Systems | Development | Analytics | API | Testing

AI is so much more than that—it spans numerous fields, from machine learning to predictive analytics, computer vision, natural language processing, and beyond. Are we narrowing the conversation too much? Check out the full episode for more insights.

Welcome to Episode 6 of The Innovation Blueprint! This time, we’re diving deep into the impact of AI, data, and digital tools on real estate investment and business scaling. Our guest? Sean Everett, CEO of Evergence — a company that helps executives and boards tackle tough scaling challenges through acquisition and innovation. With decades of experience leading AI-driven growth strategies for Fortune 500s, private equity, and high-growth startups, Sean has built products used by billions, attracted acquisition interest from Apple and Box, and driven explosive business growth.

Are AI tools really helping developers, or are they creating more problems than they solve? In this episode of Test Case Scenario, Jason Baum, Marcus Merrel, and Evelyn Coleman are joined by Titus Fortner, Senior Solutions Architect at Sauce Labs, to unpack the surprising findings from the latest DORA report. Together, they dive into the unexpected decline in productivity following AI adoption and discuss the challenges developers face in balancing automation, innovation, and collaboration.

AI was hyped as the big solution to developer productivity, but the 2024 DORA report paints a different picture. Here’s what’s holding teams back: Developers don’t need help writing code—they need time to write it. AI isn’t clearing their calendars of endless meetings. Tech debt and documentation remain roadblocks, and AI tools aren’t solving them. AI can assist, but it often acts like a junior dev—adding more work instead of reducing it.