14:00 - 14:45

As you move into Senior+, Tech Lead, or Engineering Manager roles, your calendar fills up fast, and your time to actually build steadily shrinks. Yet your responsibility for technical outcomes, architectural decisions, and knowledge sharing doesn’t disappear.

This talk shows how an AI-Native Software Development Lifecycle, powered by Kiro, can become a real leverage for senior engineers and engineering leaders.

Through a hands-on story of vibecoding between meetings, we’ll explore a practical setup designed for the challenges that dominate senior roles: problem framing, architectural reasoning, documentation, and alignment. We’ll build a first MCP server / Kiro power and show how AI can amplify impact - helping us learn faster, reduce cognitive load, and keep architecture and documentation in sync with reality, even when hands-on time is scarce.

While the focus is on Senior+ and Engineering Manager workflows, the tools and patterns shown are just as valuable earlier in a career, offering a powerful boost for learning, exploration, and day-to-day development, and you’ll leave with concrete examples and a repeatable blueprint for applying an AI-native SDLC in your own context.

OpenPrime is a platform that allows non-experts to design and deploy production-ready AWS infrastructure using Infrastructure as Code.

Through a guided ClickOps experience and an AI assistant, users define what they need, while OpenPrime automatically generates best-practice, auditable IaC that follows proven architectural, security, and operational standards. The result is consistent, maintainable AWS infrastructure without requiring deep AWS or Terraform knowledge.

Food and drinks are two of my major hobbies, and I love mixing cocktails at home. But when I host friends, I always end up as the menu. People keep asking what I have and what I can make.

In this talk I will show how I built an AI bartender on AWS that lets guests interact with a drink menu using natural language. Instead of listing options or explaining what’s available, guests can ask for things like “something fruity” or “a gin drink”, and the AI Bartender respond with suggestions powered by Amazon Bedrock.

We will go deep into how I built the AI agent with Amazon Bedrock using Strands Agents, and AgentCore providing conversation memory, identity, and a gateway for tool access. I’ll show how streaming responses, with Amazon API Gateway, are implemented for a great chat experience. MCP tools play a important role providing the agent with data, like ingredients, and menu stored in Aurora DSQL. Finally how serverless and event-driven patterns are used to decouple AI processing from APIs.

This is a technical, demo-heavy session with code walkthroughs and architecture deep-dives. We will explore agentic AI with tool calling workflows, conversation memory, and event-driven AI integration. You’ll walk away with insights on how to build intelligent, context-aware AI assistants that work with real data on AWS.