Software Engineering Radio - the podcast for professional software developers

Costa Alexoglou, co-founder of the open source Hopp pair-programming application, talks with host Brijesh Ammanath about remote pair programming. They start with a quick introduction to pair programming and its importance to software development before discussing the various problems with the current toolset available and the challenges that tool developers face for enabling pair programming. They consider the key features necessary for a good pair-programming tool, and then Costa describes the journey of building Hopp and the challenges faced while building it.

Héctor Ramón Jiménez, creator of iced, an Elm-inspired, cross-platform GUI toolkit for Rust, speaks with SE Radio host Gavin Henry about building a GUI library in Rust. Héctor discusses why he created iced, what was needed, the process required to paint on the screen across different operating systems, how multi-operating systems are handled, and what the iced testing ecosystem is like. This episode explores the Elm architecture, how iced compares to other frameworks, what the core components of iced are, Elements, asynchronous functions, state, threads, 3d rendering, headless mode testing, end-to-end testing, test recorders, runtime emulators, ice test syntax, example apps, tiny-skia, DirectX, Vulkan, Metal, winit, wgpu, egui, tauri, comet, and why Android and iOS support is hard.

Dan Lorenc, co-founder and CEO of Chainguard, joins host Priyanka Raghavan to explore Sigstore and its role in securing the software supply chain. They unpack the challenges of supply chain security, including verifying the origin and integrity of software artifacts, and explain the problems Sigstore is designed to solve. The conversation goes under the hood to examine how Sigstore works, covering key components such as code signing, verification, the certificate authority model, and transparency logs—often compared conceptually to blockchain for their auditability. The episode also highlights real-world adoption, community resources for getting started, and closes with a discussion of Chainguard Images and how development teams can use them to build with more secure base images.
This episode is sponsored by IEEE Computer Society.

Scott Hanselman, the VP of Developer Community at Microsoft, speaks with host Jeremy Jung about AI-assisted coding. They start by considering how the tools are a progression from syntax highlighting and autocomplete. Scott describes the ambiguity and non-determinism of agentic loops, why vague high-level prompts usually don't give good results, and the need to express intent and steer the models. He explains how knowing fundamentals helps you create better plans and know what to ask the models, and how to treat agents differently based on your knowledge level. He discusses his experience porting Windows Live Writer to a modern .NET stack, and defining success and providing tools for models to verify their work. Finally, he explains why you need to read and understand generated code in production environments, plus methods for sandboxing agents.

Marc Brooker, VP and Distinguished Engineer at AWS, joins host Kanchan Shringi to explore specification-driven development as a scalable alternative to prompt-by-prompt "vibe coding" in AI-assisted software engineering. Marc explains how accelerating code generation shifts the bottleneck to requirements, design, testing, and validation, making explicit specifications the central artifact for maintaining quality and velocity over time. He describes how specifications can guide both code generation and automated testing, including property-based testing, enabling teams to catch regressions earlier and reason about behavior without relying on line-by-line code review.
The conversation examines how spec-driven development fits into modern SDLC practices; how AI agents can support design, code review, documentation, and testing; and why managing context is now one of the hardest problems in agentic development. Marc shares examples from AWS, including building drivers and cloud services using this approach, and discusses the role of modularity, APIs, and strong typing in making both humans and AI more effective. The episode concludes with guidance on rollout, evaluation metrics, cultural readiness, and why AI-driven development shifts the engineer's role toward problem definition, system design, and long-term maintainability rather than raw code production.
Brought to you by IEEE Computer Society and IEEE Software magazine.