AWS AI & GenAI: Build with Amazon Q Developer & Kiro Basics

Karen shifts from easy coding to debugging with many errors, then adopts Amazon Q as a coding buddy for code completion, debugging, and auto completion, boosting productivity.

Define artificial intelligence as the simulation of human thinking in machines. Explain core components such as machine learning, natural language processing, and computer vision, and note real-world applications.

Explore GenAI, a class of generative artificial intelligence trained on large data sets to create text, images, and music that mimic training data, with applications in health care and gaming.

GenAI offers opportunities in healthcare, creative arts, and business, from diagnostic image generation to chatbots and analysis. Mitigate risks with ethical development, transparency, bias mitigation, quality data, and user education.

Discover how the Amazon Q developer enhances the AWS console with chat, debugging, and support features, including architecture best practices, error diagnosis, and seamless integration with Slack or Teams.

Learn to use the Amazon Q developer in the AWS console to query service details, view billing, and inspect resources across regions, including EC2, S3, and SageMaker.

Diagnose AWS errors with Amazon Q, analyze EC2 placement group issues, and learn the supported instance types—M1, M series, C series, R series, and X series—to resolve compatibility.

Learn to raise a support ticket in the AWS console using Amazon queue, including drafting the case, selecting account and billing or technical, and submitting with email, chat, or phone.

Explore how AWS Amazon Q developer can provide python code for a calculator in the console, covering plus, minus, multiplication, and division operations, including division by zero scenarios.

Explore how Amazon QDeveloper handles questions: it answers only AWS and coding related queries, not general knowledge, and shows how to access details about your AWS account and AWS services.

Discover how AWS Cairo powers an AI coding assistant that takes a project from prototype to production using natural language prompts to generate, review, and deploy code with testing.

Understand Kairos pricing and plans, from free starter and student credits to pro and enterprise tiers; credits vary by request type and model, including Sonnet and Claude.

Learn the four core components—steering, specs, hooks, and MCPs—and how they drive a workflow from natural language prompts through context enrichment, design, task generation, and maintenance.

Set up the Kyro2Dev console with identity center or external providers as Microsoft and Okta, invite users by email, and configure MFA with authenticator apps to access the AWS-based portal.

Install Cairo.dev, a VS Code-style IDE for Amazon Q, on macOS Apple Silicon. Sign in with Google, GitHub, or AWS Builder and import VS Code settings.

Begin your first interaction with the Amazon Q KyroDev IDE, write a simple Python calculator, and explore available models, autopilot, and the free credits offered.

Master steering to guide and refine AI outputs by setting prompts, constraints, and rules, using context awareness and a persistent project memory.

Discover how Cairo helps you understand code by cloning a GitHub repo and explaining each file. Choose vibe for testing or spec for requirements to build features.

Understand specs and specification based development, turning prompts into structured requirements, design, and architecture, reducing ambiguity and enabling production-ready code with verified tests and automated deployment.

Create and apply a spec to formalize artifacts and commands within a project, using prompts to define folder layouts, package.json scripts, and npm start, and illustrate running locally.

Create a custom spec in your project, enter details to generate requirements, and build features using credits. Follow the design workflow with design.md previews and architecture insights.

Engage in a specs workflow hands-on session to design a custom spec, generate requirements and a task list, and build end-to-end documentation covering fetch and render of the random fact.

Explore how to translate gathered requirements and design into executable tasks by generating a task list, creating and running tasks, checking test coverage, and committing changes to GitHub.

Explore agent hooks, the event-driven triggers that automate maintenance tasks like tests, documentation, and deployment by detecting events such as file changes and code commits.

Explore agent hooks in Cairo, compare manual builds with Cairo-based prompts, and watch end-to-end creation of a basic calculator in node.js with automated readme and docs updates.

Learn to set up MCP with AWS Labs and Cairo cli, load MCP servers, and configure workspace or user-specific MCPs for AWS resources and document summarization.

Explore how Amazon Q uses AI to help employees find information, solve tasks, and generate or debug code, while summarizing company data, with two dedicated and three integrations.

Explore a practical UI tour of the Amazon Cube to learn how its centralized Identity Center, subscriptions, and application management streamline access for users and groups.

Explore Amazon Q Developer as an AI-powered co-pilot that assists coding, diagnosing errors, and improving security, architecture, and AWS resource best practices across the AWS console, CLI, and IDE.

Discover how Amazon Q developer diagnoses AWS console errors and acts as a co-pilot to plan features, generate code, and transform Java eight to Java 17 in IDEs and chat.

Explore the AWS queue developer in the console, subscribe and manage users, review settings and the dashboard, and customize chatbot deployment features and visualizations across regions.

IAM roles enable secure authorization and authentication with service roles and service link roles, guiding least privilege access for EC2, S3, and auto scaling.

Learn how IAM policies define permissions for users, groups, and roles in AWS, using built-in and inline policies, attached to users or roles with JSON statements and conditions.

Attach IAM roles to services and users by creating or selecting roles, attach execution roles to Lambda and EC2, and use STS assume role with inline policies for access control.

