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AI Agents in Modern Software Development Workflows
Rating: 4.7 out of 5(17 ratings)
122 students

AI Agents in Modern Software Development Workflows

Master AI agent workflows from local setup to real-world integrations
Last updated 4/2026
English

What you'll learn

  • Build and deploy AI agents using n8n to automate real software development workflows, from local setup with Docker to production-ready deployments.
  • Integrate Claude, OpenAI, Gemini, and open-source models into automated workflows that process data, call APIs, and make intelligent decisions.
  • Design multi-step agent systems with tools, memory, error handling, and webhooks that connect directly to your existing software stack.
  • Expose n8n workflows as production APIs and automate content pipelines, bots, transcription, and developer tasks that save real engineering hours.

Course content

4 sections5 lectures1h 0m total length
  • Install n8n with Docker - Complete Setup Guide8:16
  • Introduction to n8n Workflow Builder9:37

    Learn to build a low-code chatbot workflow in n8n using a chat message trigger, an AI agent with OpenAI, memory for context, and templates to accelerate development.

Requirements

  • No coding experience required! Just bring a computer, willingness to learn, and curiosity about automation. Basic computer skills are enough to get started.

Description

Stop Writing Glue Code. Start Shipping AI Agents.

Modern software development isn't just about writing code anymore, it's about orchestrating intelligent systems that build, test, deploy, and maintain software alongside you. AI agents are quickly becoming the new backbone of developer productivity, and the engineers who know how to integrate them are pulling ahead.

This course teaches you exactly how to do that, using n8n, the leading open-source automation platform built for developers who want real control over their workflows.

What You'll Learn

You'll start by setting up a professional n8n environment with Docker, giving you a local playground that mirrors production. From there, you'll master the n8n workflow builder and learn the architectural patterns behind every serious AI agent system: triggers, tools, memory, error handling, and deployment.

Then you'll build. A lot.

You'll create AI agents that transcribe audio, process documents, and extract structured data from unstructured input. You'll build conversational interfaces with Telegram, Slack, and webhook-driven APIs that plug directly into your existing stack. You'll automate content pipelines, code review workflows, CI/CD notifications, database operations, and internal developer tools.

You'll learn how to connect n8n to Claude, OpenAI, Gemini, and open-source models, how to give agents the right tools, how to design multi-agent systems that actually work, and how to expose your workflows as production APIs that other services can call.

You'll also learn the hard parts most tutorials skip: authentication, error recovery, rate limiting, observability, versioning, and deploying n8n on your own infrastructure.

Why This Course

n8n isn't a toy. It's a serious orchestration layer that connects hundreds of services, APIs, and AI models, and it fits perfectly into a developer's workflow. Instead of writing the same integration code over and over, you'll build once, reuse everywhere, and ship features in hours instead of weeks.

Whether you're a backend engineer exploring AI, a technical founder racing to ship, a DevOps practitioner automating operations, or a developer who wants to stop wasting time on boilerplate, this course gives you a complete system for integrating AI agents into the way you actually build software.

By the end, you'll have built a portfolio of real workflows, understood the patterns behind production-grade AI systems, and gained the skills to deploy intelligent automations that save your team real engineering hours.

No prior n8n experience required. Basic familiarity with APIs and development concepts will help you move faster.

Who this course is for:

  • Backend and full-stack developers who want to integrate AI agents into their projects without writing endless glue code.
  • Technical founders and indie hackers who need to ship AI-powered features fast without hiring a full engineering team.
  • DevOps practitioners and automation engineers looking to orchestrate intelligent workflows across APIs, services, and AI models.
  • Software engineers tired of repetitive integration work who want to build once and reuse across projects.