Podcasts

The Myth of 100% Utilization: The Neuroscience of Productive Teams

In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Shannon Mason about optimizing team productivity by understanding the neuroscience behind cognitive load, distinguishing between beneficial "slack time" and detrimental "idle time", and how the pursuit of maximum utilization that leads to burnout and poor decision-making.

Why Software Development Sucks And 7 Mental Models To Help Fix It

Shane Hastie, Lead Editor for Culture & Methods, spoke to Thanos Diacakis about how teams often struggle with software delivery. He proposes a shift in mental models and a four-step framework to systematically improve software development by focusing on bottlenecks, balancing different types of work beyond just feature delivery, and investing 20-30% of effort in improving how the team works.

Finding Your Engineering Bottleneck: The Hierarchy of Engineering Needs

In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Myles Henaghan about the open-sourced "Hierarchy of Engineering Needs" - a systematic framework inspired by Maslow's hierarchy that helps engineering leaders identify and prioritize the most impactful constraints limiting their software delivery systems among competing improvement initiatives.

Building Human-Centered Engineering Cultures with Leadership, Diversity, and Trust

In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Tara Hernandez about the importance of building generative cultures with strong leadership development, psychological safety, diversity, and transparency over simply chasing new technologies. Technology should be a means to solve meaningful human problems rather than an end in itself.

Building a Product-First Engineering Culture in the Age of AI

In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Zach Lloyd about building a product-first engineering culture, and the critical importance of developers learning to effectively use AI tools while maintaining responsibility for code quality and understanding fundamental programming principles.