Training course · Agentic Coding · JavaScript & TypeScript

Agentic Coding for JavaScript and TypeScript Developers

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 JavaScript and TypeScript Developers” is a hands-on course for roles such as Front-end and full-stack developers working in JavaScript or TypeScript, Teams migrating an existing JavaScript codebase to TypeScript and Library and SDK maintainers in the npm ecosystem. Rather than learning Agentic Coding in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from JavaScript & TypeScript.

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.

JavaScript and TypeScript now run in the browser, on servers, in build pipelines and on edge platforms. That breadth comes with complex toolchains: bundlers, transpilers, linters, package managers and an npm ecosystem that never stands still. AI coding assistants and agents remove a great deal of that friction. They migrate JavaScript modules to TypeScript incrementally, derive precise types from API responses, fix ESLint findings, write Vitest or Jest tests and explain nested generics in plain language. For the output to fit your project, the tools need clear guardrails: tsconfig strictness, module system, coding guidelines and test commands. This course shows you how to provide that context deliberately and how to scrutinise generated code.

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?

  • Front-end and full-stack developers working in JavaScript or TypeScript
  • Teams migrating an existing JavaScript codebase to TypeScript
  • Library and SDK maintainers in the npm ecosystem
  • Tech leads who own tooling, linting and build processes

Typical challenges we address

  • Gradual type erosion through any, type assertions and lax tsconfig settings
  • Complex toolchains mixing bundlers, transpilers, ESM and CommonJS that are hard to debug
  • Huge dependency trees carrying security and maintenance risk
  • Asynchronous code with hard-to-reproduce race conditions and gaps in error handling

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.
  • Use AI agents deliberately for TypeScript migrations, typing work and test generation.
  • Feed assistants your tsconfig, lint rules and project conventions so generated code fits your existing stack.
  • Critically assess proposed npm dependencies and generated code for type safety and security.

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: JavaScript & TypeScript
  • Incremental TypeScript migration
  • Deriving types from APIs and schemas
  • Writing Vitest and Jest tests
  • Fixing ESLint findings and code smells
  • Debugging build and bundler issues
  • Upgrading dependencies
Module 7 Data protection, quality & transfer to daily work
  • The npm ecosystem is a frequent target of supply-chain attacks, so vet every dependency the AI suggests for provenance, maintenance and licence (for example copyleft terms). Keep API keys and tokens out of prompts and clarify contractually whether your source code may be used to train the provider’s 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

Incremental TypeScript migration

The agent converts JavaScript files to TypeScript module by module, infers types from usage, replaces any with precise types and tightens tsconfig strictness in controlled steps until the compiler runs clean.

Deriving types from APIs and schemas

JSON samples, OpenAPI specifications or database schemas are turned into TypeScript interfaces and Zod schemas for runtime validation, so front end and back end share one consistent contract.

Writing Vitest and Jest tests

For utilities, hooks and services, the AI generates unit tests with sensible mocks, fake timers and snapshot strategies, runs them and fixes failing cases on its own.

Fixing ESLint findings and code smells

The assistant works through lint warnings systematically, replaces outdated patterns such as callback chains with async/await and explains for each rule why the change makes sense.

Debugging build and bundler issues

Error output from Vite, webpack or esbuild is analysed, ESM/CommonJS conflicts are resolved and configuration for path aliases, tree shaking or source maps is corrected.

Upgrading dependencies

The AI reads changelogs for major npm package upgrades, adapts code to breaking changes, updates lockfiles and verifies everything through a type check and a full test run.

Possible hands-on projects

Type-safe API client

A small TypeScript package that generates a type-safe fetch client with Zod validation from an OpenAPI specification, ready to publish to npm with tests.

Browser extension

A TypeScript browser extension that analyses page content and copies it to the clipboard in a structured format – including manifest, content script and automated build.

Monorepo health check

A Node script that inspects workspaces in a monorepo, detects duplicate or inconsistent dependency versions and proposes a clean-up plan.

Prerequisites

You have several years of development experience, are confident with Git, testing and CI, and ideally have already used AI coding tools. Good command of modern JavaScript, a working knowledge of TypeScript and experience with npm, pnpm or yarn and Git.

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

The npm ecosystem is a frequent target of supply-chain attacks, so vet every dependency the AI suggests for provenance, maintenance and licence (for example copyleft terms). Keep API keys and tokens out of prompts and clarify contractually whether your source code may be used to train the provider’s models.

Suggested dates

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

  • Thu, 26 November 2026 – Fri, 27 November 2026 Online Request
  • Wed, 9 December 2026 – Thu, 10 December 2026 Berlin Request
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Thu, 7 January 2027 – Fri, 8 January 2027 Online Request
  • Wed, 13 January 2027 – Thu, 14 January 2027 Stuttgart Request
  • Tue, 19 January 2027 – Wed, 20 January 2027 Online 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.

How well do AI assistants handle complex TypeScript types?

Current models understand generics, conditional types and mapped types very well and can explain them clearly. For highly complex type constructions, though, the compiler remains the ultimate judge. On the course you learn to have the agent run tsc iteratively, so suggestions are not merely plausible but genuinely type-correct before you accept them.

Is the course suitable for pure front-end developers?

Yes. The focus is the language and its tooling – typing, tests, linting, builds and dependencies – which matter equally on the front end and the back end. If you want to go deeper into React or Node.js specifically, our catalogue includes dedicated course variants for those stacks.

How much does “Agentic Coding for JavaScript and TypeScript 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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