Training course · Agentic Coding · Node.js Back End

Agentic Coding for Node.js Back-End 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

This course connects Agentic Coding with the everyday processes of Node.js Back End. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

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.

For many teams, Node.js is the backbone of REST and GraphQL APIs, real-time services, serverless functions and integration layers. Typical back-end work follows recurring patterns: routes and validation, database access with Prisma, Drizzle or TypeORM, authentication, error handling, logging and tests against real dependencies. AI coding assistants and agents handle these patterns reliably once they understand the project architecture. They generate endpoints from OpenAPI specifications, migrate Express applications to modular structures, write integration tests with Testcontainers and analyse memory leaks or event-loop-blocking operations. This course teaches you to use agents in a way that keeps security, observability and maintainability firmly intact.

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?

  • Back-end developers using Express, Fastify or NestJS
  • Full-stack developers responsible for API layers
  • Developers building serverless functions and integration services
  • Software architects designing Node.js-based microservices

Typical challenges we address

  • Organically grown Express apps with no clear layering and scattered error handling
  • Insufficient input validation and weaknesses in authentication and authorisation
  • Performance issues caused by blocking code or memory leaks that are hard to diagnose
  • Missing integration tests against databases, queues and external APIs

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.
  • Have AI agents build endpoints, data layers and integration tests that fit your Node.js architecture.
  • Use AI to analyse performance problems, memory leaks and security weaknesses in the back end.
  • Define guardrails so that generated back-end code meets your standards for validation, logging and error handling.

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: Node.js Back End
  • API endpoints from specifications
  • Database access and migrations
  • Integration tests with Testcontainers
  • Restructuring Express applications
  • Analysing performance and memory leaks
  • Security hardening
Module 7 Data protection, quality & transfer to daily work
  • Back ends often process personal data: production data, logs and database dumps should never go into prompts unfiltered, and credentials from environment variables must stay excluded. Vet new npm dependencies for supply-chain risk and licensing, and for critical services take the security requirements of NIS2 into account.
  • 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

API endpoints from specifications

From an OpenAPI or GraphQL schema, the agent generates routes or resolvers, validation with Zod or class-validator, service layers and consistent error responses – all matching your existing project structure.

Database access and migrations

The AI models schemas for Prisma, Drizzle or TypeORM, writes migrations, optimises queries with indexes and transactions and explains the impact on existing data before rollout.

Integration tests with Testcontainers

The assistant writes tests that spin up real databases, Redis or message brokers in containers, seed data and exercise API endpoints end to end with Supertest against realistic dependencies.

Restructuring Express applications

Monolithic Express projects are split into modules with controllers, services and repositories, middleware is standardised and callback code moved to async/await – backed by existing and new tests.

Analysing performance and memory leaks

The AI interprets heap snapshots, profiler output and logs, identifies operations blocking the event loop and proposes fixes such as streams, worker threads or caching.

Security hardening

The agent reviews authentication flows using JWTs or sessions, adds rate limiting, secure HTTP headers and input validation and checks the code against the OWASP API security risks.

Possible hands-on projects

Webhook relay service

A Fastify service that receives webhooks from various SaaS providers, verifies signatures, queues events and forwards them to internal systems with retry logic.

Job queue with dashboard

A background-processing service built on BullMQ and Redis, with retry strategies, a monitoring UI and integration tests. Failed jobs can be inspected and retried directly from the UI.

API gateway prototype

A lean gateway service with authentication, rate limiting, request logging and routing to several back-end services, developed entirely by an AI agent.

Prerequisites

You have several years of development experience, are confident with Git, testing and CI, and ideally have already used AI coding tools. Back-end development experience with Node.js and JavaScript or TypeScript, plus a working knowledge of databases, HTTP 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

Back ends often process personal data: production data, logs and database dumps should never go into prompts unfiltered, and credentials from environment variables must stay excluded. Vet new npm dependencies for supply-chain risk and licensing, and for critical services take the security requirements of NIS2 into account.

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 Bremen Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Online Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Salzburg Request
  • Tue, 9 February 2027 – Wed, 10 February 2027 Online Request
  • Wed, 24 February 2027 – Thu, 25 February 2027 Kaiserslautern 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.

Is the course suitable for both NestJS and Express?

Yes. We work with framework-neutral principles such as layering, validation and testability, and show with examples how to capture the conventions of Express, Fastify or NestJS in instruction files. That way the assistant generates code that fits your framework and your project structure rather than generic boilerplate.

How do I stop the AI from producing insecure back-end code?

Through clear rules, automated checks and critical review. On the course you define security rules for validation, authentication and data access, plug in static analysis and dependency scanning, and learn to spot typical weaknesses in generated code, such as missing authorisation checks or unsafe queries.

How much does “Agentic Coding for Node.js Back-End 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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