Learn how to create and manage AWS organizations, structure accounts with organizational units, and apply service control and tag policies to manage access and resources.

Explore Amazon S3, a scalable, high-speed cloud storage service used as a data source in AWS, enabling storing and retrieving any amount of data from anywhere on the web.

Learn AWS Lambda, a serverless compute service that runs code as functions and auto-scales on events. Build, trigger, test, and monitor functions with Q developer, paying only for usage.

Harness IAM Identity Center to centrally manage users and groups across AWS accounts and applications, control permission sets, enable single sign-on, and secure access to resources.

Enable the IAM Identity Center to centralize identity management for multi-account AWS use, configure identity sources, enforce MFA, and manage permission sets, users, and groups across the organization.

Enable IAM Identity Center in a single AWS account and learn to create or remove AWS Organizations directly from Identity Center, suitable for proof-of-concept scenarios.

Learn how to create users in AWS IAM Identity Center, assign emails and names, add to groups, generate passwords or one-time passwords, and enable access for your application.

Enroll users in IAM Identity Center by guiding them through email or one-time password verification within seven days, set up MFA with the built-in macOS authenticator, and assign permissions.

Assign permissions in IAM Identity Center by creating predefined or custom permission sets, granting administrator or read-only access, and assigning users to AWS accounts.

Compare Amazon Q developer free and pro subscriptions: free provides basic AI tasks for individuals; pro offers unlimited usage, higher limits, advanced word generation and analysis, and enterprise-grade AWS integration.

Learn how AWS Builder ID enables single sign-on across services with MFA, centralizes access control, and how to create and use it for developer workflows.

Install the Amazon Q extension in VS Code, sign in with an Amazon Builder ID, choose free license, and browser authentication to access analysis, chat, software development, and code transformation.

Log in to the pro version in VS Code, authenticate via the console, complete MFA, and assign a pro developer subscription to a user.

Explore the functionality of Amazon Q in the IDE, including login, queue features, and code execution. Manage history, pause and resume auto suggestions, and access documentation and GitHub links.

Chat about code with Amazon Cube to understand, build, and transform code directly in your IDE; generate code, unit tests, explanations, and refactor for improved efficiency.

Discover how to use Amazon Queue in VSCode, run lambda code in Python, generate PHP hello world snippets, and learn Java variable declarations with practical code examples.

Explore how to manage, explain, refactor, fix, and optimize code using the Amazon Q developer in the IDE, with example Python projects and prompts.

Discover how AWS Amazon Q developer delivers real-time code suggestions and inline completions, with customization and line-by-line recommendations to accelerate single-line and entire function generation.

Learn to generate inline suggestions and code completions with Amazon Q developer and Codewhisperer in the AWS IDE, including files, boto3 imports, and S3 or DynamoDB functions.

Learn how Amazon Q Developer automates transforming Java code from older versions (Java 8/11) to Java 17, including building, verifying, transforming, testing, and reviewing changes.

Transform Java code from 8 to 17 using Amazon Q developer on AWS by uploading the project, building, reviewing proposed changes, and accepting updates to pom.xml.

Develop code with the Amazon Cube by explaining your feature and using slash dev to generate a context-aware implementation plan and code from your workspace.

Explore how the Amazon Q dev copilot generates code in VS Code, creating a Python calculator and supporting HTML and YAML CloudFormation templates, with workspace folder requirements and code updates.

Scan code with Amazon Q developer to test security and quality across the development cycle, discover and fix vulnerabilities via auto scans, findings descriptions, and automatic fixes.

Demonstrate scanning code with amazon q to detect, explain, and fix vulnerabilities in a project, using vscode, run project scan, and address high-priority issues.

Understand how the AWS chatbot integrates with Slack, Ms. Teams, and Chime to monitor AWS resources, deliver real-time alerts, and run CLI commands for CloudWatch and CloudFormation.

Configure AWS chatbot to connect Slack with Amazon Q developer using SNS behind the scenes. Set up a Slack channel with permissions and guardrail policies.

Discover Slack as a cloud-based collaboration tool for real-time messaging, file sharing, and integrations with tools like Google Drive, Trello, and Jira, using channels (public or private) and direct messages.

Learn how to install Amazon queue for the command line on macOS, enable CLI authentication via IAM Identity Center, and use suggestions and auto-completion to streamline daily tasks.

Explore the Amazon Q developer command line interface, focusing on autocompletion, chat, and translation. Configure themes, enable or disable options, and adjust appearance for streamlined workflows.

Explore how to chat with the amazon q command-line assistant using a natural language model to obtain history, git, and environment commands for efficient terminal work.

Learn to translate natural language into shell commands with Amazon Q command line interface, using translate to generate, edit, and execute commands like git reset and folder operations.

Discover how to debug Amazon queue issues from the command line with queue doctor and queue issues, auto-create GitHub issues, and use debug to diagnose apps.

Learn to use Amazon Q developer in Lambda to generate inline functions via code whisperer, and set up Lambda with Python or Node.js runtimes and IAM permissions.