Training course · Agentic Coding · UX Design & Prototyping

Agentic Coding for UX Designers

Use autonomous coding agents effectively: specs instead of prompts, task decomposition, test-driven loops, multi-agent setups and governance.

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

“Agentic Coding for UX Designers” is designed for roles such as UX and UI designers, Product designers and interaction designers and UX researchers who want to test variants quickly and shows step by step how to use Agentic Coding productively, safely and transparently in UX Design & Prototyping – from the fundamentals to advanced workflows.

Agentic coding means working with AI agents that carry out development tasks largely on their own: they read code, plan changes, run commands and tests, and correct themselves based on the results. Tools such as Claude Code, OpenAI Codex, the GitHub Copilot coding agent and Cursor’s agent mode have made this way of working practical for everyday use. This vendor-neutral course teaches the underlying methodology so that you achieve reliable results whatever the tool, and redefine the developer’s role within your engineering team.

The core shift is from ad hoc prompts to robust specifications. You will learn to decompose and describe tasks so that agents solve them reliably, to set up test-driven loops in which tests act as objective acceptance criteria, and to run several agents in parallel or with a division of labour. We also cover review strategies for agent-generated code and team governance: permissions, security boundaries, accountability, cost control and the gradual introduction of agentic workflows into your existing development processes.

AI coding tools are shifting the boundary between design and development: UX designers can now build interactive prototypes in real code instead of only drawing clickable mock-ups. A screenshot, a sketch or a short description quickly becomes a working interface with real states, form logic and sample data that feels like a finished product in usability testing. AI assistants also translate design tokens, component libraries and accessibility checks straight into code. In this course you learn how vibe coding and AI agents take you from idea to testable prototype faster, how to hand results over cleanly to engineering teams and where the line runs between a prototype and production-ready software.

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?

  • UX and UI designers
  • Product designers and interaction designers
  • UX researchers who want to test variants quickly
  • Product owners and product managers with design responsibility
  • Design system teams working closely with frontend engineering

Typical challenges we address

  • Static mock-ups barely capture interactions, states and real data
  • Hand-offs to engineering lose details, spacing and behavioural logic
  • Long waits for engineering capacity to run experiments and A/B variants
  • Accessibility is often considered late and incompletely

What you will be able to do

  • You understand how coding agents work and choose the right tool and level of autonomy.
  • You write specifications and project context that agents can work with reliably.
  • You break initiatives into verifiable sub-tasks and steer agents through test-driven loops.
  • You use multi-agent setups and parallel work in a controlled way.
  • Build interactive, code-based prototypes with AI and test ideas with users much earlier.
  • Translate design systems and tokens into code and improve hand-offs to engineering teams.
  • Review prototypes systematically for accessibility and understand the line between prototype and production code.

Course outline

Day 1

Module 1 Foundations of agentic development
  • How coding agents work: tool calls, context windows and feedback loops
  • Comparing tools: terminal agents, IDE agents and cloud agents
  • Recognising suitable tasks and choosing levels of autonomy deliberately
  • The new role in the team: from implementation to steering and acceptance
Module 2 Specifications instead of prompts
  • Describing tasks with goal, context, constraints and acceptance criteria
  • Keeping project context in files such as CLAUDE.md, AGENTS.md or rules
  • Plan-first approach: let the agent draft a solution and review it before implementation
  • Versioning specifications and maintaining them as part of the repository
Module 3 Task decomposition and test-driven agent loops
  • Breaking large initiatives into independent, verifiable sub-tasks
  • Having tests written first and using them as an objective stopping criterion
  • Using linters, type checks and builds as automatic feedback
  • Recognising stuck loops and restarting with a new strategy
Module 4 Multi-agent setups and parallel work
  • Defining specialised subagents for research, implementation, testing and review
  • Organising parallel work with branches, worktrees and isolated environments
  • Orchestration: merging results and resolving conflicts
  • Sharing tools and data sources through MCP

