diagrams, drafting architecture decision records and weighing alternatives against quality attributes. Fitness functions and architecture tests can be generated and anchored in your pipelines. In this course you learn to use AI as a sparring partner for architectural decisions, prepare architectural knowledge so that coding agents follow it reliably and spot erosion early in fast-growing codebases.

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 architects and solution architects
  • Enterprise architects with links to application development
  • Senior developers and tech leads with architectural responsibility
  • Platform and cloud architects
  • Owners of architecture governance and review boards

Typical challenges we address

  • Architecture documentation goes stale quickly and drifts from the actual code
  • Decisions are made verbally and their context is lost
  • Gradual architectural erosion through cyclic dependencies and violated layer boundaries
  • Without clear guidance, AI-generated code ignores established patterns and conventions

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 to analyse existing systems, evaluate architectural options and record decisions as ADRs.
  • Anchor architecture rules as fitness functions in the pipeline and detect erosion early.
  • Shape context and rules so that AI coding agents reliably respect your architectural guidelines.

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: Software Architecture
  • Documenting architecture decisions
  • Reconstructing existing architecture
  • Evaluating alternatives
  • Generating fitness functions
  • Guardrails for coding agents
  • Carving out domains
Module 7 Data protection, quality & transfer to daily work
  • Architecture documents often describe security-relevant details such as network zones and data flows: you learn which information may be shared with AI services, how to assess licensing risks of components and how architectural decisions traceably reflect GDPR, NIS2 and Cyber Resilience Act requirements.
  • 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

Documenting architecture decisions

Turn discussions, meeting notes and pull requests into structured architecture decision records with context, options considered, decision and consequences, stored consistently in the repository. Related decisions are linked automatically.

Reconstructing existing architecture

Analyse existing codebases, extract modules, dependencies and interfaces and generate up-to-date C4 diagrams as diagrams-as-code with PlantUML, Mermaid or Structurizr. Diagrams can be refreshed automatically on every build.

Evaluating alternatives

Compare options such as a modular monolith, microservices or event-driven integration against quality scenarios, cost and team structure, and make trade-offs visible following ATAM principles.

Generating fitness functions

Express architecture rules such as layer access, forbidden dependencies or naming conventions as automated tests with ArchUnit, dependency-cruiser or similar tools and wire them into CI.

Guardrails for coding agents

Describe architectural principles, module boundaries and patterns in rule files and context documents so AI agents follow them reliably when generating code, and spot deviations in review.

Carving out domains

Derive bounded contexts, aggregates and context maps following domain-driven design from event storming results and business descriptions, and use them to shape teams and services.

Possible hands-on projects

ADR assistant

A command-line tool that turns bullet points into a complete ADR from a template, links related decisions and updates an index in the repository.

Dependency visualiser

A script that analyses import relationships in a codebase, flags cycles and layer violations and renders an interactive diagram in the browser.

Architecture Q&A over repos

A small application that indexes ADRs, diagrams and code and answers architecture questions with references to the underlying sources. New team members onboard faster.

Prerequisites

Basic programming knowledge and some Git experience are helpful; you should be able to read simple code and make sense of error messages. You have several years of development experience and have made or supported architectural decisions in larger software systems.

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

Architecture documents often describe security-relevant details such as network zones and data flows: you learn which information may be shared with AI services, how to assess licensing risks of components and how architectural decisions traceably reflect GDPR, NIS2 and Cyber Resilience Act requirements.

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, 17 February 2027 – Thu, 18 February 2027 Munich 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 make architecture decisions?

AI is a strong sparring partner: it offers options, names trade-offs, finds gaps in reasoning and documents decisions in a structured way. Responsibility stays with people, because architecture depends on business context, team skills, budget and risk appetite. In the course you learn to use AI so that decisions are better reasoned and made faster.

How do we stop AI agents from eroding the architecture?

Through a combination of clear context and automated checks: rule files and ADRs describe module boundaries and patterns, fitness functions and architecture tests in CI block violations, and reviews focus on structural changes. Architecture thus turns from documentation into a verifiable guardrail for humans and agents alike.

How much does “Vibe Coding for Software Architects” 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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