Podcasts

Context is the Key to the Agentic Architecture Revolution: a Conversation with Baruch Sadogursky

Michael Stiefel spoke to Baruch Sadogursky about software architecture in the age of agentic AI. LLM can function, albeit stochastically, as reasoning machines capable of interpreting human ambiguity. With the appropriate rigorous context artifacts to control the LLM’s reasoning, software specifications can become the source of truth, while the code becomes a disposable intermediate language.

From Java EE to Quarkus and LLMs: Adam Bien’s Playbook for Boring, Future‑Proof Systems

Adam Bien, an independent consultant and pioneer of zero dependencies in the enterprise world of Java, highlights the benefits of consistently using standards, regardless of whether they involve Java or existing patterns. He argues that by doing so, he managed to future-proof the systems he built, preparing them for the cloud era and even for the AI-Native era.

Roq: Leveraging Quarkus to Build Static Sites at the Speed of Go

Andy Damevin, a developer who worked on Quarkus for almost a decade, talks about Roq, a project that started as an experiment to try to see if it’s possible to build a static web site generator on top of quarkus. He touches on the rationale for choosing Java and Quarkus, how to migrate to Roq, and the platform's future.

A Java Performance Quest: Taming Unsafe Code, Embracing Idiomatic Style & Debugging the Linux Kernel

In this podcast, Jaromir Hamala, a seasoned Java engineer specialising in high-throughput data systems, shares his thoughts on how developers can tackle high-performance software development. He touches on the benefits of modern Java that allow writing idiomatic Java code while remaining "mechanically sympathetic", and also on his experience debugging a Linux kernel bug.

Engineering Stable, Secure and Scalable Platforms: a Conversation with Matthew Liste

In this podcast, Michael Stiefel spoke to Matthew Liste about building and managing software platforms. Platform services act as the basis for application development, and must always be stable, secure, and scalable. Scaling these systems is particularly difficult because unknown resource contention often causes them to break.

Using Brain Science to Communicate and Lead Technical Teams Effectively

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Charlotte de Jong Schouwenburg about how understanding brain science and emotional intelligence can help engineers and technical leaders improve communication, manage conflict, and build stronger teams.

Building Engineering Culture Through Autonomy and Ownership

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Marcos Arribas about building and scaling engineering culture as an organisation grows, emphasizing autonomous teams, ownership mentality, progressive feature rollouts with flags, small pull requests, strategic AI adoption, and the importance of hiring junior engineers for long-term organizational growth.

How Blameless Culture Transforms Engineering Teams

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Tameem Hourani about building a blameless engineering culture through radical transparency, focusing on system resilience over individual blame, and creating high-performing teams that can embrace change and learn from failures.

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.