Day 2

Module 5 Review, security and team governance
  • Review strategies for large, agent-generated changes
  • Defining permissions, sandboxing and protection against prompt injection
  • Embedding agents in CI pipelines and pull request processes
  • Planning team guidelines, accountability, costs and a phased rollout
Module 6 Practice lab: UX Design & Prototyping
  • Clickable prototypes in code
  • Generating test variants
  • Turning design tokens into code
  • Checking accessibility
  • Designing microinteractions
  • Synthesising research
Module 7 Data protection, quality & transfer to daily work
  • Prototypes often contain unreleased product ideas and research data from participants: you learn to pseudonymise interview notes in line with the GDPR, clarify rights to fonts, images and generated assets and plan early for the European Accessibility Act.
  • 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

Clickable prototypes in code

Turn sketches, wireframes or screenshots into working web prototypes with navigation, form validation, loading and error states and realistic sample data that can be tested directly in the browser.

Generating test variants

Produce several design variants of a flow in parallel, for example onboarding or checkout, and prepare them for usability tests or A/B experiments with minimal adjustments.

Turning design tokens into code

Structure colours, typography, spacing and radii from your design system as tokens and convert them into CSS variables, Tailwind configuration or theme files for component libraries.

Checking accessibility

Examine prototypes for contrast, semantic HTML, keyboard navigation, focus order and ARIA attributes and have concrete WCAG-based improvements applied directly in the code. Issues are fixed before reaching engineering.

Designing microinteractions

Describe transitions, animations and feedback states and implement them in CSS or JavaScript, so you can judge timing and effect early in the real medium rather than in a drawing tool.

Synthesising research

Cluster notes from interviews and usability tests, surface patterns and pain points and derive prioritised design hypotheses that feed straight into the next prototype iteration.

Possible hands-on projects

Onboarding prototype

A multi-step onboarding flow as a web app with a progress indicator, validation and saved inputs, ready for moderated usability testing.

Token converter

A small tool that reads exported design tokens and generates CSS variables, a colour palette with contrast ratios and a preview page.

Component playground

An overview page showing your design system’s buttons, forms and cards in every state, including light and dark mode. It doubles as a living reference.

Prerequisites

You have several years of development experience, are confident with Git, testing and CI, and ideally have already used AI coding tools. You have experience in UX or UI design and with common design tools; no programming skills are required, although a basic understanding of HTML and CSS helps.

Technical requirements

Your own laptop with Git, a terminal and your development environment, plus access to at least one coding agent such as Claude Code, Codex, Copilot or Cursor.

Data protection & compliance

Prototypes often contain unreleased product ideas and research data from participants: you learn to pseudonymise interview notes in line with the GDPR, clarify rights to fonts, images and generated assets and plan early for the European Accessibility Act.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Salzburg Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Online Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Bremen Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Online Request
  • Mon, 8 February 2027 – Tue, 9 February 2027 Augsburg Request

Frequently asked questions

How does agentic coding differ from vibe coding?

Vibe coding relies on fast, intuitive iteration in natural language and is particularly suited to prototypes. Agentic coding is an engineering discipline for professional codebases: precise specifications, tests as acceptance criteria, clear permissions and structured reviews ensure that agents deliver reliable, maintainable results even in complex, long-lived projects.

Is the course tied to a specific tool?

No. The course teaches methods that work with Claude Code, OpenAI Codex, the GitHub Copilot coding agent, Cursor and comparable tools. The exercises highlight differences and common ground, for example in context files, permissions and subagents. You can work with whichever tool your organisation already uses or plans to adopt.

How do we stay in control of quality and security with autonomous agents?

Control comes from several layers: tightly scoped permissions and sandboxing, tests and static analysis as automatic checks, mandatory human review before merging, and clear team rules on accountability. During the course you develop a governance concept that fits your processes, security requirements and regulatory obligations.

Do I need to know how to code as a designer?

No. You describe interfaces and behaviour in plain language, with sketches or screenshots, and the AI tool generates the code. It helps to understand basic terms such as component, state or CSS class so you can steer precisely. We cover these concepts hands-on in the course, so you can adapt and evolve prototypes on your own.

Can the engineering team reuse the prototype code?

Sometimes, but more often it serves as a precise specification. Prototypes are optimised for speed, not for security, performance or maintainability. If you use the same component library and tokens as the product from the outset, reuse becomes much more likely. In the course you work out how to design hand-offs that benefit both sides.

How much does “Agentic Coding for UX Designers” 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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