Engineering Managers and Staff+ engineers often share the same fate: back-to-back meetings while the builder inside silently screams. This talk explores how adopting an AI-Native SDLC helped me reclaim my building time: allowing me to learn a new topic, structure my exploration, and build a proof of concept in the gaps between meetings.
We’ll go from zero to deployed: starting with a simple stdio MCP server, evolving it into an HTTP MCP server, validating everything with the MCP UI Inspector, and finally deploying it on AWS using Agent Core Runtime. Along the way, we’ll lean on Kiro hooks, steering, and MCP servers to accelerate learning loops, automate documentation, and capture architectural decisions.
Whether you’re struggling to find time to build or simply want to use your time more efficiently, you’ll walk away with a practical blueprint for making AI a force multiplier across your engineering organization. And you’ll learn how Agent Core Runtime and Gateway make it possible to build, host, and operate powerful AI agents and MCP servers in minutes.