AWS Kiro Course: Spec Driven Agentic AI Coding - 2026 (Udemy.com)
Build features with spec-driven development in AWS Kiro. Hands-on steering files, skills, MCP servers, hooks and CLI
Created by: Alex Dan
Last updated September 2026
What you will learn
- Turn a single prompt into requirements, design and task documents using Kiro's spec-driven development workflow
- Write steering files that force every Kiro response to follow your project's coding standards and conventions
- Build custom Kiro skills from SKILLmd, including skills that run your own Node.js scripts to save time and tokens
- Configure MCP servers in mcp.json and connect Kiro to live data, including the official AWS MCP server
- Use Kiro Powers to load only the tools a task actually needs instead of bloating your context with every MCP tool
- Create custom agents with scoped tool access, per-agent model selection and pre-approved permissions
- Automate your workflow with agent hooks that fire on file changes, tool calls and prompt submissions
- Run Kiro from the terminal with Kiro CLI, using slash commands, JSON agents and parallel sessions
How it compares
Against the other 518 rated Udemy courses in Software Development on CourseDuck:
- Rating4.6 out of 5higher than 62% of them
- Reviews2,692#68 of 519 by number of reviews
- Length2.9 hoursshorter than 80% of them
- Last updatedSeptember 2026more recently than 97% of them
Course Description
AWS Kiro is Amazon's agentic IDE — a VS Code fork built around spec-driven development. Instead of turning your prompt straight into code, Kiro writes a requirements document, a technical design and an ordered task list that you review and edit before anything is built.
This course covers every major Kiro feature, hands-on: spec-driven development with requirements md, design md and tasks md; EARS acceptance criteria; steering files that enforce your coding standards; custom skills built from SKILLmd; MCP servers configured in mcp json, including the official AWS MCP server; Kiro Powers for controlling context bloat; custom agents with scoped tools and permissions; agent hooks; and the Kiro CLI.
You start by installing Kiro IDE and signing in with an AWS Builder ID, and finish running Kiro from the terminal in parallel CLI sessions. Each concept gets a short explanation, then we build it live: a steering file that forces AI-generated constants into your naming convention, a skill that runs a Nodejs script, a hook that blocks a tool call on a keyword, an agent restricted to commands you pre-approve.
All code, generated spec documents and prompts are attached as downloadable resources. Optional lectures on VS Code basics and agentic AI fundamentals are marked, so you can skip what you already know.
What you'll learn
Spec-driven development — turn a prompt into requirements, design and task documents, write acceptance criteria in EARS syntax, and let Kiro build a dependency graph that runs tasks in parallel waves. You'll also learn when to use plan mode instead.
Configuring Kiro — generate project steering documentation, then write custom steering with conditional inclusion that activates only on matching files. Build skills from scratch, including one that executes your own script.
MCP and Kiro Powers — what the Model Context Protocol solves, how to configure servers at workspace or user scope, and how to install the official AWS MCP server so Kiro answers from current AWS documentation. Then use Powers to stop stacked MCP servers from destroying your context window.
Agents, hooks and the CLI — scope agents to specific tools, models and permissions; automate with hooks that fire on file changes, tool calls and prompt submissions; and run everything from the terminal with Kiro CLI.
An honest note on scope
This is a deep course on Kiro, not an app-building bootcamp — the hands-on work uses a small Vite and React project as a vehicle for learning the tool, so you can apply it to any stack. You'll also see Kiro's rough edges: where a feature was buggy at recording time, I say so and show the workaround.
Instructor Details
- 4.6 Rating
2,692 Reviews
Alex Dan
Alex Dan — Cloud Architect, Developer & Instructor
With over a decade of hands-on software engineering experience, I've built my career at the intersection of cloud infrastructure, web development, and practical education.
My technical journey started in embedded automotive systems — developing Java-based navigation solutions for major car brands. From there, I moved into cloud engineering, building AWS-powered data pipelines for connected vehicles using Node.js, TypeScript, Lambda, DynamoDB, and a full suite of AWS services. I later worked as a Node.js developer at one of Eastern Europe's largest e-commerce platforms, before transitioning into independent cloud architecture consulting.
Today, as a freelance Cloud Architect, I design and implement scalable cloud solutions across industries — from automotive to enterprise — with a focus on infrastructure reliability, CI/CD automation, and modern serverless architectures.
Parallel to my engineering career, I've been teaching on Udemy since 2017, growing a community of over 300,000 students across 19 courses. My current focus is AI-assisted development — helping developers work smarter with tools like GitHub Copilot, VS Code AI extensions, and agentic coding workflows.
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Reviews
By Jose Luis Aused on 9/24/2026
Muy buen curso introductorio para entender todas las herramientas que nos da kiro. Luego queda en nosotros en explotar todas las tools
By Yatindra Srivastava on 6/30/2026
good for new learning.
By Ramu Arumugam on 6/8/2026
The Amazon Q Developer for Programmers and DevOps course was a good match for my background and learning goals. I wanted to understand how AI-assisted coding can improve software development and operational workflows on AWS, and the course provided practical examples that helped me get started. I found the hands-on exercises particularly valuable because they demonstrated how Amazon Q Developer can assist with code generation, code explanations, troubleshooting, and AWS-related tasks. The course was most beneficial for someone with some programming or DevOps experience, as it builds on existing technical knowledge. Overall, I found it informative and relevant to modern development practices.
By Jonathan Saddler on 5/28/2026
The lectures toward the end in the terraform section: good content but sometimes the projects did not deploy all the way (ran with Hashicorp Terraform in mid-2026), and some manual work had to be done to get the Python example to work. Otherwise, really tries to sell the power of AmazonQ developer. I used IBM Bob to run the tutorials.
By Anonymized User on 5/25/2026
As an RTE and former developer, this material gave me some insight into the challenges being faced by the software development engineers in my domain's delivery team. I can now help the SM's better serve the SDE's in the squads.
By Mehul Kanojiya on 4/17/2026
Impressive point of this course is it covers a wide range of techstack.
By Jean-Louis VEREECQUE on 4/2/2026
Really nice course on Amazon Q Developer. Instructions and examples are very useful and clear to follow. I like the multiple use cases approach. A very good introduction for those discovering Amazon Q developer.
By Charlotta Langner on 1/20/2026
Good and clear explanations about what an AI assistant really is.
By Larry Earl Donald on 1/18/2026
This course was just incredible! I am new to Amazon Q Developer and this course was exactly what I needed to get me started.
By Lefteris Chaniotaks on 10/28/2025
Excellent course on Amazon Q Developer, the instructions and examples are very useful and clear to follow. I especially like the multiple use cases approach, from simple coding assistance to CI/CD and Terraform. You can apply all the learniings and examples with the free version of Amazon Q Developer.
Quality Score
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Overall Score : 92 / 100









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