Join AWS She Builds Tech Skills hosts, Brittany Wolfrom and Jane Ridge for an exclusive deep-dive into generative AI innovation with Parmida Atighehchian and Smita Bailur, expert builders and advisors from the AWS GenAI Innovation Center. Discover how leading organizations are successfully implementing AI solutions across industries and learn practical strategies you can apply today.

Our guests bring hands-on experience architecting and deploying GenAI applications for enterprise clients. They’ll share current industry trends, demonstrate real-world solutions, and provide actionable guidance for building your own GenAI applications on AWS.

What You’ll Walk Away Learning: 🎯

🏢 AWS GenAI Innovation Center Deep-Dive - How the team operates as both advisors and builders, working directly with organizations to solve complex challenges

📈 Industry Trends & Patterns - Latest GenAI developments and adoption patterns across sectors like healthcare, finance, and retail

💡Real Solutions - Case studies showing how GenAI solves actual business problems and drives measurable outcomes

⚒️ Live Demo - Hands-on demonstration of GenAI application development and deployment best practices

🎯 Implementation Strategy - Key architectural considerations, cost optimization, and scaling strategies for GenAI solutions

⚖️ Expert Best Practices - Technical and strategic recommendations from practitioners who’ve built dozens of production GenAI systems

Perfect for: Developers, architects, product managers, and technical leaders interested in practical GenAI implementation strategies and AWS AI/ML services.

Explore how you can leverage Kiro and Q CLI to elevates the quality of what you are building in a more efficient way. On this episode we will walk through a real-world example showing how Kiro's unique design → requirements → tasks workflow can be implemented. You will learn how Kiro breaks down complex specs into manageable, precise tasks while maintaining a holistic view of the project. The Q CLI integration showes how seamlessly these components work together, making it feel like having an expert architect guiding every decision

Key takeaway: This isn't just about coding faster—it's about building better. And it can be applied to any industry and scope of work.

Discover the cutting-edge world of Model Context Protocol (MCP) servers and how they're revolutionizing AI code assistants!

Join the AWS PACE team as they share their incredible journey from internal hackathon project to releasing 30+ open source MCP servers that are transforming how developers interact with AI assistants like Amazon Q Developer.

What You'll Learn:

🔧 Model Context Protocol Fundamentals - Understanding MCP and why it's the future of AI assistant integration

🚀 Real-World MCP Development - Live demos of AWS MCP servers in action with code assistants

📈 Open Source Success Story - How a team hackathon became a viral open source project featured in AWS blogs

⚡ AWS Service Integration - See MCP servers connecting AI assistants to AWS services seamlessly

🎯 Best Practices & Lessons Learned - Practical insights from building and maintaining 30+ MCP servers

🌟 Emerging Technology Focus - How the PACE team identifies and builds the next generation of developer tools

Featured Team:

Meet Alexa Perlov, Anita Lewis, and Jimin Kim from the AWS PACE team who've made MCP development their specialty, with extensive open source experience including their GenAI constructs library and numerous community contributions.

Perfect for: Developers interested in AI assistant extensibility, open source contributors, AWS developers looking to enhance their AI workflows, and anyone curious about the future of developer tooling and AI integration.