CF

Agentic AI Coding

2h 51m 16s
English
Paid

Agentic AI Coding is a 12-lesson 2 hours 51 minutes self-paced course by Zen van Riel. Welcome to the course dedicated to modern software development methods using AI tools.

Course facts

Lessons
12
Duration
2 hours 51 minutes
Level
All levels
Language
English
Updated
Instructor
Zen van Riel
Price
Premium

Welcome to the course dedicated to modern software development methods using AI tools. In this course, you will master practical engineering strategies that will significantly accelerate the process of creating production-ready code without sacrificing quality.

About the Course

The course is focused on real-world tasks and reflects the experience of senior-level engineers — from startups to large corporate projects. You will gain universal approaches and a mindset that can be applied in any development environment, without being tied to a specific technology stack or project.

What You Will Gain

  • Practical methods for accelerating development with AI.
  • Approaches to creating production-ready code.
  • Engineering mindset and strategies applicable to various types of projects.
  • Skills for integrating AI into the developer's everyday workflow.

Who is the Course For

  • Developers wishing to increase productivity using AI.
  • Engineers working in startups and enterprise environments.
  • Those who strive to implement AI in their current projects.
  • Beginners with basic programming knowledge seeking a practical entry point.

Important Information

To complete the course, it is not required to work on the same projects as the instructor. The main focus is on strategies and approaches that you can adapt to your own tasks.

If you don't have your own project yet, we recommend starting with a practical assignment — for example, developing an application such as a transcription service, to immediately apply the knowledge gained in practice.

Additional

  • https://github.com/AI-Engineer-Skool/local-ai-transcript-app
  • https://github.com/AI-Engineer-Skool/prompt-vault/tree/main

Who teaches Agentic AI Coding? Zen van Riel

Zen van Riel thumbnail

I am focused on creating AI systems that truly work in production, rather than remaining at the demo level.

As a software engineer, I work on scaling real AI solutions in production at GitHub, and I also teach developers how to adapt to the future by practically implementing artificial intelligence.

Besides my main work, I am developing AI Native Engineer — my YouTube channel and community, where I share applied AI development skills.

My experience:

  • Over 5 years of developing and implementing cloud solutions
  • Deep expertise in LLMs, cloud architecture, and full-stack AI systems
  • Experience in creating and scaling AI products

I am convinced that the best engineers use AI not only as a tool to accelerate development but also as a foundation for creating new features and AI-native platforms that solve real problems.

What lessons are included in Agentic AI Coding?

This is a demo lesson (10:00 remaining)

You can watch up to 10 minutes for free. Subscribe to unlock all 12 lessons in this course and access 10,000+ hours of premium content across all courses.

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#1: 001 Module Introduction
All Course Lessons (12)
#Lesson TitleDurationAccess
1
001 Module Introduction Demo
00:35
2
002 How to code with AI like a pro
17:28
3
003 Beginner Git Workflow
12:12
4
004 Product Engineer Masterclass
26:00
5
005 Learn any technology faster with AI
10:05
6
006 Intermediate Git Workflow
18:37
7
007 Spec-based AI Coding in the Terminal
21:01
8
008 AI Context Engineering
12:19
9
009 AI Agent Hands-Free Mode
07:47
10
010 AI Test Driven Development
15:20
11
011 Auto-updating AI Agent Memory
12:33
12
012 Auto-updating Repo Documentation
17:19
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Frequently asked questions

What prerequisites are needed for this course?
The course is designed for beginners with basic programming knowledge. It assumes familiarity with general coding concepts but does not require expertise in a specific technology stack. Some understanding of version control systems, like Git, will be beneficial, as the course includes lessons on Beginner and Intermediate Git Workflows.
What kind of projects will I be working on in this course?
The course emphasizes strategies and approaches adaptable to various projects rather than specific project completion. However, it suggests starting with practical assignments like developing a transcription service to immediately apply the learned strategies to real-world tasks.
Who is the target audience for this course?
This course is intended for developers who wish to increase productivity using AI, engineers working in both startups and large enterprises, and beginners with basic programming knowledge seeking to integrate AI into their workflow. It is ideal for those looking to implement AI tools in their current projects.
How does this course compare in depth and scope to similar courses?
This course focuses on universal engineering strategies and an adaptable mindset rather than a specific technology stack. It covers practical methods for accelerating development with AI, which can be applied to any project, offering a broader application scope compared to courses tied to specific tools or environments.
What AI tools and techniques are covered in the course?
The course includes lessons on coding with AI, AI Test Driven Development, AI Context Engineering, and using AI Agents in a hands-free mode. It provides strategies for integrating AI into everyday developer workflows, emphasizing practical applications over theoretical knowledge.
What topics or skills are not covered in this course?
The course does not focus on specific technology stacks or the development of particular projects alongside the instructor. It also does not cover advanced programming languages or frameworks extensively, as the emphasis is on strategies that can be adapted to a wide range of projects.
What is the expected time commitment for completing the course?
The course consists of 12 lessons of unspecified duration. The time commitment will vary based on your engagement level with the practical assignments and the application of strategies to your own projects. As it is self-paced, completion time depends largely on individual learning speed and project complexity.