InfoQ Homepage Agile Content on InfoQ
-
Simplify Your System by Challenging the Status-Quo and Learning from Other Ecosystems
In this podcast, Max Rydahl Andersen, distinguished engineer at RedHat and the creator of JBang, discusses how continuously learning from other ecosystems and adopting new tools allows you to simplify your thinking and systems. This will increase the developer joy of the coders and further obtain safer and more robust systems.
-
Facilitating Software Architecture with Andrew Harmel-Law
In this episode, Thomas Betts speaks with Andrew Harmel-Law about his new book, Facilitating Software Architecture: Empowering Teams to Make Architectural Decisions. The conversation includes a discussion of what constitutes an architecturally significant decision, how the practice of architecture is evolving, and how architects have a role to facilitate software architecture.
-
Key Trends from 2024: Cell-Based Architecture, DORA & SPACE, LLM & SLM, Cloud Databases and Portals
In this year-in-review episode, Daniel Bryant, along with InfoQ podcast hosts Thomas Betts, Shane Hastie, Srini Penchikala, and Renato Losio, reflect on the trends and developments of 2024 across key domains: architecture, culture and methods, AI and data engineering, and cloud and DevOps.
-
Crossing the Feedback Chasm - a Conversation with Ken Finnigan
Michael Stiefel spoke with Ken Finnigan about how the lack of feedback impedes the development of software professionals. Without feedback, the right candidates are not hired, software professionals cannot improve or grow into new roles, or individuals stagnate or regress in their current positions. Feedback must also be delivered at the right time - when it can be effectively used.
-
Communication Patterns for Architects and Engineers with Jacqui Read
In this episode, Thomas Betts talks with Jacqui Read about communication patterns. Similar to software and architecture patterns, these provide guidance for how to improve communication by knowing your audience and what you need to explain to them.
-
Engineering Leadership: Building Culture, Career Growth, and Ownership
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Thiago Ghisi about building engineering culture through leading by example, advancing careers by embracing "glue work" (non-technical but necessary tasks), taking full ownership of projects, and developing self-awareness to choose between technical and management career paths.
-
Elisabeth Hendrickson on Systems Thinking for Quality Engineering
In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Elisabeth Hendrickson about using systems thinking to understanding relationships between problem elements rather than focusing on individual parts, and how quality engineering practices become even more critical in the age of AI where tools can accelerate code production but humans need to remain in charge of verification.
-
Team Building in the Brave New World: Transforming Software Engineering Culture and Leadership
In this podcast, Shane Hastie, spoke to Duncan Grazier about transforming software engineering teams into polymorphic cultures where humans work alongside AI agents, requiring leaders to rethink career paths, focus more on communication and coaching skills, and navigate the implications of how the gap between junior and senior engineers rapidly closes due to AI augmentation.
-
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.