Agentic coding fundamentals for developers
Learn a tool-agnostic system for applying AI agents in daily development work, with clear context, instructions, and validation loops that reduce risk, tech debt, and confusion.
Built from real-world development experience and designed to stay useful as tools and models change.
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A practical path through agentic coding fundamentals
Each module focuses on evergreen fundamentals so you can build a personal system for working with AI agents across tools, models, and environments.
Course introduction
What you can expect from the course, why it exists, and which practical experience shaped it.
- Welcome to AI Fundamentals
- Why I created this course
- My journey to agentic coding
Understanding agentic coding
How you build a clear mental model of agentic coding before touching workflows or tools.
- What is Agentic Coding?
- What are AI Agents?
- Agentic coding vs. autocomplete and AI coding assistants
- Why agent guidelines matter more than code
- How agentic coding changes the way you build software
The agentic coding mindset
How you prepare for the mental shift and risks of agentic coding.
- Preparing yourself for a mental shift
- Code less, build more
- Why agentic coding intimidates senior developers
- Treat your agents like junior hires
- Garbage in, garbage out
- Shipping code you didn’t read
- The risk of rapid tech debt
- Deep work in an agentic workflow
Getting started with agentic coding
How you pick an entry point, choose your tools, and get the sample project running without overthinking.
- The AI development tooling landscape
- How to pick your agent of choice (Codex, Claude, Cursor, etc.)
- CLI vs IDE: Which fits you?
- Local vs cloud agents
- Choosing the right model for the task
- Setting up the sample project
Task context, prompts, and execution
How you use the core mechanics that determine whether agents succeed or fail.
- What is a task context?
- Understanding task context limitations
- Understanding tokens and what they cost
- Prompting techniques that save context and tokens
- What is a prompt (and what is it not)?
- Different modes of execution (plan, execute)
- Plan, review, execute, review, compound
- Recursive work and recursive tasks
Building and improving agent instructions
How you systemize experience into reusable agent behavior.
- Why agent instructions matter
- AGENTS.md
- Agent skills (local and public)
- AGENTS.md vs. agent skills: When to use which
- Using agent skills to apply coding principles
- What are MCPs and when do they matter?
- Adding MCP servers
- Why documenting context matters more than ever
Validation, safety, and feedback loops
How you make agentic coding safe, scalable, and production-ready.
- Preventing tech debt by cleaning up frequently
- Commits as checkpoints
- Independent code reviews after a task
- Using linters and formatters
- Giving AI eyes
- Adding AI validation: builds, warnings, and errors
- Lint, format, test, fix
- Security, privacy, and redaction
- Comparing your result against the final project
Scaling across projects and environments
How you apply agentic coding beyond a single repository or project.
- Creating reusable commands
- Running agents in parallel
- Maintaining best practices across multiple projects
- Cross-repository tasks
- Should you use a monorepo?
- Strategic decisions with agentic coding in mind
- Spotting wasted time and optimizing your workflow
- Preparing prompts with prompts
Wrapping up and certification
How you turn the course into a personal agentic coding system and complete your certification.
- Reflecting on your agentic coding system
- Obtaining your certificate
A clear way to learn agentic coding
Designed for experienced developers who want reliable practices they can reuse as tools and models change.
Text-based lessons
Direct explanations, examples, and checklists focused on applying agentic coding in real development work.
Interactive Quizzes
Quick checks to confirm understanding of the core concepts and workflows.
Video Explanations
Short walkthroughs that show how to apply the fundamentals without relying on any specific tool.
Frequently Asked Questions
Is this course suitable for beginners?
Yes. This course is designed as an entry point if you feel overwhelmed by how fast AI moves. You will leave with a clear, repeatable way of working.
What are the prerequisites for this course?
Basic programming knowledge is helpful, but no prior AI experience is required. The course focuses on fundamentals that apply to any development workflow.
How long will I have access to the course materials?
You get lifetime access to all course materials, including future updates and new content.
Can I get a refund if I'm not satisfied?
Yes, we offer a 14-day money-back guarantee. If you're not satisfied, we'll provide a full refund.
Is there a certificate of completion?
Yes, you will receive a certificate of completion after finishing the course.
Does it matter which tools (Codex, Cursor, etc.) I use?
No. The course is tool-agnostic and focuses on fundamentals that apply no matter which agent or editor you prefer.