Training course · Vibe Coding · API Development

Vibe Coding for API 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

“Vibe Coding for API Developers” is designed for roles such as Backend developers building REST, GraphQL or gRPC interfaces, API architects and owners of API governance and Integration developers connecting partners and platforms and shows step by step how to use Vibe Coding productively, safely and transparently in API Development – from the fundamentals to advanced workflows.

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.

APIs form the backbone of modern software landscapes and are increasingly the interface through which AI agents interact with systems. AI coding assistants speed up the entire API lifecycle, from drafting an OpenAPI or AsyncAPI specification to generating server stubs, clients and contract tests, through to documentation and versioning. At the same time, demands for consistency, security and backward compatibility keep rising, because APIs are consumed by many teams, partners and automated agents. In this course you learn to practise API-first development with AI support, enforce design guidelines automatically, catch breaking changes early and expose existing interfaces to AI agents through the Model Context Protocol or tool definitions.

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?

  • Backend developers building REST, GraphQL or gRPC interfaces
  • API architects and owners of API governance
  • Integration developers connecting partners and platforms
  • Platform engineering teams running API gateways and developer portals
  • Developers making company data available to AI agents

Typical challenges we address

  • Inconsistent API design across teams with differing conventions for errors, pagination and versioning
  • Specification, implementation and documentation drift apart
  • Breaking changes are only discovered by consumers
  • Securing authentication, authorisation and rate limiting as users and agent traffic grow

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.
  • Practise API-first development with AI support, from specification to clients, tests and documentation.
  • Automate design governance, contract testing and breaking-change detection in your pipeline.
  • Make existing APIs available to AI agents securely and in a controlled way, for example via the Model Context Protocol.

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: API Development
  • Generating OpenAPI specs
  • Generating servers and clients
  • Building contract tests
  • Detecting breaking changes
  • Reviewing API security
  • Opening APIs to AI agents
Module 7 Data protection, quality & transfer to daily work
  • APIs frequently carry personal and confidential data: you learn to create specifications and sample data without real customer records, keep API keys and tokens out of the AI context and apply data protection by design under the GDPR as well as NIS2 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

Generating OpenAPI specs

Draft complete OpenAPI specifications with schemas, examples, error objects and security schemes from requirements, domain models or existing code, and check them against your style guide rules.

Generating servers and clients

Derive controller scaffolding, validation logic and type-safe client SDKs for several languages from a specification, keeping generated parts cleanly separated from hand-written business logic. Regenerating after spec changes is simple.

Building contract tests

Define consumer-driven contracts, generate test cases for edge values, error paths and authentication, and run them automatically in CI against both the specification and the live implementation.

Detecting breaking changes

Compare two versions of a specification, identify incompatible changes, write migration notes for consumers and plan deprecation strategies using versioning and sunset headers. The check runs on every pull request.

Reviewing API security

Analyse endpoints for typical weaknesses from the OWASP API Security Top 10, such as broken object-level authorisation, mass assignment or missing rate limits, and propose fixes.

Opening APIs to AI agents

Expose existing interfaces as MCP servers or tool definitions, phrase descriptions and parameters so agents use them correctly and scope permissions so agents can only perform approved actions.

Possible hands-on projects

API linter with house rules

A command-line tool that checks OpenAPI files against your design guidelines and posts clear improvement suggestions directly on the pull request.

Mock server from spec

A small service that generates realistic sample responses from a specification so frontend teams can work in parallel with backend development.

MCP server for an internal API

An MCP server that exposes selected endpoints of an internal REST API as tools for AI assistants, with authentication and logging.

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 build backend applications in a mainstream language such as Java, C#, TypeScript, Python or Go and understand HTTP, JSON and REST fundamentals.

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

APIs frequently carry personal and confidential data: you learn to create specifications and sample data without real customer records, keep API keys and tokens out of the AI context and apply data protection by design under the GDPR as well as NIS2 requirements.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Mon, 7 December 2026 – Tue, 8 December 2026 Salzburg Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Wed, 13 January 2027 – Thu, 14 January 2027 Online Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Bremen Request
  • Thu, 11 February 2027 – Fri, 12 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.

Is spec-first still worth it when AI writes code so quickly?

More than ever. A precise specification is the best context you can give an AI assistant: it pins down data structures, error cases and security requirements, serves as a contract for consumers and underpins your tests. Without one, AI quickly produces inconsistent endpoints. In the course you use the spec as the single source for generation and validation.

What is the difference between a REST API and an MCP server?

A REST API is aimed at developers and applications, whereas an MCP server exposes capabilities in a standardised format for AI assistants and agents, including descriptions the model can interpret. An MCP server is often a thin layer on top of existing APIs. You learn when that step pays off and how to implement it securely.

How much does “Vibe Coding for API 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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