AI is evolving at a breakneck speed, leaving engineering leaders with a critical dilemma: innovate or fall behind. But how do you experiment with AI without risking your credibility? Andrew Zigler sits down with Adnan Ijaz, Director of Product Management for Next Gen Developer Experience at AWS, to unpack the power of AI agents. Together they discuss how to leverage autonomous AI in your development workflow, and learn from real-world examples like Amazon Q. Dive into the evolving role of the developer and discover how to mentor your AI, not just use it. It's time to shift from task-oriented coding to strategic architecture, and this episode shows you how. But first, co-host Dan Lines frames the conversation by discussing the shift towards measuring the concrete benefits of AI tools in development, rather than just their potential. Dan also provides examples of how to set realistic expectations for AI implementation by focusing on specific tasks and measuring both individual and workflow improvements, highlighting the need for overall workflow optimization. Check out: Translating DevEx to the Board Beyond the DORA Frameworks Introducing AI-Powered Code Review with gitStream Follow the hosts: Follow Ben Follow Andrew Follow today's guest(s): Adnan Ijaz Amazon Q Developer OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.
