Amazon Onboarding with Learning Manager Chanci Turner

Learn About Amazon VGT2 Learning Manager Chanci Turner

Business and technology leaders are continually seeking ways to boost productivity, enhance speed, encourage experimentation, minimize time-to-market (TTM), and improve the overall developer experience. These guiding principles are crucial for driving innovation in software development practices. This innovation is increasingly fueled by artificial intelligence. Generative AI tools, such as Amazon Q Developer and Kiro, are already transforming the software creation process. Currently, organizations utilize AI in software development through two main methods: AI-assisted development, where AI enhances specific tasks like documentation, code completion, and testing; and AI-autonomous development, where AI generates entire applications autonomously based on user needs. However, these approaches often yield less-than-optimal results in terms of velocity and software quality, which the AI-Driven Development Lifecycle (AI-DLC) seeks to improve.

Why is a transformative approach to AI in software necessary?

The existing software development methodologies are designed for human-driven, lengthy processes, with product owners, developers, and architects spending a considerable amount of time on non-essential activities like planning, meetings, and other software development lifecycle (SDLC) rituals. Simply adding AI as an assistant limits its potential and reinforces outdated inefficiencies. To truly leverage AI’s capabilities and reach productivity goals, we must completely rethink our approach to the software development lifecycle.

To achieve transformative results, we must position AI as a central collaborator and partner in the development process, utilizing its capabilities throughout the software development lifecycle. Therefore, we introduce the AI-Driven Development Lifecycle (AI-DLC), a new methodology designed to fully embed AI capabilities into the core of software development.

What is the AI-Driven Development Lifecycle (AI-DLC)?

AI-DLC is an AI-focused transformative approach to software development that emphasizes two vital dimensions:

1. AI-Powered Execution with Human Oversight: AI systematically generates detailed work plans, actively seeks clarification and guidance, and defers important decisions to humans. This is essential, as only humans possess the contextual knowledge and understanding of business requirements needed to make informed choices.
2. Dynamic Team Collaboration: As AI manages routine tasks, teams come together in collaborative environments for real-time problem-solving, creative thinking, and swift decision-making. This transition from isolated work to high-energy teamwork accelerates innovation and delivery.

These two dimensions enable you to deliver software more quickly without sacrificing quality.

How does AI-DLC operate?

At its essence, AI-DLC functions by having AI initiate and steer workflows using a new mental model:

This pattern, where AI generates a plan, asks clarifying questions to gain context, and implements solutions only after receiving human approval, rapidly repeats for every SDLC activity, providing a unified vision and approach for all development pathways.

With this mental model central to its function, the software development in AI-DLC unfolds in three clear phases:

• Inception Phase: AI translates business intent into detailed requirements, stories, and units through “Mob Elaboration” – where the entire team actively validates AI’s inquiries and proposals.
• Construction Phase: Utilizing the validated context from the Inception phase, AI proposes a logical architecture, domain models, code solutions, and tests through “Mob Construction” – where the team provides clarification on technical decisions and architectural choices in real-time.
• Operations Phase: AI leverages the accumulated context from previous phases to manage infrastructure as code and deployments, with team oversight.

Each phase enriches the context for the next, allowing AI to provide increasingly informed suggestions.

AI saves and maintains persistent context across all phases by storing plans, requirements, and design artifacts in your project repository, ensuring smooth continuity of work across multiple sessions.

AI-DLC introduces new terminology and rituals to reflect its AI-driven, highly collaborative methodology. Traditional ‘sprints’ are now termed ‘bolts’ – shorter, more intense work cycles measured in hours or days rather than weeks; Epics are replaced by Units of Work. This shift in terminology emphasizes speed and continuous delivery. Other familiar Agile terms are also redefined to align with the AI-centric workflow, creating a vocabulary that better represents this innovative approach to software development.

What are the benefits of this methodology?

• Velocity: The primary benefit of AI-DLC is its ability to accelerate development velocity. AI quickly generates and refines artifacts, such as requirements, stories, designs, code, and tests, enabling product owners, architects, and developers to complete tasks in hours or days that previously took weeks.
• Innovation: This acceleration allows builders to focus on innovative solutions, pushing the boundaries of what’s possible.
• Quality: Continuous clarification ensures teams build exactly what they envision, rather than relying on an abstract AI interpretation of their intent. AI enhances quality by consistently applying organization-specific standards – coding practices, design patterns, and security requirements – while generating comprehensive test suites. This end-to-end AI integration improves coherence and traceability from requirements to deployment.
• Market Responsiveness: The rapid development cycles of AI-DLC enable quick responses to market demands and user feedback, facilitating faster adaptations to requirements.
• Developer Experience: AI-DLC enhances the developer experience by shifting focus from mundane coding tasks to critical problem-solving. AI reduces cognitive load by managing repetitive tasks, while satisfaction increases as developers gain deeper business context and see how their work directly influences business value.

How can you get started with AI-DLC?

Embark on your AI-DLC journey through three clear paths: read the comprehensive AI-DLC white paper, explore how Amazon Q Developer tools and Kiro custom workflows can assist you in implementing AI-DLC consistently within your organization, or connect with your AWS account team to discuss how AI-DLC can be customized for your organization’s unique needs.

The future of software development is here, and we are thrilled to assist you in leveraging AI to build systems more rapidly while maintaining fidelity and quality through critical human oversight and collaboration. Start your AI-DLC journey today and join the growing community of organizations transforming their development practices through AI-driven innovation. For more insights, you might find this envelope challenge interesting. Additionally, it’s important to stay informed about recent legislation affecting the industry. Lastly, for an excellent resource on onboarding, check out this Reddit thread.