Software Engineering Radio - the podcast for professional software developers

Sahaj Garg, co-founder and CTO of Wispr, a voice-to-text AI that turns speech into polished writing, talks with host Amey Ambade about designing systems for the ambiguity that's inherent in human input (text, voice, multimodal). Sahaj focuses on concrete architectural and training strategies for building robust AI systems. This episode examines the problem of ambiguity, where it shows up, building robust systems, personalization, communicating uncertainty, and evaluation. The conversation starts by exploring the difference between inherent and reducible ambiguity, major categories of ambiguity including lexical, syntactic, and pragmatic, and the additional sources of ambiguity in voice, such as homophones and accents. Garg details how to build systems through model training, including providing additional context and constructing datasets for good annotation. They discuss personalization with a focus on "revealed preferences"—learning from user behavior without explicit feedback—and fighting the problem of AI writing that "regresses to the mean." Finally, they consider how to communicate uncertainty to users without degrading the experience, as well as methods for evaluating ambiguity resolution through offline and online signals.

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.